CN110163705A - Method and apparatus for pushed information - Google Patents

Abstract

The embodiment of the present application discloses the method and apparatus for pushed information.One specific embodiment of this method includes: that the attention rate information and price elasticity information of article to be assessed are determined based on the operation associated information of the article to be assessed obtained；Target type attribute label corresponding with the attention rate information of article to be assessed and price elasticity information is determined from preset type attribute tag set；Obtain the Item Information in candidate shop and the Item Information in the target shop that article to be assessed is provided；The Item Information of Item Information and candidate shop based on target shop determines the similar article collection of article to be assessed；The target price information with the article to be assessed of target type attribute label is determined based on the pricing information for the similar article that the similar article of article to be assessed is concentrated；It is pushed target price information as the price evaluation result of article to be assessed.The embodiment realizes the item price assessment and push of automation.

Description

Method and apparatus for pushed information

Technical field

The invention relates to field of computer technology, and in particular to Internet technical field more particularly, to pushes away It delivers letters the method and apparatus of breath.

Background technique

With the development of e-commerce technology, more and more platforms provide on-line goods transactional services.The price of article It would generally change with its temperature, market demand.

Existing item price is usually in the just and sound a certain range in market, with reference to identical items or similar article There is price to set.The technology for realizing this method is that the relevant information of article is obtained using web crawlers, with article into Row is matched and is compared with the present price of article, adjusts price according to comparison result after successful match.

Summary of the invention

The embodiment of the present application proposes the method and apparatus for pushed information.

In a first aspect, the embodiment of the present application provides a kind of method for pushed information, comprising: based on obtained to The operation associated information of assessment article determines the attention rate information and price elasticity information of article to be assessed；From preset type category Target type attribute mark corresponding with the attention rate information of article to be assessed and price elasticity information is determined in property tag set Label；Obtain the Item Information in candidate shop and the Item Information in the target shop that article to be assessed is provided, wherein Item Information Including at least article description information and item price information；The Item Information of Item Information and candidate shop based on target shop Determine the similar article collection of article to be assessed, wherein the similar article that the similar article of article to be assessed is concentrated is candidate shop The article provided is provided；Determine that there is target type based on the pricing information for the similar article that the similar article of article to be assessed is concentrated The target price information of the article to be assessed of attribute tags；Using target price information as the price evaluation result of article to be assessed It is pushed.

In some embodiments, the operation associated information of above-mentioned article to be assessed includes providing the target shop of article to be assessed The data on flows and transaction data of each article in paving；Based on the article to be assessed obtained operation associated information determine it is to be assessed The attention rate information and price elasticity information of article, comprising: based on each article in target shop data on flows determine it is to be assessed The data on flows of article；The data on flows of each category article in target shop is counted, each product in target shop are obtained The data on flows of class；According to the data on flows of each article in the data on flows of article to be assessed in target shop, target shop, with And the data on flows of each category determines the attention rate information of article to be assessed in target shop；Count the transaction data in target shop In the affiliated category of article to be assessed transaction data, calculate the price elasticity data of each article under the affiliated category of article to be assessed； According under the price elasticity data of article to be assessed and the affiliated category of article to be assessed each article price elasticity data determine to Assess the price elasticity information of article.

In some embodiments, the above-mentioned data on flows according to article to be assessed in target shop, each object in target shop The data on flows of each category determines the attention rate information of article to be assessed in the data on flows of product and target shop, comprising: base The data on flows of each category determines flow reference threshold value in the data on flows of each article and target shop in target shop； The data on flows and flow reference threshold value for comparing article to be assessed determine that the attention rate of article to be assessed is believed according to comparison result Breath.

In some embodiments, under above-mentioned price elasticity data and the affiliated category of article to be assessed according to article to be assessed The price elasticity data of each article determine the price elasticity information of article to be assessed, comprising: are based on the affiliated category of article to be assessed Under the price elasticity data of each article determine elastic data reference threshold；Judge article to be assessed in the transaction data in target shop Transaction data indicated by the quantity on order of article to be assessed whether reach the first preset threshold；If the transaction of article to be assessed The quantity on order of article to be assessed indicated by data reaches the first preset threshold, the price elasticity data based on article to be assessed The price elasticity information of article to be assessed is determined with the comparison result of elastic data reference threshold；If the number of deals of article to be assessed It is not up to the first preset threshold according to the quantity on order of indicated article to be assessed, is judged to be evaluated in the transaction data in target shop Estimating the quantity on order of the affiliated brand of article to be assessed indicated by the transaction data of the affiliated brand of article, whether to reach second default Threshold value；If the quantity on order of the affiliated brand of article to be assessed indicated by the transaction data of the affiliated brand of article to be assessed reaches Two preset thresholds, the transaction data of the affiliated brand of article to be assessed calculates article to be assessed in the transaction data based on target shop The price elasticity data of affiliated brand, and threshold is referred to according to the price elasticity data of the affiliated brand of article to be assessed and elastic data The comparison result of value determines the price elasticity information of article to be assessed；If indicated by the transaction data of the affiliated brand of article to be assessed The quantity on order of the affiliated brand of article to be assessed be not up to the second preset threshold, the price based on the affiliated category of article to be assessed The comparison result of elastic data and elastic data reference threshold determines the price elasticity information of article to be assessed.

In some embodiments, above-mentioned Item Information further includes article inventory information and article trading information；And it is above-mentioned The Item Information of Item Information and candidate shop based on target shop determines the similar article collection of article to be assessed, comprising: The Item Information of Item Information and candidate shop based on target shop determines candidate shop similar with target shop；From with The similar article of article to be assessed is determined in article set indicated by the Item Information in the similar candidate shop in target shop Collection.

In some embodiments, above-mentioned Item Information based on target shop and the Item Information in candidate shop determine with The similar candidate shop in target shop, comprising: filtered out based on the similarity between at least one of following similar to target shop Candidate shop: the Transaction Income number of same category article indicated by the similarity, article trading information between article inventory information According to similarity, the similarity between the Transaction Income data of same brand objects indicated by article trading information.

In some embodiments, above-mentioned Item Information based on target shop and the Item Information in candidate shop determine with The similar candidate shop in target shop, further includes: article trading income indicated by the article trading information based on candidate shop Data are ranked up candidate shop, and according to the candidate shop of sequencing selection preset quantity as time similar with target shop Select shop.

In some embodiments, article collection indicated by the above-mentioned Item Information from candidate shop similar with target shop The similar article collection of article to be assessed is determined in conjunction, comprising: the article description based on candidate shop similar with target shop Information and the article description information in target shop determine the similar article collection of article to be assessed.

In some embodiments, the pricing information for the similar article that the above-mentioned similar article based on article to be assessed is concentrated is true Surely the target price information of the article to be assessed with target type attribute label, comprising: the homologue based on article to be assessed The distribution of the pricing information for the similar article that product are concentrated determines each type corresponded in preset type attribute tag set The pricing information of attribute tags；Determine that the pricing information for corresponding to target type attribute label is the target price of article to be assessed Information.

In some embodiments, the pricing information for the similar article that the above-mentioned similar article based on article to be assessed is concentrated Distribution determines the pricing information of each type attribute label corresponded in preset type attribute tag set, comprising: is based on The distribution of the pricing information for the similar article that the similar article of article to be assessed is concentrated, is filtered similar article；It was based on The quantity and pricing information of similar article after filter determine each type category corresponded in preset type attribute tag set The pricing information of property label.

Second aspect, the embodiment of the present application provide a kind of device for pushed information, comprising: the first determination unit, For determining the attention rate information and price elasticity of article to be assessed based on the operation associated information of the article to be assessed obtained Information；Second determination unit is believed for determining from preset type attribute tag set with the attention rate of article to be assessed Cease target type attribute label corresponding with price elasticity information；Acquiring unit, for obtain the Item Information in candidate shop with And provide the Item Information in the target shop of article to be assessed, wherein Item Information includes at least article description information and article Pricing information；Matching unit, the Item Information for Item Information and candidate shop based on target shop are determined to be assessed The similar article collection of article, wherein the similar article that the similar article of article to be assessed is concentrated is the article that candidate shop provides； The pricing information of assessment unit, the similar article for the similar article concentration based on article to be assessed determines there is target type The target price information of the article to be assessed of attribute tags；Push unit, for using target price information as article to be assessed Price evaluation result pushed.

In some embodiments, the operation associated information of above-mentioned article to be assessed includes providing the target shop of article to be assessed The data on flows and transaction data of each article in paving；First determination unit is further used for determining object to be assessed as follows The attention rate information and price elasticity information of product: the stream of article to be assessed is determined based on the data on flows of each article in target shop Measure data；The data on flows of each category article in target shop is counted, the flow of each category in target shop is obtained Data；According to the data on flows of each article and target shop in the data on flows of article to be assessed in target shop, target shop The data on flows of each category determines the attention rate information of article to be assessed in paving；Count to be assessed in the transaction data in target shop The transaction data of the affiliated category of article calculates the price elasticity data of each article under the affiliated category of article to be assessed；According to be evaluated The price elasticity data for estimating each article under the price elasticity data and the affiliated category of article to be assessed of article determine article to be assessed Price elasticity information.

