CN103325047B - Net purchase guide device and method - Google Patents
Net purchase guide device and method Download PDFInfo
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- CN103325047B CN103325047B CN201210078517.3A CN201210078517A CN103325047B CN 103325047 B CN103325047 B CN 103325047B CN 201210078517 A CN201210078517 A CN 201210078517A CN 103325047 B CN103325047 B CN 103325047B
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Abstract
The invention discloses a kind of net purchase guide device and method, the device includes：One information acquisition module, for for each user collection multiple factors of influence related to the total volume of commodities for improving user purchase；One commercial product recommending module, for the part or all of factor of influence being respectively adopted for different commodity classifications in the plurality of factor of influence, and based on the relevance between adopted each factor of influence and the total volume of commodities for improving user purchase to user's Recommendations.The present invention neatly makes more accurately commercial product recommending using whole factors of influence in multiple factors of influence related to the total volumes of commodities of raising user purchase or some effects factor for different users and for different commodity classifications to user, therefore it is not only able to provide the user more commodity selections, additionally it is possible to simultaneously effective increase the sales volume of commodity.
Description
Technical field
The present invention relates to a kind of net purchase guide device, and the net is utilized more particularly to a kind of net purchase guide device and one kind
Purchase the net purchase bootstrap technique that guide device is realized.
Background technology
With the progress of computer and network technologies, people can easily utilize B2C (Business-to-
Customer, businessman is to customer) website buys extensive stock.And with net purchase this shopping means continuous popularization and
The continuous development of B2C websites is grown, and many B2C websites have been no longer satisfied with merely showing commodity so that they are clear to customer
Look at, search for or buy, but begin attempt to further carry out commercial product recommending to customer, to increase the sale number of commodity
Amount.
Current B2C websites are typically based on the self attributes of commodity to carry out commercial product recommending.So-called commodity from
Body attribute, generally comprise the price of commodity classification belonging to the commodity, the brand of the commodity, the weight of the commodity and the commodity
Etc..Such commercial product recommending mode is although simple and convenient, and preferably can provide more commodity selections for customer, but
It is the commodity purchasing quantity that but can not often increase customer.
For example, customer have purchased one bag of salt, now existing commercial product recommending system will be further different brands
Different Package specification salt show for customer select, even if but most customers see the business of various salt
Product are recommended, and but still only one bag of salt can be bought according to original plan when needing to buy salt thereafter.Therefore such commodity push away
Recommend the sales volume that mode is obviously difficult to increase commodity.
The content of the invention
Although the technical problem to be solved in the present invention be in order to overcome commercial product recommending mode of the prior art can be use
Family provides more commodity selections, but the defects of be difficult to increase the sales volume of commodity, there is provided one kind be not only able to for
Family provides more commodity selections, additionally it is possible to simultaneously effective increases the net purchase guide device and one kind of the sales volume of commodity
The net purchase bootstrap technique realized using the net purchase guide device.
The present invention is that solve above-mentioned technical problem by following technical proposals：A kind of net purchase guide device, its feature
It is, it includes：
One information acquisition module, for gathering related more of the total volume of commodities bought with improving the user for each user
Individual factor of influence；
One commercial product recommending module, for the part that is respectively adopted for different commodity classifications in the plurality of factor of influence or
Whole factors of influence, and based on the relevance between adopted each factor of influence and the total volume of commodities for improving user purchase
To user's Recommendations.
For different users, to improving the related factor of influence either species of the total volume of commodities that they buy also
It is that specific data content all can difference, therefore the operation for gathering factor of influence needs respectively to enter for different users
OK.
And for different commodity classifications, it is also difference that the factor of influence that uses is needed in Recommendations
, therefore the operation of Recommendations needs also exist for carrying out respectively for different commodity classifications.
Wherein, the factor of influence is selected from：The personal information of user, the self attributes of commodity, the purchase preference of user, user
The relating attribute browsed between preference, the searching preferences of user and commodity and commodity.
