CN102722567B - Method and device for screening in-station information - Google Patents
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Abstract
The invention discloses a method and a device for screening in-station information, which screen out category attributes and difference attributes among the in-station information by a technical means of text mining, screen out the in-station information of the same type with higher matching degree by using an identification algorithm of the matching degree of the in-station information of the same type, and compare the in-station information of the same type by the difference attributes. The invention can screen more accurate relevant in-station information, reduces the interface pressure of interaction between the webpage client and the website server, and is convenient for users to compare the inquired relevant in-station information.
Description
Technical field
The present invention relates to Internet Information Service technical field, particularly relate to screening technique and the device of a kind of internal information of standing.
Background technology
Search, classification navigation are to aid in people in the important means being issued as the quick locating desired information in major function website with information.Quantity of information yet with issue every day of this website is very big, navigates even by keyword search or by segmentation classification, and the relevant information being eventually found is still a lot, allows people be difficult to quickly and carries out selecting and decision-making.And when searching station internal information by key word or segmentation classification navigation, all and described key word can be transferred or segment the station internal information that classification is relevant, interface pressure mutual between webpage client and Website server is so made to increase, when visit capacity from client is too much, the systematic function to server impacts, and can cause that server communication is congested even paralyses time serious.The present invention technological means by text mining, it is provided that the recognizer of a kind of similar goods matching degree, helps people to be automatically found most like similar commodity, and by the contrast shopping guide of similar commodity, helps user to be rapidly performed by decision-making in purchasing.
Summary of the invention
It is an object of the invention to propose screening technique and the device of a kind of internal information of standing, it is possible to screen more accurate associated station internal information, reduce interface pressure mutual between webpage client and Website server.
For reaching this purpose, the present invention by the following technical solutions:
The screening technique of a kind of internal information of standing, comprises the following steps:
A, signature identification according to input obtain possesses the station internal information of described signature identification, in parsing key word from the station internal information obtained and being filled up to the attribute field of structured storage form；
B, the key word in described each attribute field of structured storage form is carried out word frequency analysis, determine category attribute and difference attribute；
C, calculate according to category attribute in the station internal information of described acquisition and be currently accessed for the matching degree between internal information and other station internal informations of standing, filter out the matching degree similar coupling station internal information higher than preset matching degree threshold value；
D, the preset attribute stood described similar coupling in internal information judge, filter out the similar coupling station internal information that described preset attribute is abnormal；
E, generate similar coupling station internal information table and show the difference attribute of internal information of standing in table.
In step B, occurrence number in each attribute field is more than the key word high-frequency key words as this attribute of the first predetermined threshold value, described high-frequency key words occurring, ratio is more than the attribute of the second predetermined threshold value and is defined as category attribute, and other attributes outside described category attribute are difference attribute.
After step B determines category attribute and difference attribute, calculate the weight of each attribute.
In step C, according to the weight of each category attribute, utilize the text Similarity matching algorithm of weighting must arrive at a station the matching degree between internal information.
In step E, the station internal information in the internal information table of described similar coupling station arranges from big to small according to the matching degree being currently accessed for station internal information, when the arbitrary station internal information in table is accessed, shows the difference attribute of other station internal informations in table simultaneously.
The screening plant of a kind of internal information of standing, including information analysis module, attributive analysis module, similar matching module, mistake filtering module and differential disply module, described information analysis module, attributive analysis module, similar matching module, mistake filtering module and differential disply module are sequentially connected with, wherein
Information analysis module, obtains for the signature identification according to input and possesses the station internal information of described signature identification, in parsing key word from the station internal information obtained and being filled up to the attribute field of structured storage form；
Attributive analysis module, for the key word in described each attribute field of structured storage form is carried out word frequency analysis, determines category attribute and difference attribute；
Similar matching module, is currently accessed for, in the station internal information calculating described acquisition according to category attribute, the matching degree between internal information and other station internal informations of standing, and filters out the matching degree similar coupling station internal information higher than preset matching degree threshold value；
Mistake filtering module, for judging the preset attribute in the internal information of described similar coupling station, filters out the similar coupling station internal information that described preset attribute is abnormal；
Differential disply module, for generating similar coupling station internal information table and showing the difference attribute of internal information of standing in table.