In some embodiments, above-mentioned first determination unit is further used for determining article to be assessed as follows Attention rate information: the data on flows of each category determines in the data on flows and target shop based on each article in target shop Flow reference threshold value；The data on flows and flow reference threshold value for comparing article to be assessed, determine object to be assessed according to comparison result The attention rate information of product.

In some embodiments, above-mentioned first determination unit is further used for determining article to be assessed as follows Price elasticity information: determine elastic data with reference to threshold based on the price elasticity data of each article under the affiliated category of article to be assessed Value；Judging in the transaction data in target shop the quantity on order of article to be assessed indicated by the transaction data of article to be assessed is It is no to reach the first preset threshold；If the quantity on order of article to be assessed indicated by the transaction data of article to be assessed reaches first Preset threshold determines object to be assessed based on the price elasticity data of article to be assessed and the comparison result of elastic data reference threshold The price elasticity information of product；If the quantity on order of article to be assessed indicated by the transaction data of article to be assessed is not up to first Preset threshold judges object to be assessed indicated by the transaction data of the affiliated brand of article to be assessed in the transaction data in target shop Whether the quantity on order of the affiliated brand of product reaches the second preset threshold；If indicated by the transaction data of the affiliated brand of article to be assessed The quantity on order of the affiliated brand of article to be assessed reach the second preset threshold, it is to be assessed in the transaction data based on target shop The transaction data of the affiliated brand of article calculates the price elasticity data of the affiliated brand of article to be assessed, and according to article institute to be assessed The comparison result of the price elasticity data and elastic data reference threshold that belong to brand determines the price elasticity information of article to be assessed； If the quantity on order of the affiliated brand of article to be assessed indicated by the transaction data of the affiliated brand of article to be assessed is not up to second The comparison result of preset threshold, price elasticity data and elastic data reference threshold based on the affiliated category of article to be assessed determines The price elasticity information of article to be assessed.

In some embodiments, above-mentioned Item Information further includes article inventory information and article trading information；And it is above-mentioned Matching unit is further used for the Item Information based on target shop and the Item Information in candidate shop, determines as follows The similar article collection of article to be assessed out: the Item Information of Item Information and candidate shop based on target shop is determined and mesh Mark the similar candidate shop in shop；In article set indicated by Item Information from candidate shop similar with target shop really Make the similar article collection of article to be assessed.

In some embodiments, above-mentioned matching unit is further used for Item Information and candidate shop based on target shop Item Information, determine candidate shop similar with target shop as follows: between at least one of following Similarity filters out candidate shop similar with target shop: the similarity, article trading information between article inventory information are signified The transaction of same brand objects indicated by similarity, article trading information between the Transaction Income data of the same category article shown is received Similarity between beneficial data.

In some embodiments, above-mentioned matching unit is also used to the Item Information based on target shop and the object in candidate shop Product information determines candidate shop similar with target shop: the article trading information based on candidate shop as follows Indicated article trading avail data is ranked up candidate shop, and makees according to the candidate shop of sequencing selection preset quantity For candidate shop similar with target shop.

In some embodiments, above-mentioned matching unit is further used for as follows from time similar with target shop It selects the similar article collection for determining article to be assessed in article set indicated by the Item Information in shop: being based on and target shop The article description information in similar candidate shop and the article description information in target shop determine the homologue of article to be assessed Product collection.

In some embodiments, above-mentioned assessment unit is further used for the phase of the concentration of the similar article based on article to be assessed Like the pricing information of article, determine has the target price letter of the article to be assessed of target type attribute label as follows Breath: it is determined based on the distribution of the pricing information of the similar article of the similar article concentration of article to be assessed corresponding to preset type The pricing information of each type attribute label in attribute tags set；Determine that the price for corresponding to target type attribute label is believed Breath is the target price information of article to be assessed.

In some embodiments, above-mentioned assessment unit is further used for the phase of the concentration of the similar article based on article to be assessed Like the distribution of the pricing information of article, each class corresponded in preset type attribute tag set is determined as follows The pricing information of type attribute tags: the distribution of the pricing information for the similar article that the similar article based on article to be assessed is concentrated, Similar article is filtered；Based on the quantity and pricing information of filtered similar article, determines and correspond to preset type The pricing information of each type attribute label in attribute tags set.

The third aspect, the embodiment of the present application provide a kind of electronic equipment, comprising: one or more processors；Storage dress It sets, for storing one or more programs, when one or more programs are executed by one or more processors, so that one or more A processor realizes the method for pushed information provided such as the application first aspect.

Fourth aspect, the embodiment of the present application provide a kind of computer storage medium, are stored thereon with computer program, In, the method for pushed information provided such as the application first aspect is provided when program is executed by processor.

Detailed description of the invention

By reading a detailed description of non-restrictive embodiments in the light of the attached drawings below, the application's is other Feature, objects and advantages will become more apparent upon:

Fig. 1 is that this application can be applied to exemplary system architecture figures therein；

Fig. 2 is the flow chart according to one embodiment of the method for pushed information of the application；

Fig. 3 is the side that the price elasticity information of article to be assessed is determined in the method for pushed information according to the application A kind of flow diagram of implementation of method；

Fig. 4 is closed based on the determining type attribute label of the distribution of the pricing information of similar article is corresponding with pricing information A kind of concrete scene schematic diagram of system；

Fig. 5 is the structural schematic diagram according to one embodiment of the device for pushed information of the application；

Fig. 6 is adapted for the structural schematic diagram for the computer system for realizing the electronic equipment of the embodiment of the present application.

Specific embodiment

The application is described in further detail with reference to the accompanying drawings and examples.It is understood that this place is retouched The specific embodiment stated is used only for explaining related invention, rather than the restriction to the invention.It also should be noted that in order to Convenient for description, part relevant to related invention is illustrated only in attached drawing.

It should be noted that in the absence of conflict, the features in the embodiments and the embodiments of the present application can phase Mutually combination.The application is described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

Fig. 1 is shown can be using the webpage generating method of the embodiment of the present application or the exemplary system of auto-building html files device Framework 100.

As shown in Figure 1, system architecture 100 may include terminal device 101,102,103, network 104 and server 105. Network 104 between terminal device 101,102,103 and server 105 to provide the medium of communication link.Network 104 can be with Including various connection types, such as wired, wireless communication link or fiber optic cables etc..

User 110 can be used terminal device 101,102,103 and be interacted with server 105 by network 104, with reception or Send message etc..Various telecommunication customer end applications can be installed, such as web browser is answered on terminal device 101,102,103 With, shopping class application, searching class application etc..In the scene of the application, user 110 can be shop user or consumer on line User.

Terminal device 101,102,103 can be with display screen and support the various electronic equipments of data processing, packet Include but be not limited to smart phone, tablet computer, E-book reader, pocket computer on knee and desktop computer etc..

Server 105 can be to provide the server of various services, such as to showing on terminal device 101,102,103 Item Information provides the backstage Item Information processing server supported.Backstage Item Information processing server can be to receiving Article trading request, item price recommendation request data analyze etc. processing, and by processing result (such as transaction results, valence Lattice assessment result) feed back to terminal device.

It should be noted that the method provided by the embodiment of the present application for pushed information is generally held by server 105 Row, correspondingly, the device for pushed information is generally positioned in server 105.

It should be noted that server can be hardware, it is also possible to software.When server is hardware, may be implemented At the distributed server cluster that multiple servers form, individual server also may be implemented into.It, can when server is software To be implemented as multiple softwares or software module (such as providing Distributed Services), single software or software also may be implemented into Module.It is not specifically limited herein.

It should be understood that the number of terminal device, network and server in Fig. 1 is only schematical.According to realization need It wants, can have any number of terminal device, network and server.

With continued reference to Fig. 2, it illustrates the processes according to one embodiment of the method for pushed information of the application 200.This is used for the method for pushed information, comprising the following steps:

Step 201, the operation associated information based on the article to be assessed obtained determines the attention rate letter of article to be assessed Breath and price elasticity information.

In the present embodiment, the electronic equipment of the above-mentioned method operation for pushed information thereon is (such as shown in FIG. 1 Server 105) operation associated information that article to be assessed can be obtained first, then to the operation associated information of article to be assessed Data statistics and analysis are carried out, the attention rate information and price elasticity information of article to be assessed are extracted.

Above-mentioned article to be assessed can be the article that the shop of line upper mounting plate provides, in actual scene, article to be assessed It can be the commodity that businessman specifies, be also possible to any one effective article of line upper mounting plate.Article to be assessed it is operation associated Information can be to operate on the lines such as browsing, collection, transaction, restocking, undercarriage, price adjustment, the attribute configuration of article to be assessed and close The information of connection, can include but is not limited to: the historical transactional information, to be evaluated of the goods attribute of article to be assessed, article to be assessed Estimate access information on the line of article, the Transaction Information of the affiliated brand of article to be assessed and access information, the affiliated product of article to be assessed The Transaction Information and access information of class, with article to be assessed have similar goods attribute other articles Transaction Information and Access information.Wherein goods attribute may include the build-in attributes information such as material, purposes, size, color of article, Transaction Information It may include transaction value information, number of transaction information and exchange hour information, access information may include pageview information, divide The amount of enjoying information and amount of collection information.

