CN103258022A - Local commerce service recommendation system and method based on user interest - Google Patents
Local commerce service recommendation system and method based on user interest Download PDFInfo
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Abstract
The invention discloses a local commerce service recommendation system and method based on user interest. The local commerce service recommendation method based on the user interest comprises the following steps of (1) carrying out statistics on user interest distribution contained in a plurality of pictures, carrying out sequencing according to frequency of appearance of interest information to obtain estimation of the user interest, and generating interest distribution, (2) obtaining location information of a user through a mobile device of a mobile client side, (3) carrying out service recommendation grading and grade sequencing according to the geographic information and the interest distribution of the user, wherein the geographic information and the user distribution of the user are obtained in the (1) and the (2), (4) recommending commerce information around the user to the user according to grades and the sequencing, and displaying the commerce information on the mobile client side. Compared with the prior art, the local commerce service recommendation system and method based on the user interest is more targeted, and smaller in amount of recommended information, and can be accepted by the user more easily, and thus the effect of the local commerce service recommendation system and method based on the user interest is better than that of traditional information recommendation. With development of a mobile internet and popularization of intelligent mobile phones, services based on mobility can be more and more popular, and the local commerce service recommendation system and method based on the user interest can be wide in application prospect.
Description
Technical field
The present invention relates to the Image mining technical field, the semantic content that particularly relates to a kind of CBIR technical field, image is understood field, LBS content recommendation method.
Background technology
Along with continuous development, the especially intelligent mobile terminal of mobile Internet and mobile netizen's quick growth, the mobile interconnected huge commercial value that contains displays just gradually.Each big internet enterprise such as Google, Microsoft, Tengxun, Baidu, Alibaba etc. fall over each other to seize the commanding elevation of mobile Internet, the various mobile interconnect services of constantly weeding out the old and bring forth the new.LBS(Location Based Services wherein), i.e. location-based service is subjected to the attention of each big internet enterprise just gradually.LBS is the positional information (as geographic coordinate) of obtaining mobile phone users by the radio telecommunication network of telecommunications mobile operator (as GSM net, CDMA net, WCDMA net, CDMA2000 net, TD-SCDMA net) or outside locator meams (as GPS, Big Dipper positioning system, GLONASS positioning system), at GIS (Geographic Information System, Geographic Information System) under the support of platform, provides a kind of value-added service of respective service for the user.In numerous LBS services, recommend its location business information on every side according to user position information, be common a kind of marketing model, typically use as Baidu's map.This trade marketing mode has obtained huge market success because relatively meeting particularly youthful use habit of its modern.Traditional local commerce services recommends to obtain earlier user's geography information (as GPS), and the interior commerce services information of certain distance (as two kilometers) is informed the user in the mode that pushes or the user initiatively selects on every side again.As being used for location-based service (LBS) system and method [1] of targeted ads, this invention utilizes GPS to obtain user position information, in conjunction with its ad system of setting up, the advertising message around the user is recommended the user.But this mode is just simply recommended the user with business information on every side, does not consider the user to the acceptance level of this recommendation, and therefore the effect of this simple recommendation service is unsatisfactory.For solving this defective, the present invention proposes a kind of local commerce services commending system based on user interest.
Previous invention documentation ﹠ info is with reference to as follows:
[1] is used for location-based service (LBS) system and method (Qualcomm Inc) patent No. of targeted ads: 200580036708.1
Summary of the invention
Based on problems of the prior art, the present invention proposes local commerce services commending system and the method based on user interest, carry out the recommendation score of commerce services in conjunction with user position information and user's interest distribution, carry out sequencing display according to the automatic scoring result, finish based on the local commerce services of user interest and recommend.