Described attributive analysis module, occurrence number in each attribute field is more than or equal to the key word high-frequency key words as this attribute of the first predetermined threshold value, described high-frequency key words occurring, ratio is more than or equal to the attribute of the second predetermined threshold value and is defined as category attribute, and other attributes outside described category attribute are difference attribute.
Described attributive analysis module, is additionally operable to the weight calculating each category attribute with difference attribute.
Described similar matching module according to the weight of each category attribute, utilizes the text Similarity matching algorithm of weighting must arrive at a station the matching degree between internal information.
Station internal information in the similar coupling station internal information table that described differential disply module generates arranges from big to small according to the matching degree being currently accessed for station internal information, when arbitrary station internal information in table is accessed, show the difference attribute of other station internal informations in table simultaneously.
Use technical scheme, by the technological means of text mining, the recognizer of a kind of similar station internal information matching degree is provided, more accurate associated station internal information can be screened, reduce interface pressure mutual between webpage client and Website server, and facilitate user that the associated station internal information inquired is contrasted.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of the station internal information screening technique that the specific embodiment of the invention provides.
Fig. 2 is the structural representation of the station internal information screening plant that the specific embodiment of the invention provides.
Fig. 3 is the schematic flow sheet during station internal information screening technique applying the specific embodiment of the invention to provide as a example by electricity business website.
Detailed description of the invention
Technical scheme is applicable to provide information promulgating platform and the channel website as major function to the public, such as ecommerce, with large-scale synthesis information promulgating platform websites such as city information, and real estate, travel, recruit, marriage-seeking etc. the website with subject information issuing function, by the technological means of text mining, the recognizer of a kind of similar station internal information matching degree is provided, more accurate associated station internal information can be screened, reduce interface pressure mutual between webpage client and Website server.
Further illustrate technical scheme below in conjunction with the accompanying drawings and by detailed description of the invention.
Fig. 1 is the schematic flow sheet of the station internal information screening technique that the specific embodiment of the invention provides.As it is shown in figure 1, the method includes:
Step S101, obtains according to the signature identification of input and possesses the station internal information of described signature identification, in parsing key word from the station internal information obtained and being filled up to the attribute field of structured storage form.
Described signature identification refer to the title of information or key word, kind and other information to be filtered out is had the reference information of mark action.System passes through whole internal informations of standing with the acquisition of category information import feature interface routine with described signature identification according to the signature identification of input.
Utilizing conventional text participle technique, described title and the content of each information to carry out keyword resolution by participle, obtain the key word of all kinds of attribute descriptions about each information, same attribute connects with cornet when having multiple key word.
If original information describes structuring in website, the mapping relations having described in i.e. between the key word of description effect and described attribute have existed, then be filled up to by the key word parsed in the form of the message structureization storage data base that attribute field is row name.When the description of original information does not has structuring in website, need the mapping dictionary first setting up key word with attribute field, then the key word counter structure parsed is stored in each attribute column of tables of data.
Step S102, carries out word frequency analysis to the key word in described each attribute field of structured storage form, determines category attribute and difference attribute.
Using occurrence number in each attribute field more than the key word of the first predetermined threshold value as the high-frequency key words of this attribute, described high-frequency key words occurring, ratio is more than the attribute of the second predetermined threshold value and is defined as category attribute, and other attributes outside described category attribute are difference attribute.
The information key of structured storage is analyzed, obtain the key word that in each Column Properties, frequency of occurrence is higher, occurrence number in each attribute field is more than or equal to the key word high-frequency key words as this attribute of the first predetermined threshold value, and the number of times occurred in each high-frequency key words in different information is added up.For a certain attribute field, if number of times/total line number (i.e. total information number) that list records medium-high frequency key word occurs in different rows (i.e. different information) is more than or equal to the second predetermined threshold value, then using this attribute as category attribute, category attribute is used for determining whether information is similar, only just will reveal whether to contrast with category information；Other attribute is as difference attribute, and for after having locked with category information, contrast is with the key difference in category information.