The information that the attention rate information of article can be the degree that characterization article is concerned can be based on to be evaluated herein Pageview, amount of collection, sharing amount, trading volume of article etc. is estimated to determine the attention rate information of article to be assessed.Such as it can be straight It connects and regard trading volume or pageview etc. as attention rate information, or the data such as pageview, amount of collection, trading volume can be transformed into Weighted sum obtains the numerical value for indicating the attention rate information of article to be assessed after same scale.

In some optional implementations of the present embodiment, the attention rate information of above-mentioned article to be assessed be can be to upper State the data further progress sections such as pageview, amount of collection, sharing amount, the trading volume of article to be assessed delimit after, according to locating for Section determine attention rate label.For example, if pageview of the article to be assessed in nearly one month is greater than 1000 times, The attention rate information that can determine article to be assessed is attention rate label " high flow capacity "；If otherwise article to be assessed was at nearly one month Interior pageview can then determine that the attention rate information of article to be assessed is attention rate label " low discharge " less than 1000 times.? Here, the boundary value (1000 times in such as above-mentioned example) in section can be preset value.

Price elasticity information is the information for characterizing the sensitivity that the price of article changes with trading volume or demand.? It, can be according to the Transaction Information and valence of article to be assessed after the operation associated information for obtaining article to be assessed in the present embodiment Lattice adjustment information calculates the change rate that the price of article to be assessed changes with trading volume, can specifically calculate the hundred of trading volume variation The ratio for dividing ratio and the percentage of price change, as the data for measuring price elasticity.

It, can be using the data of above-mentioned measurement price elasticity as price in some optional implementations of the present embodiment Elastic information can also carry out interval division to the data of above-mentioned measurement price elasticity, fall according to the data for measuring price elasticity The numerical intervals entered determine the price elasticity label for characterizing price elasticity information.Such as the number for measuring price elasticity According to value be greater than 3 when, elastic label of setting price be " high price elasticity "；Otherwise the value of the data for measuring price elasticity is not When greater than 3, elastic label of setting price is " low price elasticity ".

Step 202, the attention rate information and valence with article to be assessed are determined from preset type attribute tag set The corresponding target type attribute label of lattice elastic information.

In the present embodiment, the type attribute tag set comprising multiple type attribute labels can be preset.Such Each type attribute label in type attribute tags set is corresponding with one group of attention rate information and price elasticity information respectively.Such as Type attribute tag set includes four type attribute label As, B, C, D, wherein type attribute label A and attention rate information c1+ Price elasticity information d1 is corresponding, and type attribute label B is corresponding with attention rate information c1+ price elasticity information d2, type attribute mark It is corresponding with attention rate information c2+ price elasticity information d1 to sign C, type attribute label D and attention rate information c2+ price elasticity information D2 is corresponding.

In actual scene, the above-mentioned type attribute tags set can be set in advance by the shop user for providing article to be assessed It is fixed, and obtained by the electronic equipment of the above-mentioned method operation for pushed information thereon by user interface.The above-mentioned type category Property tag set can also be stored in advance in above-mentioned electronic equipment, as default type attribute tags set, to set in this The attention rate information and price elasticity information pair of article to be assessed are determined when being set to default using default type attribute tags set The target type attribute label answered.

Type attribute label can be attention rate label for characterizing corresponding attention rate information and for characterizing correspondence The price elasticity tag combination of price elasticity information generate, such as can be that " high flow capacity high price elasticity ", " high flow capacity is low Price elasticity ", " low discharge high price elasticity " or " low discharge low price elasticity ".

In the present embodiment, can be believed according to the attention rate information and price elasticity for the article to be assessed that step 201 determines Breath is matched in preset type attribute tag set, using the type attribute label of successful match as target type attribute Label.

Step 203, the Item Information in candidate shop and the Item Information in the target shop that article to be assessed is provided are obtained, Wherein, Item Information includes at least article description information and item price information.

In the present embodiment, can collect article to be assessed online upper mounting plate and all of other line upper mounting plates obtain The information of the information in the shop taken, shop may include the Item Information in shop.Herein, Item Information at least may include object Product description information and item price information.It is then possible to be selected from the shop of all acquisitions one or more as candidate shop Paving, or using the shop of all acquisitions as candidate shop, obtain the Item Information in candidate shop.It can be from the shop of acquisition It determines to provide the target shop of article to be assessed, the Item Information in the target shop of offer article to be assessed is provided.In reality In the scene of border, the target shop for providing article to be assessed can be the shop for selling article to be assessed.

In some optional implementations of the present embodiment, above-mentioned candidate shop can be preassigned shop, then The Item Information in these candidate shops and the target shop that article to be assessed is provided can be grabbed by web crawlers.In reality In scene, each shop can provide the article of multiple categories, multiple brands, then the different product that available each shop provides The Item Information of class, different brands article.

Step 204, the Item Information of Item Information and candidate shop based on target shop determines article to be assessed Similar article collection.

In the present embodiment, the similar article collection of article to be assessed can be determined based on the similarity between article, In, the similar article that the similar article of article to be assessed is concentrated is the article that candidate shop provides.It specifically, can be according to be evaluated Semantic similarity between the article description information for each article that the article description information and candidate shop for estimating article provide comes true The similar article of fixed article to be assessed, and then combine all similar articles for similar article collection.

Article description information can be the information of the attribute of description article, can be for example including the material for describing article The information of the attributes such as matter, type, purposes, color, shape, size, grown place, title, brand identity.

Step 205, the pricing information for the similar article concentrated based on the similar article of article to be assessed, which is determined, has target The target price information of the article to be assessed of type attribute label.

In the present embodiment, the target price letter of article to be assessed can be determined based on the pricing information of similar article Breath.The price for the similar article that above-mentioned similar article can be concentrated first in the target price information for determining article to be assessed Information carries out data statistics, determines that the similar article of article to be assessed or article to be assessed has often according to data statistics result Corresponding price range when a type attribute label, thus in conjunction with article to be assessed target type attribute label determine it is to be assessed The target price information of article.

Specifically, the price distribution that the similar article of article to be assessed can be counted, then according to type attribute label The price distribution of similar article is divided into the price range of corresponding number by the quantity of the type attribute label in set, and will be every A price range is associated with a type attribute label respectively.It can then determine and the associated price area of target type attribute label Between be target price information, or can in the associated price range of target type attribute label select a price numerical value As target price information.

Step 206, it is pushed target price information as the price evaluation result of article to be assessed.

Above-mentioned electronic equipment can be issued in response to user to article to be assessed carry out price evaluation request and will be to The target price information of assessment article is pushed to user.The user can be to provide the shop user of article to be assessed.Above-mentioned electricity Sub- equipment can also monitor the price of article to be assessed in real time, and when price exceeds preset secure threshold, (price is extremely low Or price it is extremely high when) the target price information of article to be assessed is actively pushed to corresponding user.

The method for pushed information of the above embodiments of the present application, passes through the association based on the article to be assessed obtained Operation information determines the attention rate information and price elasticity information of article to be assessed, then from preset type attribute tag set In determine target type attribute label corresponding with the attention rate information of article to be assessed and price elasticity information, then obtain The Item Information in the target shop of the Item Information and offer article to be assessed in candidate shop, wherein Item Information at least wraps Article description information and item price information are included, the Item Information of the Item Information and candidate shop that are then based on target shop is true Make the similar article collection of article to be assessed, wherein the similar article that the similar article of article to be assessed is concentrated is candidate shop The article of offer, the pricing information for the similar article concentrated later based on the similar article of article to be assessed determine there is target class The target price information of the article to be assessed of type attribute tags, is finally commented target price information as the price of article to be assessed Estimate result to be pushed, realizes the item price assessment and push of automation.Due to establishing object when carrying out price evaluation Being associated between the attention rate information and price elasticity information and item price of product, can more accurately orient the valence of article Lattice, and then promote the accuracy of the pricing information of push.

In some embodiments, the operation associated information of above-mentioned article to be assessed may include providing the mesh of article to be assessed Mark the data on flows and transaction data of each article in shop.Herein, brand, the category of each article are preset in target shop , then article to be assessed can be determined based on the data on flows and transaction data of the affiliated category of article to be assessed and affiliated brand Attention rate information and price elasticity information.

In these embodiments, the attention rate information of article to be assessed can be determined as follows: based on target shop The data on flows of each article determines the data on flows of article to be assessed in paving；To the flow number of each category article in target shop According to being counted, the data on flows of each category in target shop is obtained；According to the data on flows of article to be assessed in target shop, The data on flows of each category determines the concern of article to be assessed in the data on flows of each article and target shop in target shop Spend information.