The present invention proposes a kind of local commerce services recommend method based on user interest, set up picture database in advance, the every pictures in the database all is provided with the markup information of its related interests of expression, and this method may further comprise the steps:
Step 1, in having the picture database of markup information, the picture that contains interest information that the user uploads in social network sites is retrieved, return the picture mark similar to this picture semantic as interest information, this interest information is input in the interest tree automatically, the estimation that the user interest that obtains that this pictures is comprised distributes, the picture that relevant this user uploads is handled successively, then result is added up, the frequency that occurs according to interest information sorts, obtain the estimation of user interest, and then generate the interest distribution;
Step 2, obtain user position information by the mobile device of mobile client;
Step 3, the user's that obtains according to above-mentioned steps one and step 2 geographic position and interest distribute, carry out service recommendation scoring and scoring ordering, when the user opens mobile client and connects network, client can send to server with user position information, and every setting-up time renewal customer location, the positional information of server meeting recording user obtains user's commerce services information of certain limit on every side; According to the size marking of commerce services and user distance, apart from the less mark that gives more far away; Interest distribution according to the user gives higher mark with the commerce services information relevant with user interest then, contact the lower lower mark that gives with user interest, the mark that gives for twice is merged as key word according to interest, and sort according to the height of score;
Step 4, recommend business information around the user according to scoring and ordering, show in mobile client.
The user's of described step 1 interest distributes and also obtains by following steps:
The approach that the another kind of step 1 obtains the interest distribution is: from user's the interest of extracting the user the record of browsing, with each grouping of social network sites or the public homepage point of interest as the user, calling and obtaining user is browsed the information of each grouping or interest sites within a certain period of time, it is done statistics by the number of times that occurs, and sort according to the frequency of browsing, draw the user based on the interest information of browsing, data that draw in conjunction with the picture by the user and browse the information that record counts, wherein identical or similar part is classified as same interest, and the interest that provides the user again distributes.
Take all factors into consideration in the scoring process of described step 3 user interest and with two factors of distance of user, and user's interest factor compared user's the bigger ratio of distance, the recommendation information that draws so more meets user's interest.
The present invention also proposes a kind of local commerce services commending system based on user interest, this system comprises server and mobile client, wherein server comprises positional information collection module, user's picture library, user interest statistical module and image data base, these two modules realize the scoring of service recommendation as the foundation of service recommendation grading module; Mobile client comprises the display module of transmission module on position information acquisition module, the user profile and service recommendation.
Described service recommendation grading module comprises following processing:
Geographic position and interest according to the above user who obtains distribute, carry out service recommendation scoring and scoring ordering, when the user opens mobile client and connects network, client can send to server with user position information, and every setting-up time renewal customer location, the positional information of server meeting recording user obtains user's commerce services information of certain limit on every side; According to the size marking of commerce services and user distance, apart from the less mark that gives more far away; Interest distribution according to the user gives higher mark with the commerce services information relevant with user interest then, contact the lower lower mark that gives with user interest, the mark that gives for twice is merged as key word according to interest, and sort according to the height of score;
Described user goes up transmission module also from user's the interest of extracting the user the record of browsing, with each grouping of social network sites or the public homepage point of interest as the user, calling and obtaining user is browsed the information of each grouping or interest sites within a certain period of time, it is done statistics by the number of times that occurs, and sort according to the frequency of browsing, drawing the user gives based on the interest information of browsing, data that draw in conjunction with the picture by the user and browse the information that record counts, wherein identical or similar part is classified as same interest, and the interest that provides the user again distributes.
Only compare to user's method the commerce services information recommendation near the certain limit user with tradition, the present invention is more targeted, and the quantity of information of recommending is fewer, the easier acceptance that obtains the user, so effect is better than traditional information recommendation.And along with the development of mobile Internet and popularizing of smart mobile phone, more and more universal based on mobile service meeting, the method that proposes among the present invention will great prospect.
Description of drawings
Fig. 1 is CBIR process flow diagram of the present invention;
Fig. 2 is the overall flow synoptic diagram of the user interest extracting method based on user's picture of the present invention;
The customer position information synoptic diagram that Fig. 3 obtains for the specific embodiment of the invention;
Fig. 4～Fig. 8 is the service recommendation display interface synoptic diagram of the specific embodiment of the invention;
Fig. 9 is the system architecture synoptic diagram based on the local commerce services commending system of user interest of the specific embodiment of the invention.
Embodiment
In the present invention, earlier according to the user in social network sites such as QQ space, little letter, the picture of uploading among everybody, user's the information such as record of browsing, its interest distributed carries out modeling, the interest that obtains every user distributes.When the user opened mobile client, client can ask to open outside locating device, if the user agrees to open outside locating device (as GPS), then obtained user's accurate position accordingly.Otherwise just according to the wireless network of telecommunications mobile operator, utilize locator meamss such as COO (Cell of Origin) location based on GSM net or CDMA net, Signaling System Number 7 location, TOA/TDOA location to obtain customer position information.In conjunction with GIS, the commerce services information around its location is recommended by its interest distribution afterwards.So just avoided the blindness of traditional local commerce services to recommend, reduced the quantity of the information of recommending, owing to be to recommend targetedly, its effect is apparently higher than traditional mode.
