CN103810626A - Method for online shopping and online shopping intermediary - Google Patents
Method for online shopping and online shopping intermediary Download PDFInfo
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- CN103810626A CN103810626A CN201210453687.5A CN201210453687A CN103810626A CN 103810626 A CN103810626 A CN 103810626A CN 201210453687 A CN201210453687 A CN 201210453687A CN 103810626 A CN103810626 A CN 103810626A
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Abstract
The invention discloses a method for online shopping and an online shopping intermediary. The method comprises the steps of enabling the online shopping intermediary to receive first commodity query requests sent by an online shopping user, generating and/or modifying to-be-purchased commodity necessary conditions and to-be-purchased commodity optimization conditions, and generating and/or modifying second commodity query requests; enabling the online shopping intermediary to send the second commodity query requests to an online shopping merchant; enabling the online shopping intermediary to receive second commodity query response sent by the online shopping merchant; enabling the online shopping intermediary to utilize a matching degree algorithm to calculate the commodity matching degree and/or the attribute matching degree of candidate commodities; and enabling the online shopping intermediary to generate first commodity query response. The problem that the existing online shopping process is complex and shopping experience is poor is solved, the online shopping user does not need to manually input mail delivery information and payment information, and personalized network searching and shopping recommending functions are provided.
Description
Technical field
The present invention relates to e-commerce field, be specifically related to method and the net purchase intermediary of shopping at network.
Background technology
What shopping at network was bought may be physical goods, as food, clothes, may be also virtual goods, as e-book.Shopping at network has become one of main shopping way, and netizen buys plane ticket, clothes, cosmetics, electronic product, food, books on network.According to statistics, China's Mainland in 2011 often on the net the number of users of shopping exceed 1.6 hundred million, within 2011, China's Mainland ecommerce retail sales reaches 1,226 hundred million dollars.
General net purchase flow process roughly comprises following seven steps: the first step, and the commodity that net purchase user need to choose according to oneself utilize search engine or shopping experience in the past to select net purchase businessman; Second step, net purchase user accesses the website of net purchase businessman; The 3rd step, net purchase user typing oneself need to be chosen or interested merchandise news; The 4th step, various candidate's commodity that net purchase user returns net purchase businessman carry out comparison and selection repeatedly; The 5th step, net purchase user determines certain commodity of purchase; The 6th step, net purchase user inputs and determines the Postpass Message of net purchase commodity; The 7th step, net purchase pays the payment of doing shopping, and Enters Your Credit Card Information.
Present shopping at network method is more loaded down with trivial details, and net purchase is experienced poor.First, when each net purchase, net purchase user needs input to carry out the bank card information of network payment needs, and the address information of postal delivery commodity, and net purchase user feels cumbersome.
Secondly, net purchase user requires a great deal of time and just can search out oneself satisfied commodity.As an example of predetermined hotel example, this shortcoming is described below.Net purchase user wants to search a hotel satisfying condition: wherein " move in November 5 2012 date ", " moving in number of days is two days ", " city at place is Shanghai ", " hotel's star is 3 stars ", " can surf the Net " five conditions for meeting, are to expect to meet but nonessential five satisfied conditions at " price is less than 500 yuan of every days ", " hotel provides breakfast ", " periphery convenient traffic ", " hotel's sanitary condition is good ", " house type is single room ".
Net purchase user is in the time searching hotel information, the querying condition arranging may be fairly simple, as net purchase user's querying condition only comprises " moving in November 5 2012 date ", " city at place is Shanghai ", " hotel's star is 3 stars ", more or less a hundred hotel that meets querying condition can be returned in website.Net purchase user need to check successively the details in hotel analyze, relatively to find satisfied hotel, this can expend a large amount of time of net purchase user.Net purchase user can, by increasing gradually new querying condition, as " moving in number of days is two days ", " can surf the Net ", reduce the scope, but still can return to tens hotels.
Due to these tens hotels all meet net purchase user arrange five must satisfy condition, any one hotel, net purchase user can accept.But net purchase user need to analyze these tens hotels, comparison, selects a comparatively satisfied hotel.Net purchase user need to check whether they meet " house type is single room ", " price is less than 500 yuan of every days ", " hotel provides breakfast ", " periphery convenient traffic ", " hotel's sanitary condition is good " five satisfied conditions of expectation.Possible some hotel does not meet one or two that five expectations satisfy condition, and as some hotel does not provide breakfast, the sanitary condition in some hotel is not fine, and some hotel does not have single room vacant room.In addition, for " price is less than 500 yuan of every days " and " periphery convenient traffic " these two conditions, may there is different satisfactions.For net purchase user and so, the price of wishing hotel meets and is less than 500 yuan every day, and price is lower, and net purchase user is more satisfied.For " periphery convenient traffic " condition, net purchase user can feel " within the scope of 200 meters of subway stations ", than " apart within the scope of 200 meters, bus station " more attractive.
Possible these tens hotels, some hotel's price comparison is low, but sanitary condition is not so good and traffic is not too convenient; Some hotel's moderate cost, sanitary condition is also good, but breakfast is not provided; Some hotel's price is more expensive, and sanitary condition is good, convenient traffic, and free breakfast is provided.Net purchase user, according to individual consumption preference and the object (public affair is gone on business or individual vacation tour) of this time moving in hotel, compares, accepts or rejects, sorts these tens hotels, then selects the hotel that individual is satisfied.Obviously, net purchase user need to expend a large amount of time and analyzes, more just can find satisfied hotel.
Summary of the invention
The technical problem to be solved in the present invention is that present shopping at network process is loaded down with trivial details, shopping health check-up is poor.