Specifically, above-mentioned data on flows can be commodity flows (page view, PV), can be and counts according to the date Pageview data.The transaction effective date of article is denoted as day (0), be denoted as within m days before the transaction effective date of article day (- M), m >=1 can set m≤30 in actual scene.Article to be assessed can be calculated according to following formula (1) at 30 days Average flow rate X_T:

Wherein, PV_jJ days flows before the transaction effective date for indicating article, M are total number of days.It is then available to be assessed Article provide the article to be assessed target shop average flow rate data, while can using the above method calculate provide to Assess the average flow rate data of other articles in the target shop of article.It is then based in the target shop that article to be assessed is provided Each article average flow rate data construct data set 1.Data set 1 may include array array [X1, X2, X3, X4 ..., Xi], and with array array [X1, X2, X3, X4 ..., Xi] in the corresponding article of each element number, wherein array Array [X1, X2, X3, X4 ..., Xi] be according to the ascending sort of the average flow rate data of article, i.e. Xn < Xn+1, n=1, 2,3,4 ... < i-1, and in the array each one article of element representation data on flows.Optionally, in building data set 1 Before array, verification distribution, excluding outlier (such as the value of flow less than 0) first can be carried out to the flow of all items.

Can according to the affiliated category of data on flows article to be assessed in the target shop that article to be assessed is provided provide to The total flow for assessing a period of time (such as 30 days) in the shop of article, then divided by article effective within this time and restocking Time more than preset duration (such as 20 days or more) total number of items, obtain the average flow rate of the affiliated category of article to be assessed Data, the data on flows as the affiliated category of article to be assessed.Likewise it is possible to according to the product in the shop for providing article to be assessed Class catalogue calculates the average flow rate data of each category using identical method.It is then based on and the target shop of article to be assessed is provided The average flow rate data of each category of paving construct data set 2.Data set 2 may include array array [Y1, Y2, Y3, Y4 ..., Yj], and with array array [Y1, Y2, Y3, Y4 ..., Yj] in the corresponding category of each element number, the data set 2 Including data group terminal volume one category of each element representation average flow rate data.

Later, the section of attention rate degree classification can be determined according to the distribution of data on flows in data set 1 and data set 2 Standard, then judges which attention rate degree corresponding section is the data on flows of article to be assessed fall into, then can determine The attention rate degree of article to be assessed, the attention rate information as article to be assessed.

It is possible to further the stream of the data on flows based on each article in target shop and each category in target shop Amount data determine flow reference threshold value, compare the data on flows and flow reference threshold value of article to be assessed, true according to comparison result The attention rate information of fixed article to be assessed.

Specifically, can calculate array array [X1, X2, X3, X4 ..., Xi] arithmetic mean of instantaneous value, be denoted as S1.It can be with To array array [X1, X2, X3, X4 ..., Xi] in the number of 50% percentage quartile be marked, such as percentage can be used Than ranking function to array array [X1, X2, X3, X4 ..., Xi] calculate, the number of label is S2, according to article to be assessed Affiliated category array array [Y1, Y2, Y3, Y4 ..., Yj] in find corresponding value, be denoted as S3, take among S1, S2, S3 Maximum value judges whether the data on flows of article to be assessed is greater than the flow reference threshold value as flow reference threshold value, if so, The attention rate information for determining article to be assessed is " high flow capacity ", otherwise determines that the attention rate information of article to be assessed is " low stream Amount ".

In the present embodiment, the price elasticity information of article to be assessed can be determined as follows: statistics target shop The transaction data of the affiliated category of article to be assessed, calculates the valence of each article under the affiliated category of article to be assessed in the transaction data of paving Lattice elastic data；According to the price elasticity of each article under the price elasticity data of article to be assessed and the affiliated category of article to be assessed Data determine the price elasticity information of article to be assessed.

Herein, price elasticity data can be the sensitivity that price changes with trading volume, can be in a period of time The ratio of trading volume change rate and price change rate indicates.Above-mentioned transaction data may include transaction value, number of transaction and Exchange hour.The transaction data in target shop may include all items including article to be assessed that target shop provides Transaction data, also, the article in target shop be prefixed belonging to category and affiliated brand.In the present embodiment, may be used With according under the affiliated category of article to be assessed in the transaction data of each article price change rate and trading volume change rate, calculate Out under the affiliated category of article to be assessed each article price elasticity data, then can calculate institute under the affiliated category of article to be assessed There are price elasticity data of the mean value of the price elasticity data of article as the affiliated category of article to be assessed.It can be according to be assessed The price elasticity data of the affiliated category of article determine elastic threshold value, judge the price elasticity data and the elasticity threshold of article to be assessed Relative size relationship between value, so according to the price elasticity data of pre-set article to be assessed and the elasticity threshold value it Between relative size relationship and be used to indicate price elasticity information price elasticity label between corresponding relationship determine it is to be assessed The price elasticity information of article.

It is to be evaluated to use offer in the attention rate information and price elasticity information for determining article to be assessed for above-described embodiment The data on flows and transaction data for estimating each article in the target shop of article, data on flows based on each category in target shop and Transaction data determines the reference threshold that attention rate and price elasticity determine, the method for the present embodiment is utilized more fully as a result, Data assess the price of article to be assessed, can further promote the accuracy of assessment result.

Still optionally further, the price elasticity information of article to be assessed can be related to the number of transaction of article to be assessed. Specifically, the price elasticity data of article to be assessed can be determined as follows:

Firstly, the price elasticity data based on each article under the affiliated category of article to be assessed determine elastic data with reference to threshold Value.It herein, can be by the price elasticity data of the affiliated category of article to be assessed directly as elastic data reference threshold.It is optional The price elasticity data of each article under the affiliated category of article to be assessed can also be denoted as ε 1, according to belonging to article to be assessed by ground The elastic data of each article calculates the price elasticity data ε 2 of each affiliated brand of article under the affiliated category of article to be assessed under category, Using random forests algorithm model, ε 3 is denoted as using the price elasticity data that machine learning algorithm is fitted article to be assessed.Building The price elasticity triple (ε 1, ε 2, ε 3) of each article, then calculates belonging to article to be assessed under the affiliated category of article to be assessed The mean value of the price elasticity data triple of all items under categoryThen it takesIn Intermediate value is as elastic data reference threshold.

Then, judge in the transaction data in target shop article to be assessed indicated by the transaction data of article to be assessed Whether quantity on order reaches the first preset threshold.

Then, if the quantity on order of article to be assessed indicated by the transaction data of article to be assessed reaches the first default threshold Value determines the valence of article to be assessed based on the price elasticity data of article to be assessed and the comparison result of elastic data reference threshold Lattice elastic information.If article to be assessed indicated by the transaction data of article to be assessed orders in the transaction data in target shop Odd number amount reaches the first preset threshold, then can determine that the historical trading data point quantity of article to be assessed is sufficient, can be direct The price elasticity data of article to be assessed itself are compared with above-mentioned elastic data reference threshold, if article to be assessed itself Price elasticity data be greater than elastic data reference threshold, then can determine article to be assessed elastic information be " high price bullet Property ", it otherwise can determine that the elastic information of article to be assessed is " low price elasticity ".

Then, if to be not up to first default for the quantity on order of article to be assessed indicated by the transaction data of article to be assessed Threshold value judges article institute to be assessed indicated by the transaction data of the affiliated brand of article to be assessed in the transaction data in target shop Whether the quantity on order for belonging to brand reaches the second preset threshold.The article to be assessed indicated by the transaction data of article to be assessed Quantity on order can determine that the historical trading data point of article to be assessed is very few when being not up to the first preset threshold, calculate accordingly The price elasticity data reliability of article to be assessed out is poor, therefore can further judge the affiliated brand of article to be assessed Whether the quantity of historical trading data point is enough to ensure that the reliability of the price elasticity data of the article to be assessed obtained.

Later, if the order numbers of the affiliated brand of article to be assessed indicated by the transaction data of the affiliated brand of article to be assessed Amount reaches the second preset threshold, in the transaction data based on target shop the transaction data of the affiliated brand of article to be assessed calculate to The price elasticity data of the affiliated brand of article are assessed, and according to the price elasticity data of the affiliated brand of article to be assessed and elastic number The price elasticity information of article to be assessed is determined according to the comparison result of reference threshold.At this moment, it can determine belonging to article to be assessed The quantity of the historical trading data point of brand is enough to ensure that the reliability of the price elasticity data of the article to be assessed obtained, can be with Using the price elasticity data of the affiliated brand of article to be assessed as the price elasticity data of article to be assessed, referred to elastic data Threshold value is compared, and determines corresponding price elasticity information according to comparison result.

Finally, if the order numbers of the affiliated brand of article to be assessed indicated by the transaction data of the affiliated brand of article to be assessed Amount is not up to the second preset threshold, price elasticity data and elastic data reference threshold based on the affiliated category of article to be assessed Comparison result determines the price elasticity information of article to be assessed.When the number of the historical trading data point of the affiliated brand of article to be assessed It, can be by the affiliated product of article to be assessed when amount is also not sufficient to ensure that the reliability of price elasticity data of the article to be assessed obtained Price elasticity data of the price elasticity data of class as article to be assessed, are compared, and root with elastic data reference threshold Corresponding price elasticity information is determined according to comparison result.