After the classification identifying each attribute, also need to identify the weight of each attribute, identifying of weight on the one hand can be according to the number of times ratio of high frequency words appearance, on the one hand can according to each attribute input or number of times of the behavior of click when user searches for or when carrying out filtering sequence, and be standardized two class data processing and weighted sum considers.The weighted value of each attribute is calculated by equation below:
There is ratio+standardized number of clicks * 2 in Attribute Weight weight values=1+ high frequency words
Step S103, calculates according to category attribute in the station internal information of described acquisition and is currently accessed for the matching degree between internal information and other station internal informations of standing, and filters out the matching degree similar coupling station internal information higher than preset matching degree threshold value.
The calculating of matching degree has only to consider category attribute, can obtain by calculating the text similarity of the category attribute of two information of list above matrix.Representing the information 1 vector to each category attribute with vector A, vector B represents the information 2 vector to each category attribute, then information 1 can calculate with the included angle cosine similarity formula of text below vector with the matching degree of information 2:
If considering the weight of attribute, it is only necessary to each dimension to A, B vector, being multiplied by the weighted value of each self-corresponding attribute respectively, then applying mechanically above-mentioned formula and carry out calculating.
The calculating of matching degree can also be realized by simpler algorithm, such as calculates the number of times occurring same words in each A generic attribute, and aggregative weighted summation.
Setting matching degree threshold value, if the matching degree between the station internal information of certain information and current accessed is more than or equal to this threshold value, then two information are to mate similar same category information.If the matching degree between the station internal information of certain information and current accessed is less than or equal to this threshold value, the widely different of internal information that stand of this information and current accessed is then described, it is not belonging to same category information, need not occur in follow-up information gap contrast, therefore this information filtering be fallen.Filtered by coupling, needs carry out the information that contrast selects focus on a small amount of in the range of, greatly help user to improve the efficiency of decision-making, and reduce the interface pressure of client terminal web page and server interaction, systematic function is also had the biggest lifting.
Step S104, judges the preset attribute in the internal information of described similar coupling station, filters out the similar coupling station internal information that described preset attribute is abnormal.
After determining similar match information, for preventing the inaccurate or imperfect of some information to be classified as same category information by mistake, filtered by error protection and some preset attribute are judged, filter out the exception item in match information, it is ensured that the result of coupling is the most reliable.
Step S105, generates similar coupling station internal information table and shows the difference attribute of internal information of standing in table.Station internal information in the internal information table of described similar coupling station arranges from big to small according to the matching degree being currently accessed for station internal information, when the arbitrary station internal information in table is accessed, shows the difference attribute of other station internal informations in table simultaneously.
Accordingly, the specific embodiment of the invention provides a kind of station internal information screening plant, as shown in Figure 2, this device includes information analysis module 201, attributive analysis module 202, similar matching module 203, mistake filtering module 204 and differential disply module 205, described information analysis module 201, attributive analysis module 202, similar matching module 203, mistake filtering module 204 and differential disply module 205 are sequentially connected with, wherein
Information analysis module 201, obtains for the signature identification according to input and possesses the station internal information of described signature identification, in parsing key word from the station internal information obtained and being filled up to the attribute field of structured storage form；
Attributive analysis module 202, for the key word in described each attribute field of structured storage form is carried out word frequency analysis, determines category attribute and difference attribute；
Similar matching module 203, is currently accessed for, in the station internal information calculating described acquisition according to category attribute, the matching degree between internal information and other station internal informations of standing, and filters out the matching degree similar coupling station internal information higher than preset matching degree threshold value；
Mistake filtering module 204, for judging the preset attribute in the internal information of described similar coupling station, filters out the similar coupling station internal information that described preset attribute is abnormal；
Differential disply module 205, for generating similar coupling station internal information table and showing the difference attribute of internal information of standing in table.