For solving the problems of the technologies described above, the invention provides a kind of method of shopping at network, comprising:
Net purchase intermediary is by HTML (Hypertext Markup Language) (Hypertext Transfer Protocol, be called for short HTTP) receive the first merchandise query request that net purchase user sends and or the first merchandise query request revise indication, in wherein said the first merchandise query request, carry merchandise query condition;
Described net purchase intermediary generate and or revise goods for purchase necessary condition and goods for purchase optimum condition;
Described net purchase intermediary generate and or the second merchandise query request of modification, merchandise query condition is carried in described the second merchandise query request;
Described net purchase intermediary sends the second merchandise query request by HTML (Hypertext Markup Language) to net purchase businessman;
Described net purchase intermediary receives by HTML (Hypertext Markup Language) the second merchandise query response that described net purchase businessman sends, and candidate's merchandise news is carried in described the second merchandise query response;
Described net purchase intermediary utilize matching degree algorithm calculate candidate's commodity in described the second merchandise query response goods matching degree and or attributes match degree, described goods matching degree is used for measuring the degree that candidate's commodity meet net purchase user expection and require, and described attributes match degree is used for the degree that metric attribute meets net purchase user expection and requires;
Described net purchase intermediary generates the first merchandise query response, and candidate's merchandise news is carried in described the first merchandise query response;
Described net purchase intermediary sends the first merchandise query response by HTML (Hypertext Markup Language) to described net purchase user;
Described net purchase intermediary receives by HTML (Hypertext Markup Language) the net purchase feedback that described net purchase user sends;
Described net purchase intermediary create and or upgrade described net purchase user's personalization preferences, described personalization preferences comprise following at least one: attribute bias, matching degree algorithm parameter.
Further, described net purchase intermediary receives described net purchase user's customized information by HTML (Hypertext Markup Language), comprise following at least one: net purchase user basic document information, payment information, Postpass Message, sequence information, net purchase contextual information, net purchase user's network browsing information, social network information.
Preferably, described net purchase contextual information comprise following at least one: terminal device information, geographic position, time, network environment information, weather conditions, querying triggering background;
Described intermediary of network is according to described net purchase contextual information, generate and or revise described goods for purchase necessary condition and or described goods for purchase optimum condition;
Described intermediary of network, according to described net purchase contextual information, upgrades described net purchase user's personalization preferences.
Preferably, described net purchase intermediary according to described net purchase user's described personalization preferences and or described net purchase contextual information generate commercial product recommending information, send described commercial product recommending information by HTML (Hypertext Markup Language) to described net purchase user.
Preferably, described net purchase intermediary measures the satisfaction of described net purchase user for described shopping intermediary.
Preferably, described net purchase intermediary receives by HTML (Hypertext Markup Language) the net purchase that described net purchase user sends and confirms indication, in order to confirm selected buy certain commodity and or Postpass Message, and or payment information;
Described net purchase intermediary sends the indication of net purchase result by HTML (Hypertext Markup Language) to described net purchase user, in order to represent to buy whether success.
For solving the problems of the technologies described above, the present invention also provides a kind of net purchase intermediary, comprising:
Net purchase user interactive module, for by HTML (Hypertext Markup Language) receive described net purchase user the first merchandise query request and or the first merchandise query request revise indication, send the first merchandise query response by HTML (Hypertext Markup Language) to described net purchase user, receive by HTML (Hypertext Markup Language) the net purchase feedback that described net purchase user sends, in wherein said the first merchandise query request, carry merchandise query condition, candidate's merchandise news is carried in described the first merchandise query response;
Net purchase businessman interactive module, for sending the second merchandise query request by HTML (Hypertext Markup Language) to described net purchase businessman, receive by HTML (Hypertext Markup Language) the second merchandise query response that described net purchase businessman sends, merchandise query condition is carried in wherein said the second merchandise query request, and candidate's merchandise news is carried in described the second merchandise query response;
Personalization preferences administration module, for create and or upgrade described net purchase user's personalization preferences, described personalization preferences comprise following at least one: attribute bias, matching degree algorithm parameter;
Merchandise query request processing module for generate and or revise goods for purchase necessary condition and or goods for purchase optimum condition, generate and or the second merchandise query request of modification;
Matching degree algoritic module, for the goods matching degree of calculated candidate commodity and or attributes match degree, described goods matching degree is used for measuring the degree that candidate's commodity meet net purchase user expection and require, and described attributes match degree is used for the degree that metric attribute meets net purchase user expection and requires.
Further, described net purchase user interactive module and or described net purchase businessman interactive module receive described net purchase user's customized information by HTML (Hypertext Markup Language), comprise following at least one: net purchase user basic document information, payment information, Postpass Message, sequence information, net purchase contextual information, net purchase user's network browsing information, social network information.
Preferably, described net purchase contextual information comprise following at least one: terminal device information, geographic position, time, network environment information, weather conditions, querying triggering background;
Described merchandise query request processing module is according to described net purchase contextual information, generate and or revise goods for purchase necessary condition and or goods for purchase optimum condition;
Described personalization preferences administration module, according to described net purchase contextual information, upgrades described net purchase user's personalization preferences.
Preferably, described intermediary of network also comprises recommending module, for according to described net purchase user's described personalization preferences and or described net purchase contextual information generate commercial product recommending information;
Preferably, described intermediary of network also comprises customer satisfaction tracking module, for measuring the satisfaction of described net purchase user for the described intermediary that does shopping.
Preferably, described net purchase user interactive module receives by HTML (Hypertext Markup Language) the net purchase that described net purchase user sends and confirms indication, in order to confirm selected buy certain commodity and or Postpass Message, and or payment information;
Described net purchase intermediary sends the indication of net purchase result by HTML (Hypertext Markup Language) to described net purchase user, in order to represent to buy whether success.