Still optionally further, it can also judge article to be assessed indicated by the transaction data of the affiliated category of article to be assessed Whether the quantity on order of affiliated category reaches third predetermined threshold value, if it is not, it can be then based further on random forests algorithm model, It is fitted using transaction data of the machine learning algorithm to article to be assessed, obtains the price elasticity data of article to be assessed, Whether the quality of price elasticity data that can also further judge that fitting obtains meet the requirements, if then obtaining fitting Price elasticity data are compared with above-mentioned elastic data reference threshold.

Referring to FIG. 3, it illustrates the valences for determining article to be assessed in the method for pushed information according to the application The flow diagram of the above-mentioned optional implementation of the method for lattice elastic information.

As shown in figure 3, can be based in the method flow of the price elasticity information of the determination of the present embodiment article to be assessed The operation associated information of article to be assessed is determined comprising the price elasticity data of each article under the affiliated category of article to be assessed Price elasticity database.Step 301 can be first carried out, it is default to judge whether the number of data points of article to be assessed reaches first Threshold value.If so, confirming the price elasticity data of article to be assessed；It is no to then follow the steps 302, judge whether that brand can be associated with Price elasticity data, that is, judge whether the number of data points of the affiliated brand of article to be assessed reaches the second preset threshold.If so, The price elasticity data for confirming article to be assessed are the price elasticity data of associated brand；No to then follow the steps 303, judgement is It is pre- to judge whether the number of data points of the affiliated category of article to be assessed reaches third for the no price elasticity data that can be associated with category If threshold value.If so, confirming that the price elasticity data of article to be assessed are the price elasticity data of associated category；Otherwise it executes Step 304, using Random Forest model, use and its price elasticity data for learning fitting article to be assessed, step is then executed Rapid 305, judge whether the obtained price elasticity quality of data of fitting meets preset condition (the i.e. obtained price bullet of judgement fitting Property data whether reach quality requirement), if so, the obtained price elasticity data of confirmation fitting are the price bullet of article to be assessed Property data.

Above-described embodiment, can be to be assessed by the category elastic data and brand elastic data of association article to be assessed The historical trading data point of article guarantees the reliability of the price elasticity data of article to be assessed when very few, be thus to be evaluated The price evaluation for estimating article provides more reliable foundation.

In some embodiments, above-mentioned Item Information can also include article inventory information and article trading information, then on State Item Information based on target shop and candidate shop Item Information determine article to be assessed similar article collection step Rapid 204, may include: Item Information based on target shop and candidate shop Item Information determine it is similar to target shop Candidate shop；It is determined in article set indicated by Item Information from candidate shop similar with target shop to be assessed The similar article collection of article.

It specifically, can be first according to similar between the Item Information in target shop and the Item Information in candidate shop Degree determines candidate shop similar with target shop.Such as it can choose and reach with the coincidence factor of the article of target shop offer 80% or more candidate shop is as the similar candidates shop with target shop.

It, can be based on the similarity screening between at least one of following in some optional implementations of the present embodiment Candidate shop similar with target shop out: same category indicated by the similarity, article trading information between article inventory information Between the Transaction Income data of same brand objects indicated by similarity, article trading information between the Transaction Income data of article Similarity.That is, can according between the article inventory information for characterizing the similarity between stock article similarity, With between gross turnover in category (Gross Merchandise Volume, GMV) scale similarity, advise with GMV in brand One or more in similarity between mould determine the similarity between target shop and candidate shop.And then it can basis The descending sort selected and sorted top N of similarity between target shop and candidate shop as shop similar with target shop Paving.

In some optional implementations of the present embodiment, it can also determine as follows and target shop phase As candidate shop: article trading avail data indicated by the article trading information based on candidate shop carries out candidate shop Sequence, and according to the candidate shop of institute's sequencing selection preset quantity as candidate shop similar with target shop.Herein, may be used In candidate shop will provide the article of the affiliated category of article to be assessed or affiliated brand, GMV sorts in preceding preset quantity position (such as first 20) or GMV sort before and after the GMV sequence in target shop, and (such as GMV sorts in mesh for each preset quantity position Mark shop before 20 and/or GMV sequence 20 after target shop) candidate shop be elected to be time similar with target shop Select shop.

Later, can the article of article description information and target shop based on candidate shop similar with target shop retouch State the similar article collection that information determines article to be assessed.The article that can be provided in candidate shop similar with target shop In find out the matched article of description information of article description information Yu article to be assessed, as the similar article of article to be assessed, Above-mentioned similar article is added to concentrate.It is alternatively possible to be set in advance in the homologue selected in each similar candidate shop The quantity of product, for example, 50 can then be the object of selection and article to be assessed in the similar each candidate shop in target shop 50 articles before the sequencing of similarity of product description information, the similar article as article to be assessed.

By screening similar candidate shop, the homologue of article to be assessed is searched in similar candidate shop later Product can reduce the time it takes during searching similar article, promote calculating speed.

In some embodiments, the pricing information for the similar article that the above-mentioned similar article based on article to be assessed is concentrated is true Surely the step 205 of the target price information of the article to be assessed with target type attribute label, may include: based on to be assessed The distribution of the pricing information for the similar article that the similar article of article is concentrated, which determines, corresponds to preset type attribute tag set In each type attribute label pricing information；Determine that the pricing information for corresponding to target type attribute label is object to be assessed The target price information of product.

Specifically, available above-mentioned similar article concentrates the pricing information of each similar article, then to each homologue The pricing information of product is ranked up, and obtains the distribution situation of the pricing information of similar article later, can determine similar article Price range.The quantity that can then proceed in the type attribute label for including in preset type attribute tag set, by phase Corresponding number subinterval is divided into like the price range of article.The then corresponding price subinterval of each type attribute label. The relative size relationship between the corresponding price of each type attribute label can be preset, in this manner it is possible to determine every The corresponding price subinterval of a type attribute label.Then it is corresponding to find out the target type attribute label that article to be assessed has Price subinterval.The corresponding price subinterval of target type attribute label that can have using article to be assessed is as article to be assessed Target price information, can also be selected in the corresponding price subinterval of target type attribute label that article to be assessed has Target price information of one price value (such as minimum value, maximum value or intermediate value etc.) as article to be assessed.

As an example, referring to FIG. 4, preset type attribute tag set includes 4 type attribute labels: " low discharge High resiliency ", " high flow capacity high resiliency ", " low discharge low elasticity " and " high flow capacity low elasticity ".The similar article of article to be assessed Price range minimum value be P1, maximum value P2.Wherein, " high flow capacity high resiliency " corresponding pricing information is 25% point Position, i.e. P1+25% (P2-P1), " low discharge high resiliency " corresponding pricing information be 50% quartile, i.e. P1+50% (P2-P1), " high flow capacity low elasticity " corresponding pricing information is 75% quartile, i.e. P1+75% (P2-P1), " low discharge low elasticity " is corresponding Pricing information is 100% quartile, i.e. P2.

Still optionally further, it can determine as follows corresponding to each in preset type attribute tag set The pricing information of type attribute label: point of the pricing information for the similar article that the similar article based on article to be assessed is concentrated Cloth is filtered similar article；Based on the quantity and pricing information of filtered similar article, determines and correspond to preset class The pricing information of each type attribute label in type attribute tags set.

In filtering, the just and sound valence in market can be primarily based on and be filtered, the range of the just and sound valence in market can be by be assessed Present price or to be assessed article average price P0 in each shop of the article in target shop is determined, such as can be [50%P0,150%P0].The similar article of range by price beyond the just and sound valence in the market filters out.Optionally, it can also filter out Price and the overall distribution deviation of similar article are biggish, carry out abnormal filtering in conjunction with statistical indicators such as variance, standard deviations, such as The similar article that price error is more than poor 3 times of average can be filtered out.

In the present embodiment, if after filtering similar article negligible amounts (such as no more than 10), can be according to Quartile cutting price range on statistical significance.Assuming that the quantity of filtered similar article is Q, it can be according to preset kind The price of filtered similar article is divided into q section, every Q/q by the type attribute number of labels q in attribute tags set One price range of Price Impact of a similar article, the corresponding type attribute label of each price range.

If the quantity of similar article is more (being greater than 10) after filtering, can be according to similar item price most Big value max and minimum value min, is divided into multiple sections for price range [min, max], determines the corresponding type in each section Attribute tags.

It later, can be corresponding according to the attention rate information and price elasticity information for the article to be assessed that step 202 determines Target type attribute label finds corresponding price or price range, and the price evaluation as article to be assessed is as a result, i.e. to be evaluated Estimate the target price information of article.

It, can be to avoid exceptional value shadow by filtering the similar article that similar article is concentrated according to the price distribution of similar article The accuracy that price range divides is rung, is further ensured that the accuracy of the price evaluation result of article to be assessed.