Described attributive analysis module 201, using occurrence number in each attribute field more than the key word of the first predetermined threshold value as the high-frequency key words of this attribute, described high-frequency key words occurring, ratio is more than the attribute of the second predetermined threshold value and is defined as category attribute, and other attributes outside described category attribute are difference attribute.Described attributive analysis module, is additionally operable to the weight calculating each category attribute with difference attribute.
Described similar matching module 203 according to the weight of each category attribute, utilizes the text Similarity matching algorithm of weighting must arrive at a station the matching degree between internal information.
Station internal information in the similar coupling station internal information table that described differential disply module 205 generates arranges from big to small according to the matching degree being currently accessed for station internal information, when arbitrary station internal information in table is accessed, show the difference attribute of other station internal informations in table simultaneously.
Below as a example by electricity business website, further illustrate station internal information screening technique and device that the specific embodiment of the invention provides, to the flow process of electricity station, business website internal information screening as shown in Figure 3:
Step S301, such as the input key word of " one-piece dress " classification or No. ID, obtains such storewide information now by the same classification merchandise news import feature interface routine of information analysis module.
Step S302, utilizes text participle function, by participle, each commodity title and content description is carried out keyword resolution, obtains the key word of every all kinds of attribute description of commodity, and same attribute connects with cornet when having multiple key word.
Step S303, when merchandise news original in website describes structuring, can be filled up to the key word parsed in the form of the message structureization storage data base that attribute field is row name.Such as include following attribute field: title, brand, style, fabric, sleeve length, collar, waist type, lace, style, season, pattern, color, sales volume, credit, price, other, etc..When descriptive labelling information original in website does not has structuring, need the mapping dictionary first setting up key word with attribute field, then the key word counter structure parsed is stored in each attribute column of tables of data.
Step S304, by being analyzed the merchandise news key word of structured storage, obtains the key word that in each Column Properties, frequency of occurrence is higher, and the number of times that each high-frequency key words occurs in different commodity is added up.For a certain attribute field, if number of times/total line number (i.e. total commodity number) >=a certain threshold value that list records medium-high frequency key word occurs in different rows (i.e. different commodity), then using this attribute as category attribute, category attribute is used for determining whether commodity are similar, and the most similar commodity just can show and contrast；Other attribute, as difference attribute, for after having locked similar commodity, contrasts key difference in similar commodity.After the classification identifying each attribute, also need to identify the weight of each attribute, identifying of weight on the one hand can be according to the number of times ratio of high frequency words appearance, on the one hand click on the number of times of behavior when can carry out filtering sequence when user searches for according to each attribute, and be standardized two class data processing and weighted sum considers.
Description example:
As above in table, we will appear from number of times >=2 time as high frequency words, then:
The high frequency words of attribute 1 is a, b, x；
The ratio that a occurs: 3/5=0.6；The ratio that b occurs: 2/5=0.4；The ratio that x occurs: 2/5=0.4；
The high frequency words of attribute 2 is c, z；
The ratio that c occurs: 3/5=0.6；Z occur ratio: 2/5=0.4；
The high frequency words of attribute 3 is e, f；
The ratio that e occurs: 2/5=0.4；The ratio that f occurs: 2/5=0.4；
Attribute 4 does not has high frequency words.
We set high frequency words and ratio >=0.6 threshold value as identification category attribute occur, then attribute 1, attribute 2 belong to category attribute, and attribute 3, attribute 4 belong to difference attribute.
Number of clicks is standardized by we: single attribute number of clicks/such whole attribute numbers of clicks now, after standardization, number of clicks sees the above table.
The weighted value of each attribute calculates by the following method:
There is ratio+standardized number of clicks * 2 in Attribute Weight weight values=1+ high frequency words；
Try to achieve attribute weight as above table, the importance ranking of each attribute:
Attribute 2 > attribute 1 > attribute 3 > attribute 4.