The present invention at least has following beneficial effect:
(1) avoid the manual typing Postpass Message of net purchase user and payment information.Net purchase intermediary to the robotization of net purchase businessman send Postpass Message and payment information, net purchase user needn't manual typing Postpass Message and payment information.
(2) personalized web search.Net purchase intermediary record and study net purchase user's click, browse, the network behavior such as purchase, determine net purchase user's personalization preferences.Intelligently commodity are searched for, compare, are selected according to net purchase user's personalization preferences, net purchase user needn't carry out manpower comparing, select, shorten net purchase user's net purchase process.
(3) shopping recommendation function.Net purchase user's personalization preferences is understood by net purchase intermediary, can recommend appropriate commodity to net purchase user according to user's personalization preferences.
Accompanying drawing explanation
Accompanying drawing described herein is used to provide a further understanding of the present invention, forms the application's a part, and schematic description and description of the present invention is used for explaining the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings:
Fig. 1 is net purchase system schematic
Fig. 2 is net purchase user, net purchase intermediary, the mutual net purchase schematic flow sheet of the tripartite of net purchase businessman
Fig. 3 is that net purchase user basic document information is given an example
Fig. 4 is that net purchase contextual information is given an example
Fig. 5 is that the attribute in net purchase commodity hotel is given an example
Fig. 6 is that net purchase user's attribute bias is given an example
Fig. 7 is that goods for purchase necessary condition and forward purchasing commodity optimum condition are given an example
Fig. 8 is that the computing method of attributes match degree and goods matching degree are given an example
Fig. 9 is that net purchase user's attribute weight is given an example
Figure 10 is the schematic flow sheet of revising the first merchandise query request
Figure 11 is the schematic flow sheet of revising the second merchandise query request
Figure 12 is reception and the treatment scheme schematic diagram of net purchase user personalized information
Figure 13 is recommended flowsheet schematic diagram
Figure 14 is process of feedback schematic diagram
Figure 15 utilizes net purchase contextual information to generate the schematic flow sheet of net purchase querying condition
Figure 16 is net purchase intermediary configuration diagram
Figure 17 is the net purchase intermediary configuration diagram of increased functionality
Embodiment
Below in conjunction with the drawings and specific embodiments, the technical solution of the present invention is further elaborated.
Fig. 1 display network purchase system schematic diagram, comprise net purchase user 101, net purchase intermediary 102, and net purchase businessman 103, wherein net purchase intermediary 102 converges net purchase user 101 a large amount of customized informations and net purchase feedback information, and customized information to net purchase user 101 and net purchase feedback carry out intellectual analysis, determine net purchase user 101 personalization preferences.Personalization preferences and the net purchase contextual information of net purchase intermediary 102 based on net purchase user 101, provides personalized commercial articles searching and recommendation to net purchase user 101.Meanwhile, net purchase intermediary 102 to 103 robotizations of net purchase businessman send Postpass Message and payment information, net purchase user 101 needn't manual typing Postpass Message and payment information.Preferably, net purchase user 101 needn't with network businessman 103 direct interactions, and only by with the direct interaction of net purchase intermediary 102 of realizing shopping at network agent functionality, can complete shopping at network.Net purchase intermediary 102 is as the go-between of net purchase user 101 and network businessman 103, respectively with net purchase user 101 and network businessman 103 direct interactions.
Fig. 2 shows net purchase user, net purchase intermediary, the mutual net purchase schematic flow sheet of the tripartite of net purchase businessman.In 1001 steps, net purchase intermediary 102 receives the first merchandise query request that net purchase user 101 sends by http protocol, in wherein said the first merchandise query request, carry the merchandise query condition that net purchase user 101 utilizes HTML (Hypertext Markup Language) (Hypertext Markup Language is called for short HTML) webpage input or selects.Merchandise query condition is now more rough, only reflects net purchase user 101 roughly intention.For example, if net purchase user 101 object is predetermined hotel, the merchandise query condition of carrying in the first merchandise query request may only comprise " moving in the date is on November 10th, 2012 ", " moving in city is Shanghai " two conditions, and the factor that a lot of net purchase users 101 such as " hotel's star ", " hotel's price ", " moving in region ", " convenient traffic ", " whether can surf the Net ", " whether sanitary condition is good " take notice of is not embodied in merchandise query condition.
In 1002 steps, net purchase intermediary 102 is according to the first merchandise query request receiving, and out of Memory, as net purchase user 101 personalization preferences and net purchase contextual information, generates goods for purchase necessary condition and goods for purchase optimum condition.Goods for purchase necessary condition is the condition that commodity must be satisfied, if can not meet necessary condition, thinks that commodity do not meet net purchase user 101 demand.Goods for purchase optimum condition is to expect the satisfied condition of commodity, and net purchase user 101 relatively takes notice of, likes these conditions, but these conditions not necessarily.
Then, net purchase intermediary 102 generates the second merchandise query request based on goods for purchase necessary condition and forward purchasing commodity optimum condition, and wherein merchandise query condition is carried in the second merchandise query request.In merchandise query condition, may comprise whole goods for purchase necessary conditions and goods for purchase optimum condition, also may only comprise part goods for purchase necessary condition and or goods for purchase optimum condition.For example, the commodity optimum condition of supposing net purchase user 101 predetermined hotels includes " being to surf the Net ", but net purchase businessman 103 does not provide " whether can surf the Net " such screening conditions, only whether provide function of surfing the Net in the details text message intermediary Shaoxing rice wine shop, hotel of returning.In such cases, in the second merchandise query request that net purchase intermediary 102 generates, can not comprise " no can online " this querying condition.