The personal information of user can include sex and age etc..The self attributes of commodity can include the commodity institute
The commodity classification of category, the brand of the commodity, price of the weight of the commodity and the commodity etc..It is the purchase preference of user, clear
Look at preference and searching preferences then can respectively the purchase history data from the user, browse historical data and search history number
Obtained according to middle excavated using existing data mining technology, wherein, so-called " preference " (both include " preference " above occurred,
Also " preference " for including hereinafter referring to) refer to the purchase history data of user, browse historical data and search for and go through
Commodity in history data consider it with certain weight proportion and buy number and frequency, number of visits and frequency and search time
The Taxonomy Information and commodity letter that the user that number and the post analysis of frequency obtain most is readily inclined to purchase, browses and searched for
Breath.And the relating attribute between commodity and commodity can then obtain from the common knowledge under the commodity classification belonging to commodity.
Wherein, for food materials classify, the factor of influence used for user personal information, the purchase preference of user, user
The relating attribute browsed between preference, the searching preferences of user and food materials and food materials.
When classifying for food materials not using the self attributes of food materials as factor of influence account for be because：Food materials from
Although body attribute is advantageous to provide a user more food materials selections, but be unprofitable to improve the food materials total amount of user's purchase.
It is preferred that classifying for food materials, the commercial product recommending module is inclined for the personal information based on user, the purchase of user
Good, user the relating attribute analysis browsed between preference, the searching preferences of user and food materials and food materials obtains the dish of user
Meat and fish dishes preference, and the food materials into user's recommendation menu and/or the menu related to the dish preference.
During analysis obtains the dish preference of user and recommends other food materials in menu and/or menu to user
Required menu data can be directly using the known menu data under food materials classification.
Present invention also offers a kind of net purchase bootstrap technique, its feature is, it is real using above-mentioned net purchase guide device
Existing, the net purchase bootstrap technique includes：
S1, the multiple factors of influence related to the total volume of commodities for improving user purchase are gathered for each user；
S2, the part or all of factor of influence being respectively adopted for different commodity classifications in the plurality of factor of influence, and
Based on the relevance between adopted each factor of influence and the total volume of commodities for improving user purchase to user's Recommendations.
It is preferred that the factor of influence is selected from：The personal information of user, the self attributes of commodity, the purchase preference of user, use
The relating attribute browsed between preference, the searching preferences of user and commodity and commodity at family.
It is preferred that classifying for food materials, the factor of influence used is the personal information of user, the purchase preference of user, use
The relating attribute browsed between preference, the searching preferences of user and food materials and food materials at family.
It is preferred that in S2, classify for food materials, the purchase preference of personal information, user based on user, user it is clear
The relating attribute analysis look between preference, the searching preferences of user and food materials and food materials obtains the dish preference of user, and to
User recommends the food materials in the menu and/or the menu related to the dish preference.
The positive effect of the present invention is：The present invention no longer merely using the self attributes of commodity as analysis foundation to
User's Recommendations, but for different users, for different commodity classifications neatly using multiple with improving the user
Whole factors of influence or some effects factor in the related factor of influence of the total volume of commodities of purchase are more smart to be made to user
Accurate commercial product recommending, such commercial product recommending are not only able to provide the user more commodity selections, additionally it is possible to simultaneously effective
Increase the sales volume of commodity.
Brief description of the drawings
Fig. 1 is the structural representation of the net purchase guide device of the present invention.
Fig. 2 is the flow chart of the net purchase bootstrap technique of the present invention.
Embodiment
Present pre-ferred embodiments are provided below in conjunction with the accompanying drawings, to describe technical scheme in detail.
As shown in figure 1, the net purchase guide device of the present invention mainly includes an information acquisition module 1 and a commercial product recommending
Module 2.
The information acquisition module 1 is used to gather related more of the total volume of commodities bought with improving the user for each user
Individual factor of influence, wherein each factor of influence is both selected from following factor of influence set：The personal information of user, commodity itself
Attribute, the purchase preference of user, browsing for user associate category between preference, the searching preferences of user and commodity and commodity
Property.
The commercial product recommending module 2 be used for for different commodity classifications be respectively adopted part in the plurality of factor of influence or
Whole factors of influence, and based on the relevance between adopted each factor of influence and the total volume of commodities for improving user purchase
To user's Recommendations.