Below in conjunction with accompanying drawing, further describe specific implementation of the present invention.
The acquisition of step 1, user interest
The interest that picture by the user obtains the user distributes, and is as shown in table 1.We have set up the image data base that has interest information for this reason, and each opens the mark that image has its interest information of expression.User's picture as in picture retrieval method defeated, is returned the mark of the picture similar to this picture semantic, i.e. interest information.Accordingly, these interest are input in the interest tree automatically, the estimation that the user interest that obtains that this pictures is comprised distributes.User's picture is handled in this way successively, then the result is added up, sort according to the frequency that occurs, obtain the estimation of user interest.
It is the interest of extracting the user the record of browsing from the user that the another kind of step 1 obtains approach that interest distributes: namely adopt a kind of user interest modeling method based on web page browsing [2], with each grouping of social network sites or the public homepage point of interest as the user, calling and obtaining user is browsed the information of each grouping or interest sites within a certain period of time, it is done statistics by the number of times that occurs, and sort according to the frequency of browsing, draw the user based on the interest model of browsing.
Record the information that counts by the data that draw in conjunction with the picture by the user with browsing, wherein identical or similar part is classified as same interest, the interest that provides the user again distributes, and like this, has just obtained user's interest distributed model.
Step 2, obtain user position information according to user's mobile device
If the user has opened the outside locating device (as GPS) of mobile device, we just can directly obtain user's latitude and longitude coordinates.If the user does not open locating device, then can use the base station to locate to obtain user position information.If what the user used is the WiFi link, can select the WiFi location.In addition, for the more accurate user position information that obtains, we can combine above several locator meamss, to obtain the accurate position of user.Like this, no matter whether configuring condition and the outside locating device of user's mobile phone are opened, we can obtain customer position information accurately.
Step 3, the user's that obtains according to above-mentioned steps geographic position and interest distribute, and recommend the business information around the user
When the user opened mobile client and connects network, client can send to server with user position information, and upgrades customer location at regular intervals.Like this, even the user is constantly mobile, what system obtained also is the real-time positional information of user.Server is understood the positional information of recording user at this moment, obtains user's commerce services information of certain limit on every side.We are chosen to be two kilometers with default range, if scope is too big, even the information of recommending is very accurate, most user also can abandon because of distance cause too far away, and scope is too little, and the user can directly see just there has not been the necessity of recommending.Then with commerce services information according to the rearrangement that distributes of user's interest, in this process we take all factors into consideration user interest and with two factors of distance of user.And giving bigger ratio with user's interest factor, the recommendation information that draws so more meets user's interest.
The specific embodiment of the present invention specifies as follows by way of example:
At first user's picture is handled, compared with the picture database of setting up in advance that has interest information, find the picture similar to user's picture semantic, and then find the represented interest information of user's picture, and infer that accordingly user's interest distributes.The record of browsing according to user in the social network sites in addition is converted to distributing based on the interest of browsing record of user with user's the record of browsing, and both is combined in an interest that has just obtained the user distributes.When the user when opening mobile client, according to the outside locator meams (as GPS) that wireless network or the mobile terminal oneself of telecommunications mobile operator has, determine user's position.And the commerce services information in the certain limit is recommended to the user according to user's interest distribution around the handle.