In 1003 steps, net purchase intermediary 102 sends the second merchandise query request by http protocol to net purchase businessman 103.Net purchase businessman 103 receives after the second merchandise query request, can process the second merchandise query request, generates the second merchandise query response, and wherein candidate's merchandise news, the price of for example commodity, the detailed description information of commodity are carried in the second merchandise query response.In 1004 steps, net purchase intermediary 102 utilizes http protocol to receive the second merchandise query response.
In 1005 steps, net purchase intermediary 102 utilizes matching degree algorithm to calculate the goods matching degree of candidate's commodity in the second merchandise query response.Goods matching degree is used for measuring the degree that candidate's commodity meet net purchase user expection and require.If candidate's commodity do not meet the essential condition of goods for purchase, do not meet net purchase user's condition completely, its goods matching degree is minimum.For the commodity that meet the essential condition of goods for purchase, goods matching degree is higher, represents that commodity more meet net purchase user's expectation and requirement.Net purchase user 101, according to the goods matching degree of candidate's commodity order from high to low, to the sequence of candidate's commodity, selects the candidate's commodity that come top N (for example, N=5), generates the first merchandise query response of carrying candidate's merchandise news.
In 1006 steps, net purchase intermediary 102 sends to net purchase user 101 by http protocol by the first merchandise query response.The browser of net purchase user 101 terminals can show candidate's merchandise news of the first merchandise query response, may be according to goods matching degree order from high to low, the information of show candidate commodity from top to bottom, as relevant details of condition such as " hotel's star ", " hotel's price ", " convenient traffic ", " whether sanitary condition are good ".Net purchase user 101 may directly select and be presented at uppermost candidate's commodity, also may the multiple candidate's commodity that show simply be browsed and be compared, and then determines one of them.
Then, net purchase user 101 user terminal generates net purchase and confirms indication, is used for showing that net purchase user 101 has selected certain commodity.In 1007 steps, intermediary of network 102 utilizes http protocol to receive the net purchase confirmation indication that net purchase user 101 sends.
In 1008 steps, net purchase intermediary 102 sends Postpass Message and or payment information by http protocol to net purchase user 101 user terminal.Postpass Message is the address information that postal delivery need to be used when commodity, and payment information is the bank card information that need to use while paying.Net purchase user 101 user terminal in html web page, show Postpass Message and or payment information, request net purchase user 101 be confirmed whether Postpass Message and or payment information effective.In 1009 steps, net purchase intermediary 102 utilizes HTTTP agreement to receive net purchase to confirm indication, represents that net purchase user 101 has confirmed Postpass Message and or the validity of payment information.
In 1010 steps, net purchase intermediary 102 sends net purchase by http protocol and confirms indication, wherein comprises the selected commodity of buying of net purchase user 101, net purchase user 101 Postpass Message and or payment information.In 1011 steps, net purchase intermediary 102 utilizes http protocol to receive the indication of net purchase result, in order to represent that whether net purchase is successful.In 1012 steps, intermediary of network 102 sends the indication of net purchase result by http protocol to net purchase user 101 terminal device.Then, net purchase user 101 browser shows net purchase result in html web page.
Embodiment 2
Net purchase user's customized information, comprise following at least one: net purchase user basic document information, payment information, Postpass Message, sequence information, net purchase contextual information, net purchase user's network browsing information, social network information.
Fig. 2 has enumerated several net purchase user basic document items of information, comprises the information such as net purchase user's name, birthday, sex, ID (identity number) card No., phone number, addresses of items of mail, work unit, job overall, religious belief, marital status, hobby, wages and home address.Intermediary of network can use net purchase user basic document information under multiple occasion, for example, uses home address as postal delivery address.
Net purchase contextual information comprise following at least one: terminal device information, geographic position, time, network environment information, weather conditions, querying triggering background.
Net purchase contextual information can be for carrying out personalized recommendation or generating the necessary condition of goods for purchase and goods for purchase optimum condition more accurately to net purchase user.Fig. 4 has enumerated part net purchase item of context information, comprises terminal device information, geographic position, time, network environment information, weather conditions, querying triggering background.Querying triggering background comprises browser type, browser cookie.Geographic position comprises city, place, region and street, and geographic position contributes to determine whether net purchase user is positioned at office, family or hotel.Time refers to current time, can be used for determining whether for working time or quitting time, whether be festivals or holidays, whether have specific characteristics (net purchase user birthday, certain friends birthday).The IP address that network environment information comprises terminal device and accessing Internet mode, contribute to determine no office, family or the hotel of being positioned at.The network behavior that querying triggering background comprises nearest a period of time of net purchase user (in 30 minutes), as the webpage of browsing recently, clicking and content thereof, net purchase behavior record recently, the Email that receives recently, browses, sends and content thereof, the instant communication information (as SMS, Tencent QQ etc.) and the content thereof that receive recently, browse, send, phone and the content thereof answering recently or dial.
Part net purchase contextual information can directly obtain in net purchase intermediary 102 sides, and as IP address of terminal device information, terminal device etc., some informational needs obtains from net purchase user 101 terminal device, as querying triggering background.In order to obtain accurate and valuable net purchase contextual information, net purchase user 101 need to install browser plug-in and or local application, by browser plug-in and or local application collect, process and send net purchase contextual information to net purchase intermediary 102.
Embodiment 3
Every class commodity all have item property, and net purchase user's goods for purchase necessary condition and goods for purchase optimum condition are actually some restrictive conditions to item property.As for net purchase hotel commodity, " hotel's star ", " house type " are all some item property, and " hotel's star is 3 stars ", " house type is single room " are some restrictive conditions to item property.