With further reference to Fig. 5, as the realization to method shown in above-mentioned each figure, this application provides one kind for pushing letter One embodiment of the device of breath, the Installation practice is corresponding with embodiment of the method shown in Fig. 2, which can specifically answer For in various electronic equipments.

As shown in figure 5, the device 500 for pushed information of the present embodiment includes: that the first determination unit 501, second is true Order member 502, acquiring unit 503, matching unit 504, assessment unit 505 and push unit 506.Wherein, first list is determined Member 501 is for determining the attention rate information and price of article to be assessed based on the operation associated information of the article to be assessed obtained Elastic information；Second determination unit 502 is used to determine the pass with article to be assessed from preset type attribute tag set Note degree information and the corresponding target type attribute label of price elasticity information；Acquiring unit 503 is used to obtain the object in candidate shop The Item Information in the target shop of product information and offer article to be assessed, wherein Item Information includes at least article description letter Breath and item price information；Item Information of the matching unit 504 for Item Information and candidate shop based on target shop is true Make the similar article collection of article to be assessed, wherein the similar article that the similar article of article to be assessed is concentrated is candidate shop The article of offer；Pricing information of the assessment unit 505 for the similar article that the similar article based on article to be assessed is concentrated is true Surely the target price information of the article to be assessed with target type attribute label；Push unit 506, for believing target price It ceases and is pushed as the price evaluation result of article to be assessed.

In some embodiments, the operation associated information of above-mentioned article to be assessed includes providing the target shop of article to be assessed The data on flows and transaction data of each article in paving.First determination unit 501 can be further used for determining as follows The attention rate information and price elasticity information of article to be assessed: based on each article in target shop data on flows determine it is to be assessed The data on flows of article；The data on flows of each category article in target shop is counted, each product in target shop are obtained The data on flows of class；According to the data on flows of each article in the data on flows of article to be assessed in target shop, target shop, with And the data on flows of each category determines the attention rate information of article to be assessed in target shop；Count the transaction data in target shop In the affiliated category of article to be assessed transaction data, calculate the price elasticity data of each article under the affiliated category of article to be assessed； According under the price elasticity data of article to be assessed and the affiliated category of article to be assessed each article price elasticity data determine to Assess the price elasticity information of article.

In some embodiments, above-mentioned first determination unit 501 can be further used for determining as follows to be evaluated Estimate the attention rate information of article: the flow of each category in data on flows and target shop based on each article in target shop Data determine flow reference threshold value；The data on flows and flow reference threshold value for comparing article to be assessed, determine according to comparison result The attention rate information of article to be assessed.

In some embodiments, above-mentioned first determination unit 501 can be further used for determining as follows to be evaluated Estimate the price elasticity information of article: determining elastic data based on the price elasticity data of each article under the affiliated category of article to be assessed Reference threshold；Judge in the transaction data in target shop the order of article to be assessed indicated by the transaction data of article to be assessed Whether quantity reaches the first preset threshold；If the quantity on order of article to be assessed indicated by the transaction data of article to be assessed reaches To the first preset threshold, the comparison result of price elasticity data and elastic data reference threshold based on article to be assessed determine to Assess the price elasticity information of article；If the quantity on order of article to be assessed indicated by the transaction data of article to be assessed does not reach To the first preset threshold, judge in the transaction data in target shop indicated by the transaction data of the affiliated brand of article to be assessed to Whether the quantity on order of the assessment affiliated brand of article reaches the second preset threshold；If the transaction data of the affiliated brand of article to be assessed The quantity on order of the indicated affiliated brand of article to be assessed reaches the second preset threshold, in the transaction data based on target shop The transaction data of the affiliated brand of article to be assessed calculates the price elasticity data of the affiliated brand of article to be assessed, and according to be assessed The price elasticity data of the affiliated brand of article and the comparison result of elastic data reference threshold determine the price bullet of article to be assessed Property information；If the quantity on order of the affiliated brand of article to be assessed indicated by the transaction data of the affiliated brand of article to be assessed does not reach To the second preset threshold, the comparison knot of price elasticity data and elastic data reference threshold based on the affiliated category of article to be assessed Fruit determines the price elasticity information of article to be assessed.

In some embodiments, above-mentioned Item Information can also include article inventory information and article trading information；And Matching unit 504 can be further used for the Item Information based on target shop and the Item Information in candidate shop, according to as follows Mode determines the similar article collection of article to be assessed: the Item Information of Item Information and candidate shop based on target shop is true Make candidate shop similar with target shop；Article indicated by Item Information from candidate shop similar with target shop The similar article collection of article to be assessed is determined in set.

In some embodiments, matching unit 504 can be further used for Item Information and candidate based on target shop The Item Information in shop determines candidate shop similar with target shop as follows: based on it is at least one of following it Between similarity filter out candidate shop similar with target shop: similarity, article trading information between article inventory information The friendship of same brand objects indicated by similarity, article trading information between the Transaction Income data of indicated same category article Similarity between easy avail data.

In some embodiments, matching unit 504 can be also used for Item Information and candidate shop based on target shop Item Information, determine candidate shop similar with target shop: the article trading based on candidate shop as follows Article trading avail data indicated by information is ranked up candidate shop, and according to the candidate shop of sequencing selection preset quantity Paving is as candidate shop similar with target shop.

In some embodiments, matching unit 504 is further used for as follows from time similar with target shop It selects the similar article collection for determining article to be assessed in article set indicated by the Item Information in shop: being based on and target shop The article description information in similar candidate shop and the article description information in target shop determine the homologue of article to be assessed Product collection.

In some embodiments, assessment unit 505 can be further used for the concentration of the similar article based on article to be assessed Similar article pricing information, as follows determine have target type attribute label article to be assessed target prices Lattice information: it is determined based on the distribution of the pricing information of the similar article of the similar article concentration of article to be assessed corresponding to preset The pricing information of each type attribute label in type attribute tag set；Determine the valence for corresponding to target type attribute label Lattice information is the target price information of article to be assessed.

In some embodiments, assessment unit 505 can be further used for the concentration of the similar article based on article to be assessed Similar article pricing information distribution, as follows determine correspond to preset type attribute tag set in it is each The pricing information of a type attribute label: point of the pricing information for the similar article that the similar article based on article to be assessed is concentrated Cloth is filtered similar article；Based on the quantity and pricing information of filtered similar article, determines and correspond to preset class The pricing information of each type attribute label in type attribute tags set.

It should be appreciated that all units recorded in device 500 are corresponding with each step in the method with reference to Fig. 2 description. It is equally applicable to device 500 and unit wherein included above with respect to the operation and feature of method description as a result, it is no longer superfluous herein It states.

The device 500 for pushed information of the above embodiments of the present application, by the first determination unit based on having obtained The operation associated information of article to be assessed determines the attention rate information and price elasticity information of article to be assessed, and subsequent second determines Unit determines the attention rate information and price elasticity information pair with article to be assessed from preset type attribute tag set The target type attribute label answered, then acquiring unit obtains the Item Information in candidate shop and provides the mesh of article to be assessed Mark the Item Information in shop, wherein Item Information includes at least article description information and item price information, then matching unit The Item Information of Item Information and candidate shop based on target shop determines the similar article collection of article to be assessed, wherein The similar article that the similar article of article to be assessed is concentrated is the article that candidate shop provides, and assessment is based on article to be assessed later Similar article concentrate similar article pricing information determine have target type attribute label article to be assessed target Pricing information, last push unit are pushed target price information as the price evaluation result of article to be assessed, are realized The item price assessment and push of automation.Due to establishing the attention rate information and price of article when carrying out price evaluation Being associated between elastic information and item price can more accurately orient the price of article, and then promote the price of push The accuracy of information.

Below with reference to Fig. 6, it illustrates the computer systems 600 for the server for being suitable for being used to realize the embodiment of the present application Structural schematic diagram.Server shown in Fig. 6 is only an example, should not function and use scope band to the embodiment of the present application Carry out any restrictions.

As shown in fig. 6, computer system 600 includes central processing unit (CPU) 601, it can be read-only according to being stored in Program in memory (ROM) 602 or be loaded into the program in random access storage device (RAM) 603 from storage section 608 and Execute various movements appropriate and processing.In RAM 603, also it is stored with system 600 and operates required various programs and data. CPU 601, ROM 602 and RAM 603 are connected with each other by bus 604.Input/output (I/O) interface 605 is also connected to always Line 604.

I/O interface 605 is connected to lower component: the importation 606 including keyboard, mouse etc.；It is penetrated including such as cathode The output par, c 607 of spool (CRT), liquid crystal display (LCD) etc. and loudspeaker etc.；Storage section 608 including hard disk etc.； And the communications portion 609 of the network interface card including LAN card, modem etc..Communications portion 609 via such as because The network of spy's net executes communication process.Driver 610 is also connected to I/O interface 605 as needed.Detachable media 611, such as Disk, CD, magneto-optic disk, semiconductor memory etc. are mounted on as needed on driver 610, in order to read from thereon Computer program be mounted into storage section 608 as needed.