Only the present invention will be described so that food materials are classified as an example below, and the fortune when present invention is directed to other commodity classifications
Line mode then may be referred to that method of operation during for food materials classification is similar to be obtained, therefore will not be described here.
The sales feature of commodity under classifying first to end article is analyzed, for food materials classification, food materials
Self attributes can not play substantial facilitation to the quantity purchase for improving user, but remaining factor of influence, i.e.,
The personal information of user, the purchase preference of user, user browse between preference, the searching preferences of user and food materials and food materials
Relating attribute then can more efficiently improve the quantity purchase of user, therefore carry out food materials only with these factors of influence
Recommendation.
Specifically, with reference to figure 2, now the operational process of the net purchase bootstrap technique when classifying for food materials of the invention be such as
Under：
Step 100, user's registration shopping website, and fill in personal information in registration.
Step 101, user buys, browses or searched for various food materials on the shopping website, so as in the shopping website
On leave its for food materials classification purchase history data, browse historical data and search history data.
Step 102, personal information of the background system of the shopping website based on user, the purchase preference of user, user
Browse the dish preference that the relating attribute analysis between preference, the searching preferences of user and food materials and food materials obtains user.Example
Such as, the sex of the user is women, and it buys, browses and searched for milk, sugar, meaning face, beefsteak and face in large quantities
The commodity such as powder, and can learn that the user is inclined with analysis based on the common knowledge under food materials classification and with reference to the sex of the user
Good dish is various western-style food and Western-style pastry.
Step 103, the dish preference for the user that the background system of the shopping website is obtained based on analysis, is pushed away to the user
Recommend the food materials in the menu related to the dish preference and/or the menu.For example, this still in consideration step 102 is for women
Family, it can now be shown with the dish preference for the female user on the webpage of the shopping website and belong to western-style food and Western-style pastry
Species and assorted menu and/or these dishes that the food materials degree of association having bought, browse or searched for user is higher
The assorted food materials needed to use in spectrum.
As can be seen from the above-described embodiment, the recommendation success rate of commercial product recommending mode of the invention is compared to existing commodity
Necessarily have more significant raising for the way of recommendation, such as the female user in the embodiment just has very big probability can be
Further it is bought under the inspiration of assorted food materials in assorted menu and/or menu that system is recommended in the shopping website
Required other food materials.
Although the foregoing describing the embodiment of the present invention, it will be appreciated by those of skill in the art that these
It is merely illustrative of, protection scope of the present invention is defined by the appended claims.Those skilled in the art is not carrying on the back
On the premise of principle and essence from the present invention, various changes or modifications can be made to these embodiments, but these are changed
Protection scope of the present invention is each fallen within modification.
Claims (4)
1. a kind of net purchase guide device, it is characterised in that it includes：
One information acquisition module, for for each user collection multiple shadows related to the total volume of commodities for improving user purchase
Ring the factor；
One commercial product recommending module, it is part or all of in the plurality of factor of influence for being respectively adopted for different commodity classifications
Factor of influence, and based on the relevance between adopted each factor of influence and the total volume of commodities for improving user purchase to
Family Recommendations；
Classify for food materials, the factor of influence used be the personal information of user, the purchase preference of user, user browse it is inclined
Relating attribute between the good, searching preferences of user and food materials and food materials, and the factor of influence excludes itself category of food materials
Property；
For food materials classify, the commercial product recommending module be used for the personal information based on user, the purchase preference of user, user it is clear
The relating attribute analysis look between preference, the searching preferences of user and food materials and food materials obtains the dish preference of user, and to
User recommends the food materials in the menu and/or the menu related to the dish preference.
2. net purchase guide device as claimed in claim 1, it is characterised in that the factor of influence is selected from：The personal information of user,
The self attributes of commodity, the purchase preference of user, user browse between preference, the searching preferences of user and commodity and commodity
Relating attribute.