Step S305, after above attributive analysis, so that it may calculate the matching degree of merchandise news.The calculating of merchandise news matching degree has only to consider category attribute, can obtain by calculating the text similarity of two merchandise classification attributes of list above matrix.Representing the commodity 1 vector to different attribute with vector A, vector B represents the commodity 2 vector to different attribute, then commodity 1 can calculate with following cosine similarity formula with the matching similarity of commodity 2:
Consider the weight of attribute, it is only necessary to each dimension to A, B vector, be multiplied by the weighted value of each self-corresponding attribute respectively, then apply mechanically above-mentioned formula and carry out calculating.
The calculating of matching degree can also be realized by simpler algorithm, such as calculates the number of times occurring same words in attribute of all categories, and aggregative weighted summation.
Each commodity and the matching degree of commodity 1 in such as calculating above example:
Commodity 2 and commodity 1 matching degree: 2*2.14+2*2.94=10.16；
Commodity 3 and commodity 1 matching degree: 1*2.14+1*2.94=5.08；
Commodity 4 and commodity 1 matching degree: 0+1*2.94=2.94；
Commodity 5 and commodity 1 matching degree: 0+0=0.
Step S306, sets the threshold value of matching degree as 5, and commodity 2 are both greater than this threshold value with the matching degree of commodity 3, then commodity 2, commodity 3 are to mate similar similar commodity with commodity 1.
Step S307, commodity 4, commodity 5 are because of bigger with commodity 1 matching difference, when carrying out contrasting shopping guide, need not occur, filtered by coupling, needs are carried out contrasting choose the commodity of decision-making focus on a small amount of in the range of, greatly help user to improve and choose the efficiency of decision-making, and reduce the interface pressure of client terminal web page and server interaction, systematic function is also had the biggest lifting.
Step S308, after determining coupling commodity, for preventing some commodity because the inaccurate or imperfect of information is classified as similar commodity by mistake, by the judgement to some preset attribute, filters out the exception item mating in commodity, it is ensured that the result of coupling is the most reliable.Typically can be by the price comparison of commodity, if the commodity that in the commodity mated, existent value is bigger with other commercial variations just may filter that, it is believed that by error hiding.Such as, in coupling commodity, the unit price of certain part commodity A is 50 yuan, and the average unit price of other the similar commodity mated is 500 yuan, then it is assumed that commodity A is the exception item of error hiding, it should reject out from mating commodity.
Step S309, is filtered by matching degree and after error protection filtration, can wait until the list of final similar coupling commodity, and be ranked up by matching degree, and the list of the similar commodity as finally given in this example is: commodity 2, commodity 3.
Step S310, pass through above step, acquisition commodity 1, commodity 2, commodity 3 are similar coupling commodity, when any one in browsing these 3 similar commodity of user, similar for another two coupling commodity carry out contrast simultaneously show, played effect when determining similar coupling commodity due to category attribute, the most similar coupling commodity difference on category attribute is the most notable；Therefore have only to list the difference attribute of these similar commodity when carrying out contrast and showing, and be ranked up by the weight of attribute, as this example has only to show: attribute 3, attribute 4.So shown by the contrast difference of less determinant attribute, user can be helped quickly to make a policy.
Use technical scheme, by the technological means of text mining, the recognizer of a kind of similar station internal information matching degree is provided, more accurate associated station internal information can be screened, reduce interface pressure mutual between webpage client and Website server, and facilitate user that the associated station internal information inquired is contrasted.
The above; being only the present invention preferably detailed description of the invention, but protection scope of the present invention is not limited thereto, and any is familiar with the people of this technology in the technical scope that disclosed herein; the change that can readily occur in or replacement, all should contain within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with scope of the claims.