Particularly, in accordance with an embodiment of the present disclosure, it may be implemented as computer above with reference to the process of flow chart description Software program.For example, embodiment of the disclosure includes a kind of computer program product comprising be carried on computer-readable medium On computer program, which includes the program code for method shown in execution flow chart.In such reality It applies in example, which can be downloaded and installed from network by communications portion 609, and/or from detachable media 611 are mounted.When the computer program is executed by central processing unit (CPU) 601, limited in execution the present processes Above-mentioned function.It should be noted that computer-readable medium described herein can be computer-readable signal media or Computer readable storage medium either the two any combination.Computer readable storage medium for example can be --- but Be not limited to --- electricity, magnetic, optical, electromagnetic, infrared ray or semiconductor system, device or device, or any above combination. The more specific example of computer readable storage medium can include but is not limited to: have one or more conducting wires electrical connection, Portable computer diskette, hard disk, random access storage device (RAM), read-only memory (ROM), erasable type may be programmed read-only deposit Reservoir (EPROM or flash memory), optical fiber, portable compact disc read-only memory (CD-ROM), light storage device, magnetic memory Part or above-mentioned any appropriate combination.In this application, computer readable storage medium, which can be, any include or stores The tangible medium of program, the program can be commanded execution system, device or device use or in connection.And In the application, computer-readable signal media may include in a base band or the data as the propagation of carrier wave a part are believed Number, wherein carrying computer-readable program code.The data-signal of this propagation can take various forms, including but not It is limited to electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be computer Any computer-readable medium other than readable storage medium storing program for executing, the computer-readable medium can send, propagate or transmit use In by the use of instruction execution system, device or device or program in connection.Include on computer-readable medium Program code can transmit with any suitable medium, including but not limited to: wireless, electric wire, optical cable, RF etc., Huo Zheshang Any appropriate combination stated.

The calculating of the operation for executing the application can be write with one or more programming languages or combinations thereof Machine program code, described program design language include object oriented program language-such as Java, Smalltalk, C+ +, it further include conventional procedural programming language-such as " C " language or similar programming language.Program code can Fully to execute, partly execute on the user computer on the user computer, be executed as an independent software package, Part executes on the remote computer or executes on a remote computer or server completely on the user computer for part. In situations involving remote computers, remote computer can pass through the network of any kind --- including local area network (LAN) Or wide area network (WAN)-is connected to subscriber computer, or, it may be connected to outer computer (such as utilize Internet service Provider is connected by internet).

Flow chart and block diagram in attached drawing are illustrated according to the system of the various embodiments of the application, method and computer journey The architecture, function and operation in the cards of sequence product.In this regard, each box in flowchart or block diagram can generation A part of one module, program segment or code of table, a part of the module, program segment or code include one or more use The executable instruction of the logic function as defined in realizing.It should also be noted that in some implementations as replacements, being marked in box The function of note can also occur in a different order than that indicated in the drawings.For example, two boxes succeedingly indicated are actually It can be basically executed in parallel, they can also be executed in the opposite order sometimes, and this depends on the function involved.Also it to infuse Meaning, the combination of each box in block diagram and or flow chart and the box in block diagram and or flow chart can be with holding The dedicated hardware based system of functions or operations as defined in row is realized, or can use specialized hardware and computer instruction Combination realize.

Being described in unit involved in the embodiment of the present application can be realized by way of software, can also be by hard The mode of part is realized.Described unit also can be set in the processor, for example, can be described as: a kind of processor packet Include the first determination unit, the second determination unit, acquiring unit, matching unit and push unit.Wherein, the title of these units The restriction to the unit itself is not constituted under certain conditions, for example, the first determination unit is also described as " based on The operation associated information of the article to be assessed obtained determines the attention rate information of article to be assessed and the list of price elasticity information Member ".

As on the other hand, present invention also provides a kind of computer-readable medium, which be can be Included in device described in above-described embodiment；It is also possible to individualism, and without in the supplying device.Above-mentioned calculating Machine readable medium carries one or more program, when said one or multiple programs are executed by the device, so that should Device: the attention rate information and price elasticity of article to be assessed are determined based on the operation associated information of the article to be assessed obtained Information；The attention rate information and price elasticity information pair with article to be assessed are determined from preset type attribute tag set The target type attribute label answered；Obtain the Item Information in candidate shop and the article in the target shop that article to be assessed is provided Information, wherein Item Information includes at least article description information and item price information；Item Information based on target shop and The Item Information in candidate shop determines the similar article collection of article to be assessed, wherein the similar article of article to be assessed is concentrated Similar article be article that candidate shop provides；The price letter for the similar article that similar article based on article to be assessed is concentrated Breath determines the target price information with the article to be assessed of target type attribute label；Using target price information as to be assessed The price evaluation result of article is pushed.

Above description is only the preferred embodiment of the application and the explanation to institute's application technology principle.Those skilled in the art Member is it should be appreciated that invention scope involved in the application, however it is not limited to technology made of the specific combination of above-mentioned technical characteristic Scheme, while should also cover in the case where not departing from foregoing invention design, it is carried out by above-mentioned technical characteristic or its equivalent feature Any combination and the other technical solutions formed.Such as features described above has similar function with (but being not limited to) disclosed herein Can technical characteristic replaced mutually and the technical solution that is formed.

Claims (22)

1. a kind of method for pushed information, comprising:

The attention rate information and price of the article to be assessed are determined based on the operation associated information of the article to be assessed obtained Elastic information；

It determines to believe with the attention rate information of the article to be assessed and price elasticity from preset type attribute tag set Cease corresponding target type attribute label；

Obtain the Item Information in candidate shop and the Item Information in the target shop that the article to be assessed is provided, wherein institute Item Information is stated including at least article description information and item price information；

The Item Information of Item Information and the candidate shop based on the target shop determines the article to be assessed Similar article collection, wherein the similar article that the similar article of the article to be assessed is concentrated is the object that the candidate shop provides Product；

Determine that there is target type attribute based on the pricing information for the similar article that the similar article of the article to be assessed is concentrated The target price information of the article to be assessed of label；

It is pushed the target price information as the price evaluation result of the article to be assessed.

2. according to the method described in claim 1, wherein, the operation associated information of the article to be assessed include provide it is described to Assess the data on flows and transaction data of each article in the target shop of article；

The operation associated information based on the article to be assessed obtained determine the article to be assessed attention rate information and Price elasticity information, comprising:

The data on flows of the article to be assessed is determined based on the data on flows of each article in the target shop；

The data on flows of each category article in the target shop is counted, each category in the target shop is obtained Data on flows；

According to the data on flows of each article in the data on flows of article to be assessed in the target shop, the target shop, with And the data on flows of each category determines the attention rate information of the article to be assessed in the target shop；

The transaction data for counting the affiliated category of article to be assessed described in the transaction data in the target shop, calculates object to be assessed The price elasticity data of each article under the affiliated category of product；

According to the price bullet of each article under the price elasticity data of the article to be assessed and the affiliated category of article to be assessed Property data determine the price elasticity information of the article to be assessed.

3. according to the method described in claim 2, wherein, the flow number according to article to be assessed in the target shop Described in determining according to the data on flows of each category in the data on flows of each article in, the target shop and the target shop The attention rate information of article to be assessed, comprising:

The data on flows of each category determines in data on flows and the target shop based on each article in the target shop Flow reference threshold value；

The data on flows and the flow reference threshold value for comparing the article to be assessed, determine described to be assessed according to comparison result The attention rate information of article.

4. according to the method described in claim 2, wherein, price elasticity data according to the article to be assessed and described The price elasticity data of each article determine the price elasticity information of the article to be assessed under the affiliated category of article to be assessed, packet It includes:

Elastic data reference threshold is determined based on the price elasticity data of each article under the affiliated category of article to be assessed；

Judge the article to be assessed indicated by the transaction data of article to be assessed in the transaction data in the target shop Whether quantity on order reaches the first preset threshold；

If the quantity on order of the article to be assessed indicated by the transaction data of the article to be assessed reaches the first default threshold Value, the comparison result of price elasticity data and the elastic data reference threshold based on the article to be assessed determine it is described to Assess the price elasticity information of article；

If it is default that the quantity on order of the article to be assessed indicated by the transaction data of the article to be assessed is not up to first Threshold value judges described to be evaluated indicated by the transaction data of the affiliated brand of article to be assessed in the transaction data in the target shop Whether the quantity on order for estimating the affiliated brand of article reaches the second preset threshold；

If the order numbers of the affiliated brand of article to be assessed indicated by the transaction data of the affiliated brand of article to be assessed Amount reaches the second preset threshold, based on the transaction data of the affiliated brand of article to be assessed in the transaction data in the target shop The price elasticity data of the affiliated brand of article to be assessed are calculated, and according to the price elasticity data of the affiliated brand of article to be assessed The price elasticity information of the article to be assessed is determined with the comparison result of the elastic data reference threshold；

If the order numbers of the affiliated brand of article to be assessed indicated by the transaction data of the affiliated brand of article to be assessed Amount is not up to the second preset threshold, and price elasticity data and the elastic data based on the affiliated category of article to be assessed are joined The comparison result for examining threshold value determines the price elasticity information of the article to be assessed.