Fig. 5 has enumerated the extensive stock attribute in net purchase commodity hotels, comprise move in city, hotel's star, price, house type, move in the date, move in number of days, whether breakfast be provided, whether traffic convenient, can online, sanitary condition, whether be positioned at certain appointed place annex, whether allow freely to cancel order, client comments on situation.Wherein hotel's star comprises altogether without star, 3 stars, 4 stars, 5 stars, surpasses five grades of 5 star, and internal number corresponds to respectively 1,2,3,4,5.House type comprises single room, standard double room, double large bed room, executive suite.Whether whether whether traffic is convenient comprises " apart from 200 meters of subway stations ", " apart from bus station 200 meters in ", " other situation " three classes.That sanitary condition comprises is poor, general, relatively good, unusual four grades, and internal number corresponds to respectively 1,2,3,4." whether be positioned at certain appointed place annex " and be used for weighing the distance of hotel apart from certain appointed place, be divided into " in 500 meters of air line distances ", " in 1 kilometer ", " in 2 kilometers ", " in 5 kilometers " and " more than 5 kilometers " five grades, internal number corresponds to respectively 1,2,3,4,5." whether allow freely to cancel order " and refer to user recalls an order whether there is no service charge.Client's comment situation is divided into 1,2,3,4,5 five grade, and numeral is higher, and customer satisfaction is higher.
Obviously, it is apparent to those skilled in the art that different net purchase commodity may have different characteristics, for different net purchase commodity, the system of net purchase intermediary and conceptual design personnel need to, according to product characteristics, determine item property.
Embodiment 4
Net purchase user's personalization preferences, comprise following at least one: attribute bias, matching degree algorithm parameter.Different user, for same class commodity, has different preferences.For example, for hotel's commodity, some user may be ready that 3 star hotels, some user may be ready 5 star hotels.Attribute bias is used for describing the preference of net purchase user for net purchase item property.
Fig. 6, take net purchase commodity hotel as example, has shown a net purchase user's who often goes on business throughout the country attribute bias example.Net purchase user is to moving in city without certain preference.Net purchase user is that star is more high better for the preference of hotel's star.Net purchase user is 300 yuan to 400 yuans every night for the preference of price.Net purchase user is single room for the preference of house type.Net purchase user is for moving in the date without certain preference.Net purchase user is 2 to 3 days for the preference of moving in number of days.Net purchase user takes notice of " whether breakfast is provided " very much.Net purchase user for traffic whether easily preference be to take notice of very much, and think from close to subway station than better close to bus station.Net purchase user is without preference, so but " no certain appointed place annex that is positioned at " this characteristic is taken notice of very much for appointed place for the preference that whether is positioned at certain appointed place annex.Whether net purchase user is for allowing freely to cancel the order and pay no attention to.Net purchase user pays no attention to for client's comment situation.
Embodiment 5
Fig. 7 shows goods for purchase necessary condition and the goods for purchase optimum condition of the net purchase hotel commodity of the querying condition generation in attribute bias and the first merchandise query request of net purchase intermediary based on net purchase user for example, comprises five necessary conditions and five optimum conditions.Five essential conditions are respectively: to move in city be Shanghai, move in November 5 2012 date, move in number of days be two days, can not be lower than 4 stars, can surf the Net.Five optimum conditions be respectively 300 to 400 yuans every night of prices, hotel provide breakfast, periphery convenient traffic and also " close to subway station " better than " close to bus station ", hotel's sanitary condition is good, closer from the tycoon Advisory Co., Ltd of Pudong New Area, Shanghai.
Embodiment 6
Fig. 8 enumerates and calculates net purchase user's attributes match degree and the formula of goods matching degree.In the time that calculating goods matching is spent, net purchase intermediary may need first computation attribute matching degree.Attributes match degree is used for the degree that metric attribute meets net purchase user expection and requires.
The matching degree f of hotel's star
1the in-line coding of=5-hotel star;
Whether be positioned at the matching degree f of certain appointed place annex
5=with internal number-1 of appointed place distance;
The matching degree f of sanitary condition
6the internal number of=4-hotel sanitary condition;
Goods matching degree is used for measuring the degree that candidate's commodity meet net purchase user expection and require.Hotel's commodity
The step of calculating goods matching degree is first to check whether all goods for purchase necessary conditions are all satisfied, if find to exist certain necessary condition not to be satisfied, goods matching degree is 0, represents not meet user's necessary condition requirement.Otherwise, determine and calculate whole attributes that goods matching need to relate to while spending, in the present embodiment, for hotel's star, hotel's price, whether breakfast, periphery convenient traffic are provided, whether are positioned at certain appointed place annex, sanitary condition, house type.Then distinguish the attributes match degree of computation attribute i, and then according to goods matching degree computing formula
calculate goods matching degree.
In the present embodiment, the value of attributes match degree is less, represents that attributes match degree is higher, and attributes match value is larger, represents that attributes match degree is lower.The value of goods matching degree is less, represents that goods matching degree is lower, and goods matching value is larger, represents that goods matching degree is larger.
Obviously, it is apparent to those skilled in the art that different net purchase commodity, may use different goods matching degree algorithms.Even for same item property, because net purchase user property preference may be different, different net purchase users also may use different attributes match degree computing method, or different net purchase users uses identical attributes match degree computing method, the parameter value difference still using.
Embodiment 7
The schematic flow sheet of Figure 10 display update the first merchandise query request.The querying condition that intermediary of network 102 is received in 2001 steps is more rough, cannot generate the goods for purchase necessary condition and the goods for purchase optimum condition that accurately meet net purchase user 101 true intention.Intermediary of network 102, in 2003 steps, sends the first merchandise query and revises inquiry, and request net purchase user 101 provides the querying condition of refinement.In 2004 steps, net purchase user 101 manual intervention (for example in html web page input message or utilize drop-down single choice the mode such as to select), revise querying condition, and indication is revised in the first merchandise query request that generates.For example, only comprise and move in city, move in two conditions of number of days in first querying condition of net purchase user 201, intermediary of network 102 requires net purchase users 101 to move in area information in 2003 steps.Net purchase user 101 manual inputs " tycoon Advisory Co., Ltd ".In 2005 steps, intermediary of network 102 receives the first merchandise query request and revises indication, and revises goods for purchase necessary condition and goods for purchase optimum condition.