3. a kind of net purchase bootstrap technique, it is characterised in that it is realized using net purchase guide device as claimed in claim 1, is somebody's turn to do
Net purchase bootstrap technique includes：
S1, for each user gather the related multiple factors of influence of the total volume of commodities bought with improving the user；
S2, the part or all of factor of influence that is respectively adopted for different commodity classifications in the plurality of factor of influence, and be based on quilt
Relevance between each factor of influence used and the total volume of commodities for improving user purchase is to user's Recommendations；
Classify for food materials, the factor of influence used be the personal information of user, the purchase preference of user, user browse it is inclined
Relating attribute between the good, searching preferences of user and food materials and food materials, and the factor of influence excludes itself category of food materials
Property；
In S2In, classify for food materials, the purchase preference of personal information, user based on user, user browse preference, user
Searching preferences and food materials and food materials between relating attribute analysis obtain user dish preference, and to user recommend and should
Food materials in dish preference related menu and/or the menu.
4. net purchase bootstrap technique as claimed in claim 3, it is characterised in that the factor of influence is selected from：The personal information of user,
The self attributes of commodity, the purchase preference of user, user browse between preference, the searching preferences of user and commodity and commodity
Relating attribute.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210078517.3A CN103325047B (en) | 2012-03-22 | 2012-03-22 | Net purchase guide device and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210078517.3A CN103325047B (en) | 2012-03-22 | 2012-03-22 | Net purchase guide device and method |
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| CN103325047A CN103325047A (en) | 2013-09-25 |
| CN103325047B true CN103325047B (en) | 2018-01-16 |
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| CN201210078517.3A Active CN103325047B (en) | 2012-03-22 | 2012-03-22 | Net purchase guide device and method |
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| CN104599160B (en) * | 2015-02-06 | 2020-09-08 | 腾讯科技（深圳）有限公司 | Commodity recommendation method and device |
| CN105046518A (en) * | 2015-06-29 | 2015-11-11 | 成都亿邻通科技有限公司 | Method of recommending group buying services |
| CN106469403B (en) * | 2015-08-14 | 2023-04-18 | 腾讯科技（深圳）有限公司 | Information display method and device |
| CN105678578A (en) * | 2016-01-05 | 2016-06-15 | 重庆邮电大学 | Method for measuring user brand preference on the basis of online shopping behavior data |
| CN105761111A (en) * | 2016-02-22 | 2016-07-13 | 青岛海尔股份有限公司 | Information processing method and information processing device based on dosage of ingredients |
| CN106157097A (en) * | 2016-08-22 | 2016-11-23 | 北京京东尚科信息技术有限公司 | Method of Commodity Recommendation and system |
| CN107886028A (en) * | 2016-09-29 | 2018-04-06 | 九阳股份有限公司 | The food materials input method and food materials input device of a kind of refrigerator |
| CN106651432A (en) * | 2016-10-31 | 2017-05-10 | 南京魔格信息科技有限公司 | Building advertisement accurate putting system and method |
| CN106600380B (en) * | 2016-12-28 | 2020-01-17 | 广州市供销社农产品经营有限公司 | Intelligent recommendation system and method based on catering O2O e-commerce platform |
| CN106910108A (en) * | 2017-01-24 | 2017-06-30 | 武汉奇米网络科技有限公司 | A kind of items list methods of exhibiting and system |
| CN107154109B (en) * | 2017-06-02 | 2019-10-22 | 深圳正品创想科技有限公司 | A kind of commodity rendering method, device and self-service cabinet |
| CN107247803A (en) * | 2017-06-30 | 2017-10-13 | 广东美的厨房电器制造有限公司 | Menu method for pushing and system based on cooking equipment |
| CN110210880A (en) * | 2018-02-28 | 2019-09-06 | 北京京东尚科信息技术有限公司 | Data processing method, device and computer readable storage medium |
| CN110519318B (en) * | 2018-05-22 | 2023-08-04 | 北京京东尚科信息技术有限公司 | Information pushing method and device |
| CN111429240A (en) * | 2020-06-15 | 2020-07-17 | 北京每日优鲜电子商务有限公司 | Commodity pushing method and system for fresh food sales platform, server and medium |
| CN112232916B (en) * | 2020-10-23 | 2023-04-07 | 杭州拼便宜网络科技有限公司 | Commodity recommendation method, device and equipment |
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