5. according to the method described in claim 1, wherein, the Item Information further includes article inventory information and article trading letter Breath；And

The Item Information based on the target shop and the Item Information in the candidate shop determine the object to be assessed The similar article collection of product, comprising:

The Item Information of Item Information and the candidate shop based on the target shop is determined and target shop phase As candidate shop；

It is determined in article set indicated by Item Information from candidate shop similar with the target shop described to be evaluated Estimate the similar article collection of article.

6. according to the method described in claim 5, wherein, the Item Information based on the target shop and the candidate shop The Item Information of paving determines candidate shop similar with the target shop, comprising:

Candidate shop similar with the target shop is filtered out based on the similarity between at least one of following:

Phase between the Transaction Income data of same category article indicated by similarity, article trading information between article inventory information Similarity between the Transaction Income data of the same brand objects like indicated by degree, article trading information.

7. according to the method described in claim 5, wherein, the Item Information based on the target shop and the candidate shop The Item Information of paving determines candidate shop similar with the target shop, further includes:

Article trading avail data indicated by article trading information based on candidate shop is ranked up the candidate shop, And according to the candidate shop of the sequencing selection preset quantity as candidate shop similar with the target shop.

8. according to the method described in claim 5, wherein, the article from candidate shop similar with the target shop is believed The similar article collection of the article to be assessed is determined in the indicated article set of breath, comprising:

The article of article description information and the target shop based on candidate shop similar with the target shop describes letter Breath determines the similar article collection of the article to be assessed.

9. method according to claim 1-8, wherein the similar article collection based on the article to be assessed In similar article pricing information determine have target type attribute label the article to be assessed target price information, Include:

It is determined based on the distribution of the pricing information of the similar article of the similar article concentration of the article to be assessed corresponding to default Type attribute tag set in each type attribute label pricing information；

Determine that the pricing information for corresponding to target type attribute label is the target price information of the article to be assessed.

10. according to the method described in claim 9, wherein, phase that the similar article based on the article to be assessed is concentrated The each type attribute label corresponded in preset type attribute tag set is determined like the distribution of the pricing information of article Pricing information, comprising:

The distribution of the pricing information for the similar article that similar article based on the article to be assessed is concentrated, to the similar article It is filtered；

Based on the quantity and pricing information of filtered similar article, determines and correspond in preset type attribute tag set The pricing information of each type attribute label.

11. a kind of device for pushed information, comprising:

First determination unit, for determining the article to be assessed based on the operation associated information of the article to be assessed obtained Attention rate information and price elasticity information；

Second determination unit, for determining the attention rate with the article to be assessed from preset type attribute tag set Information and the corresponding target type attribute label of price elasticity information；

Acquiring unit, for obtaining the article of the Item Information in candidate shop and the target shop of the offer article to be assessed Information, wherein the Item Information includes at least article description information and item price information；

Matching unit, the Item Information for Item Information and the candidate shop based on the target shop are determined described The similar article collection of article to be assessed, wherein the similar article that the similar article of the article to be assessed is concentrated is the candidate The article that shop provides；

The pricing information determination of assessment unit, the similar article for the similar article concentration based on the article to be assessed has The target price information of the article to be assessed of target type attribute label；

Push unit, for being pushed the target price information as the price evaluation result of the article to be assessed.

12. device according to claim 11, wherein the operation associated information of the article to be assessed includes described in offer The data on flows and transaction data of each article in the target shop of article to be assessed；

First determination unit is further used for determining the attention rate information and valence of the article to be assessed as follows Lattice elastic information:

The data on flows of the article to be assessed is determined based on the data on flows of each article in the target shop；

The data on flows of each category article in the target shop is counted, each category in the target shop is obtained Data on flows；

According to the data on flows of each article in the data on flows of article to be assessed in the target shop, the target shop, with And the data on flows of each category determines the attention rate information of the article to be assessed in the target shop；

The transaction data for counting the affiliated category of article to be assessed described in the transaction data in the target shop, calculates object to be assessed The price elasticity data of each article under the affiliated category of product；

According to the price bullet of each article under the price elasticity data of the article to be assessed and the affiliated category of article to be assessed Property data determine the price elasticity information of the article to be assessed.

13. device according to claim 12, wherein first determination unit is further used for as follows really The attention rate information of the fixed article to be assessed:

The data on flows of each category determines in data on flows and the target shop based on each article in the target shop Flow reference threshold value；

The data on flows and the flow reference threshold value for comparing the article to be assessed, determine described to be assessed according to comparison result The attention rate information of article.

14. device according to claim 12, wherein first determination unit is further used for as follows really The price elasticity information of the fixed article to be assessed:

Elastic data reference threshold is determined based on the price elasticity data of each article under the affiliated category of article to be assessed；

Judge the article to be assessed indicated by the transaction data of article to be assessed in the transaction data in the target shop Whether quantity on order reaches the first preset threshold；

If the quantity on order of the article to be assessed indicated by the transaction data of the article to be assessed reaches the first default threshold Value, the comparison result of price elasticity data and the elastic data reference threshold based on the article to be assessed determine it is described to Assess the price elasticity information of article；

If it is default that the quantity on order of the article to be assessed indicated by the transaction data of the article to be assessed is not up to first Threshold value judges described to be evaluated indicated by the transaction data of the affiliated brand of article to be assessed in the transaction data in the target shop Whether the quantity on order for estimating the affiliated brand of article reaches the second preset threshold；

If the order numbers of the affiliated brand of article to be assessed indicated by the transaction data of the affiliated brand of article to be assessed Amount reaches the second preset threshold, based on the transaction data of the affiliated brand of article to be assessed in the transaction data in the target shop The price elasticity data of the affiliated brand of article to be assessed are calculated, and according to the price elasticity data of the affiliated brand of article to be assessed The price elasticity information of the article to be assessed is determined with the comparison result of the elastic data reference threshold；

If the order numbers of the affiliated brand of article to be assessed indicated by the transaction data of the affiliated brand of article to be assessed Amount is not up to the second preset threshold, and price elasticity data and the elastic data based on the affiliated category of article to be assessed are joined The comparison result for examining threshold value determines the price elasticity information of the article to be assessed.

15. device according to claim 11, wherein the Item Information further includes article inventory information and article trading Information；And

The matching unit is further used for the Item Information based on the target shop and the Item Information in the candidate shop, The similar article collection of the article to be assessed is determined as follows:

The Item Information of Item Information and the candidate shop based on the target shop is determined and target shop phase As candidate shop；

It is determined in article set indicated by Item Information from candidate shop similar with the target shop described to be evaluated Estimate the similar article collection of article.

16. device according to claim 15, wherein the matching unit is further used for based on the target shop The Item Information of Item Information and the candidate shop determines candidate shop similar with the target shop as follows Paving:

Candidate shop similar with the target shop is filtered out based on the similarity between at least one of following:

Phase between the Transaction Income data of same category article indicated by similarity, article trading information between article inventory information Similarity between the Transaction Income data of the same brand objects like indicated by degree, article trading information.

17. device according to claim 15, wherein the matching unit is also used to the article based on the target shop The Item Information of information and the candidate shop determines candidate shop similar with the target shop as follows:

Article trading avail data indicated by article trading information based on candidate shop is ranked up the candidate shop, And according to the candidate shop of the sequencing selection preset quantity as candidate shop similar with the target shop.

18. device according to claim 15, wherein the matching unit be further used for as follows from institute State the phase that the article to be assessed is determined in article set indicated by the Item Information in the similar candidate shop in target shop Like article collection:

The article of article description information and the target shop based on candidate shop similar with the target shop describes letter Breath determines the similar article collection of the article to be assessed.

19. the described in any item devices of 1-18 according to claim 1, wherein the assessment unit is further used for based on described The pricing information for the similar article that the similar article of article to be assessed is concentrated determines there is target type attribute as follows The target price information of the article to be assessed of label:

It is determined based on the distribution of the pricing information of the similar article of the similar article concentration of the article to be assessed corresponding to default Type attribute tag set in each type attribute label pricing information；

Determine that the pricing information for corresponding to target type attribute label is the target price information of the article to be assessed.

20. device according to claim 19, wherein the assessment unit is further used for based on the article to be assessed Similar article concentrate similar article pricing information distribution, as follows determine correspond to preset type attribute The pricing information of each type attribute label in tag set:

The distribution of the pricing information for the similar article that similar article based on the article to be assessed is concentrated, to the similar article It is filtered；

Based on the quantity and pricing information of filtered similar article, determines and correspond in preset type attribute tag set The pricing information of each type attribute label.

21. a kind of electronic equipment, comprising:

One or more processors；

Storage device, for storing one or more programs,

When one or more of programs are executed by one or more of processors, so that one or more of processors are real The now method as described in any in claim 1-10.

22. a kind of computer storage medium, is stored thereon with computer program, wherein real when described program is executed by processor The now method as described in any in claim 1-10.