The schematic flow sheet of Figure 11 display update the second merchandise query request.3001 to 3004 steps and 1001 to 1004 similar, in 3004 steps, intermediary of network 102 finds not meet candidate's commodity of querying condition.In 3005 steps, intermediary of network 102 sends the first merchandise query and revises inquiry, and request net purchase user 101 provides the querying condition of modification.In 3006 steps, net purchase user 101 manual intervention (for example in html web page input message or utilize drop-down single choice the mode such as to select), revise querying condition, indication is revised in the first merchandise query request that generates, and in 3007 steps, the first merchandise query request modification indication is sent to intermediary of network 102.Intermediary of network 102, in 3008 steps, is revised goods for purchase necessary condition and goods for purchase optimum condition, and is revised the second merchandise query request.Then in 3009 steps, the second merchandise query request of revising is sent to net purchase businessman 103.
Embodiment 8
Figure 12 shows reception and the treatment scheme schematic diagram of net purchase user personalized information.In 4001 steps, net purchase intermediary 102 receives net purchase user 101, or net purchase businessman 103, or the net purchase user's 101 that sends of social network sites 105 customized information, in 4002 steps, and the customized information that net purchase intermediary 102 Storage and Processings receive.Net purchase user's customized information, comprise following at least one: net purchase user basic document information, payment information, Postpass Message, sequence information, net purchase contextual information, net purchase user's network browsing information, social network information.
Figure 13 shows recommended flowsheet schematic diagram.In 5001 steps, net purchase user 101 logging in network intermediaries 102.In 5002 steps, intermediary of network 102 according to net purchase user 101 personalization preferences and or net purchase contextual information generate commercial product recommending information, wherein net purchase user 101 personalization preferences, comprise following at least one: attribute bias, matching degree algorithm parameter.In 5003 steps, net purchase intermediary 102 sends commercial product recommending information by http protocol to net purchase user 101.For example, net purchase intermediary 102 finds that after one week, net purchase user 101 is about to celebrate a birthday, and net purchase user 101 once bought the cake of celebrating a birthday recently, net purchase intermediary 102 may send commercial product recommending information to net purchase user 101, recommends near dining room fresh flower or net purchase user residence.
Embodiment 9
Figure 14 shows process of feedback schematic diagram.In 6001 steps, net purchase intermediary 102 receives the net purchase feedback that net purchase user 101 sends.Net purchase feedback may comprise net purchase and be satisfied with satisfaction scoring, also may comprise recommendation on improvement.Net purchase satisfaction scoring may comprise multiple grades, as very disappointed, disappointed, gather together, feel quite pleased, excellent five grades.Recommendation on improvement provides concrete suggestion, as selected 3 star hotels, should select to provide breakfast hotel, should select the hotel of convenient traffic etc.Net purchase intermediary 102 upgrades net purchase user 101 personalization preferences according to net purchase user 101 feedback, comprise attribute bias and goods matching degree algorithm parameter (for example attribute weight).For example, if net purchase user 101 feedbacks are liked 5 star hotels, net purchase intermediary 102 net purchase user 101 hotel star preferences are set to 5 stars; If it is very responsive that net purchase user 101 feeds back hotel's price, net purchase intermediary 102 can, according to net purchase user 101 feedback, raise 10% by hotel's price attribute weight adjustment.
Figure 15 shows the schematic flow sheet that utilizes net purchase contextual information to generate net purchase querying condition.In 7001 steps, intermediary of network 102 receives the first merchandise query request.In 7002 steps, intermediary of network 102 sends net purchase context information request, and in 7003 steps, net purchase intermediary receives net purchase contextual information.In 7004 steps, the personalization preferences based on net purchase user 101 and net purchase contextual information, intermediary of network 102 generates the goods for purchase necessary condition and the goods for purchase necessary condition that meet net purchase user 101 demands, and the second merchandise query request.
Embodiment 10
Figure 16 shows the configuration diagram of net purchase intermediary 102, comprises net purchase user interactive module 201, net purchase businessman interactive module 202, personalization preferences administration module 203, merchandise query request processing module 204, matching degree algoritic module 205.Net purchase user interactive module 201, for by http protocol receives net purchase user the first merchandise query request and or the first merchandise query request revise indicate, send the first merchandise query response by http protocol to net purchase user, receive by http protocol the net purchase feedback that net purchase user sends, wherein in the first merchandise query request, carry merchandise query condition, candidate's merchandise news is carried in the first merchandise query response; Net purchase businessman interactive module 202, for sending the second merchandise query request by http protocol to net purchase businessman, receive by http protocol the second merchandise query response that net purchase businessman sends, wherein merchandise query condition is carried in the second merchandise query request, and candidate's merchandise news is carried in the second merchandise query response; Personalization preferences administration module 203, for create and or upgrade net purchase user's personalization preferences, personalization preferences comprise following at least one: attribute bias, matching degree algorithm parameter; Merchandise query request processing module 204 for generate and or revise goods for purchase necessary condition and goods for purchase optimum condition, generate and or revise the second merchandise query; Matching degree algoritic module 205, for goods matching degree and or the attributes match degree of calculated candidate commodity.
Net purchase user interactive module 201 and or net purchase businessman interactive module 202 receive net purchase user's customized information by http protocol, comprise following at least one: net purchase user basic document information, payment information, Postpass Message, sequence information, net purchase contextual information, net purchase user's network browsing information, social network information.