Claims (8)
1. the screening technique of an internal information of standing, it is characterised in that comprise the following steps:
A, signature identification according to input obtain possesses the station internal information of described signature identification, in parsing key word from the station internal information obtained and being filled up to the attribute field of structured storage form；
B, the key word in described each attribute field of structured storage form is carried out word frequency analysis, determine category attribute and difference attribute；
C, calculate according to category attribute in the station internal information of described acquisition and be currently accessed for the matching degree between internal information and other station internal informations of standing, filter out the matching degree similar coupling station internal information higher than preset matching degree threshold value；
D, the preset attribute stood described similar coupling in internal information judge, filter out the similar coupling station internal information that described preset attribute is abnormal；
E, generate similar coupling station internal information table and show the difference attribute of internal information of standing in table；
Wherein, in step B, occurrence number in each attribute field is more than the key word high-frequency key words as this attribute of the first predetermined threshold value, described high-frequency key words occurring, ratio is more than the attribute of the second predetermined threshold value and is defined as category attribute, and other attributes outside described category attribute are difference attribute.
The screening technique of station the most according to claim 1 internal information, it is characterised in that after determining category attribute and difference attribute in step B, calculate the weight of each attribute.
The screening technique of station the most according to claim 1 internal information, it is characterised in that in step C, according to the weight of each category attribute, utilizes the text Similarity matching algorithm of weighting must arrive at a station the matching degree between internal information.
The screening technique of station the most according to claim 1 internal information, it is characterized in that, in step E, station internal information in the internal information table of described similar coupling station arranges from big to small according to the matching degree being currently accessed for station internal information, when arbitrary station internal information in table is accessed, show the difference attribute of other station internal informations in table simultaneously.
5. the screening plant of an internal information of standing, it is characterized in that, including information analysis module, attributive analysis module, similar matching module, mistake filtering module and differential disply module, described information analysis module, attributive analysis module, similar matching module, mistake filtering module and differential disply module are sequentially connected with, wherein
Information analysis module, obtains for the signature identification according to input and possesses the station internal information of described signature identification, in parsing key word from the station internal information obtained and being filled up to the attribute field of structured storage form；
Attributive analysis module, for the key word in described each attribute field of structured storage form is carried out word frequency analysis, determines category attribute and difference attribute；
Similar matching module, is currently accessed for, in the station internal information calculating described acquisition according to category attribute, the matching degree between internal information and other station internal informations of standing, and filters out the matching degree similar coupling station internal information higher than preset matching degree threshold value；
Mistake filtering module, for judging the preset attribute in the internal information of described similar coupling station, filters out the similar coupling station internal information that described preset attribute is abnormal；
Differential disply module, for generating similar coupling station internal information table and showing the difference attribute of internal information of standing in table；
Wherein, described attributive analysis module, occurrence number in each attribute field is more than or equal to the key word high-frequency key words as this attribute of the first predetermined threshold value, described high-frequency key words occurring, ratio is more than or equal to the attribute of the second predetermined threshold value and is defined as category attribute, and other attributes outside described category attribute are difference attribute.
The screening plant of station the most according to claim 5 internal information, it is characterised in that described attributive analysis module, is additionally operable to the weight calculating each category attribute with difference attribute.
The screening plant of station the most according to claim 5 internal information, it is characterised in that described similar matching module according to the weight of each category attribute, utilizes the text Similarity matching algorithm of weighting must arrive at a station the matching degree between internal information.
The screening plant of station the most according to claim 5 internal information, it is characterized in that, station internal information in the similar coupling station internal information table that described differential disply module generates arranges from big to small according to the matching degree being currently accessed for station internal information, when arbitrary station internal information in table is accessed, show the difference attribute of other station internal informations in table simultaneously.
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| CN108304868A (en) * | 2018-01-25 | 2018-07-20 | 阿里巴巴集团控股有限公司 | Model training method, data type recognition methods and computer equipment |
| CN108734393A (en) * | 2018-05-14 | 2018-11-02 | 平安好房（上海）电子商务有限公司 | Matching process, user equipment, storage medium and the device of information of real estate |
| CN111291176A (en) * | 2018-12-06 | 2020-06-16 | 北京国双科技有限公司 | Hot event mining method and device |
| CN110837619B (en) * | 2019-11-05 | 2022-07-12 | 北京锐安科技有限公司 | Website auditing method, device, equipment and storage medium |
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| CN102419779A (en) * | 2012-01-13 | 2012-04-18 | 青岛理工大学 | Commodity personalized search method and device based on attribute sorting |
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