Net purchase contextual information comprise following at least one: terminal device information, geographic position, time, network environment information, weather conditions, querying triggering background.
Merchandise query request processing module 204 is according to net purchase contextual information, generate and or revise goods for purchase necessary condition and goods for purchase optimum condition; Personalization preferences administration module 203, according to net purchase contextual information, upgrades net purchase user's personalization preferences.
Embodiment 11
The configuration diagram of the net purchase intermediary 102 that Figure 17 Presentation Function strengthens, except comprising the net purchase user interactive module 201 shown in Figure 16, net purchase businessman interactive module 202, personalization preferences administration module 203, merchandise query request processing module 204, matching degree algoritic module 205, also comprise recommending module 206, customer satisfaction tracking module 207.Recommending module 206 for according to net purchase user's personalization preferences and or net purchase contextual information generate commercial product recommending information; Customer satisfaction tracking module 207, for measuring the satisfaction of described net purchase user for shopping intermediary.Net purchase intermediary can measure net purchase user to its satisfaction according to the statistical information (as access times, frequency etc.) of net purchase user's net purchase feedback information, use system.
Obviously, those skilled in the art should be understood that, above-mentioned of the present invention each module or each step can realize with general calculation element, they can concentrate on single calculation element, or be distributed on the network that multiple calculation elements form, alternatively, they can be realized with the executable program code of calculation element, thereby, they can be stored in memory storage and be carried out by calculation element, and in some cases, can carry out shown or described step with the order being different from herein, or they are made into respectively to each integrated circuit modules, or the multiple modules in them or step are made into single integrated circuit module to be realized.Like this, the present invention is not restricted to any specific hardware and software combination.
The foregoing is only preferred embodiment of the present invention, be not intended to limit protection scope of the present invention.For a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any modification of doing, be equal to replacement, improvement etc., all should be included in protection scope of the present invention.
Claims (12)
1. a method for shopping at network, is characterized in that, comprising:
Net purchase intermediary by HTML (Hypertext Markup Language) receive net purchase user send the first merchandise query request and or the first merchandise query request revise indication, in wherein said the first merchandise query request, carry merchandise query condition;
Described net purchase intermediary generate and or revise goods for purchase necessary condition and goods for purchase optimum condition;
Described net purchase intermediary generate and or the second merchandise query request of modification, merchandise query condition is carried in described the second merchandise query request;
Described net purchase intermediary sends the second merchandise query request by HTML (Hypertext Markup Language) to net purchase businessman;
Described net purchase intermediary receives by HTML (Hypertext Markup Language) the second merchandise query response that described net purchase businessman sends, and candidate's merchandise news is carried in described the second merchandise query response;
Described net purchase intermediary utilize matching degree algorithm calculate candidate's commodity in described the second merchandise query response goods matching degree and or attributes match degree, described goods matching degree is used for measuring the degree that candidate's commodity meet net purchase user expection and require, and described attributes match degree is used for the degree that metric attribute meets net purchase user expection and requires;
Described net purchase intermediary generates the first merchandise query response, and candidate's merchandise news is carried in described the first merchandise query response;
Described net purchase intermediary sends the first merchandise query response by HTML (Hypertext Markup Language) to described net purchase user;
Described net purchase intermediary receives by HTML (Hypertext Markup Language) the net purchase feedback that described net purchase user sends;
Described net purchase intermediary create and or upgrade described net purchase user's personalization preferences, described personalization preferences comprise following at least one: attribute bias, matching degree algorithm parameter.
2. the method for claim 1, is characterized in that,
Described net purchase intermediary receives described net purchase user's customized information by HTML (Hypertext Markup Language), comprise following at least one: net purchase user basic document information, payment information, Postpass Message, sequence information, net purchase contextual information, net purchase user's network browsing information, social network information.
3. method as claimed in claim 2, its feature with,
Described net purchase contextual information comprise following at least one: terminal device information, geographic position, time, network environment information, weather conditions, querying triggering background;
Described intermediary of network is according to described net purchase contextual information, generate and or revise described goods for purchase necessary condition and or described goods for purchase optimum condition;
Described intermediary of network, according to described net purchase contextual information, upgrades described net purchase user's personalization preferences.
4. method as claimed in claim 2, is characterized in that,
Preferably, described net purchase intermediary according to described net purchase user's described personalization preferences and or described net purchase contextual information generate commercial product recommending information, send described commercial product recommending information by HTML (Hypertext Markup Language) to described net purchase user.
5. method as claimed in claim 2, is characterized in that,
Preferably, described net purchase intermediary measures the satisfaction of described net purchase user for described shopping intermediary.
6. method as claimed in claim 2, is characterized in that,
Preferably, described net purchase intermediary receives by HTML (Hypertext Markup Language) the net purchase that described net purchase user sends and confirms indication, in order to confirm selected buy certain commodity and or Postpass Message, and or payment information;
Described net purchase intermediary sends the indication of net purchase result by HTML (Hypertext Markup Language) to described net purchase user, in order to represent to buy whether success.
7. a net purchase intermediary, is characterized in that, comprising:
Net purchase user interactive module, for by HTML (Hypertext Markup Language) receive described net purchase user the first merchandise query request and or the first merchandise query request revise indication, send the first merchandise query response by HTML (Hypertext Markup Language) to described net purchase user, receive by HTML (Hypertext Markup Language) the net purchase feedback that described net purchase user sends, in wherein said the first merchandise query request, carry merchandise query condition, candidate's merchandise news is carried in described the first merchandise query response;
Net purchase businessman interactive module, for sending the second merchandise query request by HTML (Hypertext Markup Language) to described net purchase businessman, receive by HTML (Hypertext Markup Language) the second merchandise query response that described net purchase businessman sends, merchandise query condition is carried in wherein said the second merchandise query request, and candidate's merchandise news is carried in described the second merchandise query response;
Personalization preferences administration module, for create and or upgrade described net purchase user's personalization preferences, described personalization preferences comprise following at least one: attribute bias, matching degree algorithm parameter;
Merchandise query request processing module for generate and or revise goods for purchase necessary condition and or goods for purchase optimum condition, generate and or the second merchandise query request of modification;
Matching degree algoritic module, for the goods matching degree of calculated candidate commodity and or attributes match degree, described goods matching degree is used for measuring the degree that candidate's commodity meet net purchase user expection and require, and described attributes match degree is used for the degree that metric attribute meets net purchase user expection and requires.
8. net purchase as claimed in claim 7 intermediary, its feature with,
Described net purchase user interactive module and or described net purchase businessman interactive module receive described net purchase user's customized information by HTML (Hypertext Markup Language), comprise following at least one: net purchase user basic document information, payment information, Postpass Message, sequence information, net purchase contextual information, net purchase user's network browsing information, social network information.
9. net purchase as claimed in claim 8 intermediary, is characterized in that,
Described net purchase contextual information comprise following at least one: terminal device information, geographic position, time, network environment information, weather conditions, querying triggering background;
Described merchandise query request processing module is according to described net purchase contextual information, generate and or revise goods for purchase necessary condition and or goods for purchase optimum condition;
Described personalization preferences administration module, according to described net purchase contextual information, upgrades described net purchase user's personalization preferences.
10. net purchase as claimed in claim 8 intermediary, is characterized in that,
Preferably, described intermediary of network also comprises recommending module, for according to described net purchase user's described personalization preferences and or described net purchase contextual information generate commercial product recommending information;
The described commercial product recommending information exchange that described net purchase businessman interactive module generates described recommending module is crossed HTML (Hypertext Markup Language) and is sent to described net purchase user.
11. net purchase as claimed in claim 8 intermediaries, is characterized in that,
Preferably, described intermediary of network also comprises customer satisfaction tracking module, for measuring the satisfaction of described net purchase user for the described intermediary that does shopping.
12. net purchase as claimed in claim 8 intermediaries, is characterized in that,
Preferably, described net purchase user interactive module receives by HTML (Hypertext Markup Language) the net purchase that described net purchase user sends and confirms indication, in order to confirm selected buy certain commodity and or Postpass Message, and or payment information;
Described net purchase intermediary sends the indication of net purchase result by HTML (Hypertext Markup Language) to described net purchase user, in order to represent to buy whether success.
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| CN201210453687.5A CN103810626A (en) | 2012-11-13 | 2012-11-13 | Method for online shopping and online shopping intermediary |
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| CN201210453687.5A CN103810626A (en) | 2012-11-13 | 2012-11-13 | Method for online shopping and online shopping intermediary |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104392357A (en) * | 2014-10-29 | 2015-03-04 | 广州康之家医药电子商务有限公司 | Shopping method based on O2O mode and system thereof |
| CN104731903A (en) * | 2015-03-23 | 2015-06-24 | 魏强 | Method for searching for enterprise on basis of products and search device |
| CN105160568A (en) * | 2015-08-28 | 2015-12-16 | 小米科技有限责任公司 | Reminding method and apparatus |
| CN106022497A (en) * | 2016-05-23 | 2016-10-12 | 北京依依科技有限公司 | House resource recommendation method and system and server |
| CN106204124A (en) * | 2016-07-02 | 2016-12-07 | 向莉妮 | Personalized commercial coupling commending system and method |
| CN106257452A (en) * | 2015-06-19 | 2016-12-28 | 联想（新加坡）私人有限公司 | Search Results is revised based on contextual feature |
| CN107851263A (en) * | 2015-07-16 | 2018-03-27 | B2云 | For handling the method and recommended engine of recommendation request |
| CN109858985A (en) * | 2017-11-30 | 2019-06-07 | 阿里巴巴集团控股有限公司 | Merchandise news processing, the method shown and device |
| CN110489645A (en) * | 2019-08-15 | 2019-11-22 | 深圳市云积分科技有限公司 | A kind of brand association consumer orients the information processing method and device of marketing |
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2012
- 2012-11-13 CN CN201210453687.5A patent/CN103810626A/en active Pending
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104392357A (en) * | 2014-10-29 | 2015-03-04 | 广州康之家医药电子商务有限公司 | Shopping method based on O2O mode and system thereof |
| CN104731903A (en) * | 2015-03-23 | 2015-06-24 | 魏强 | Method for searching for enterprise on basis of products and search device |
| CN106257452A (en) * | 2015-06-19 | 2016-12-28 | 联想（新加坡）私人有限公司 | Search Results is revised based on contextual feature |
| CN106257452B (en) * | 2015-06-19 | 2020-06-23 | 联想（新加坡）私人有限公司 | Modifying search results based on contextual characteristics |
| CN107851263A (en) * | 2015-07-16 | 2018-03-27 | B2云 | For handling the method and recommended engine of recommendation request |
| CN105160568A (en) * | 2015-08-28 | 2015-12-16 | 小米科技有限责任公司 | Reminding method and apparatus |
| CN106022497A (en) * | 2016-05-23 | 2016-10-12 | 北京依依科技有限公司 | House resource recommendation method and system and server |
| CN106204124A (en) * | 2016-07-02 | 2016-12-07 | 向莉妮 | Personalized commercial coupling commending system and method |
| CN109858985A (en) * | 2017-11-30 | 2019-06-07 | 阿里巴巴集团控股有限公司 | Merchandise news processing, the method shown and device |
| CN110489645A (en) * | 2019-08-15 | 2019-11-22 | 深圳市云积分科技有限公司 | A kind of brand association consumer orients the information processing method and device of marketing |
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