User's interest distributes in this example, and statistics is as shown in table 1:
| User | football | basketball | equestrian | swim |
| Picture1 | 0.523682 | 0.40275 | 0.0376588 | 0.0359096 |
| Picture2 | 0.578768 | 0.373357 | 0.0239375 | 0.0239375 |
| Picture3 | 0.0881438 | 0.683998 | 0.131112 | 0.0967457 |
| Picture4 | 0.521602 | 0.412265 | 0.0330699 | 0.0330629 |
| Picture5 | 0.166538 | 0.485237 | 0.172311 | 0.175914 |
| Picture6 | 0.543263 | 0.320413 | 0.0787941 | 0.0575301 |
| Picture7 | 0.527209 | 0.401319 | 0.0365914 | 0.0348812 |
| Picture8 | 0.264819 | 0.291763 | 0.245765 | 0.197653 |
| Picture9 | 0.200436 | 0.172335 | 0.373014 | 0.254215 |
| Picture10 | 0.578332 | 0.356099 | 0.0327496 | 0.0328191 |
| Picture11 | 0.774434 | 0.163347 | 0.0311746 | 0.0310447 |
| Picture12 | 0.185782 | 0.165214 | 0.23813 | 0.23813 |
| sum | 4.9530088 | 4.228097 | 1.4343079 | 1.2118428 |
Table 1
Annotate: what the data in the table 1 showed is the number percent that distributes according to the user interest that a pictures is guessed
According to above statistics, the interest of User distributes and mainly to concentrate on football and the basketball, therefore, can obtain the User approval easilier about the business information of football and basketball.
Secondly, do directed commerce services information recommendation according to user's position and interest distribution, when the user opened mobile client, client location user's position sent to server with positional information then.At this moment, the positional information that server sends according to client, with the user near business information earlier according to the size marking from user distance, distance is more far away gives less mark.Interest distribution according to the user gives higher mark with the commerce services information relevant with user interest then, contacts the lower lower mark that gives with user interest.The mark that gives for twice is merged as key word according to interest, and sort according to the height of score.In client the scope selection function is arranged, the user can manually select the scope of needed information on services.If the user does not select, then with two kilometers configurations by default.We handle near two kilometers the business information user, and give the user with this information recommendation.
In addition, the present invention can arrange a user to the grading module of this ground commerce services, the user accepts to serve the back and by grading module the service level on this ground is done and once given a mark and comment on, and the below that user's marking and comment placed recommendation information, for the user when the selection as a reference.
Be example with picture shown in Figure 2, it is exactly football and basketball that the interest of user's picture distributes, so recommend to comprise some relevant information such as keyword football, basketball, stadium, gymnasium, physical culture, experience according to daily life, at first the information that retrieval is comprised keyword football and physical culture is found out, and then retrieval comprises the information of basketball and physical culture.And the height of retrieved message according to the score of interest sorted successively, recommend the user again.
Be illustrated in figure 3 as the user present position that obtains, at this moment, the user has opened the GPS location, and resulting user's position is accurate.
Operation interface shown in Fig. 4 to figure has shown the recommendation information to the user on this interface, below be after the user clicks " periphery is recommended " button, and system gives the page turning demonstration result of user's recommendation information according to ordering.
As shown in Figure 9, this system comprises server and mobile client, and wherein server comprises positional information collection module, user interest statistical module, and these two modules realize the scoring of service recommendation as service recommendation grading module institute foundation; Mobile client comprises the display module of transmission module on position information acquisition module, the user profile and service recommendation.
[2] Systems and Methods for Imaging a Volume-of-Interest(LANDMARK GRAPHICS CORP A HALLI[US]) the open day 2009-01-29 of document number US2009027385 publication number: US2009027385A1.
Claims (6)
1. the local commerce services recommend method based on user interest is set up picture database in advance, and the every pictures in the database all is provided with the markup information of its related interests of expression, it is characterized in that this method may further comprise the steps:
Step 1, in having the picture database of markup information, the picture that contains interest information that the user uploads at social network sites is retrieved, return the picture mark similar to this picture semantic content as interest information, this interest information is input in the interest tree automatically, the estimation that the user interest that obtains that this pictures is comprised distributes, the picture that relevant this user uploads is handled successively, then result is added up, the frequency that occurs according to interest information sorts, obtain the estimation of user interest, and then generate the interest distribution;
Step 2, obtain user position information by the mobile device of mobile client;
Step 3, the user's that obtains according to above-mentioned steps one and step 2 interest distributes and geographical location information, carry out the scoring and scoring ordering of service recommendation, when the user opens mobile client and connects network, client can send to server with user position information, and every setting-up time renewal customer location, the positional information of server meeting recording user, and pass through the Geographic Information System GIS acquisition user commerce services information of certain limit on every side; According to the size marking of commerce services and user distance, apart from the less mark that gives more far away; Interest distribution according to the user gives higher mark with the commerce services information relevant with user interest then, contact the lower lower mark that gives with user interest, the mark that gives for twice is merged as key word according to interest, and sort according to the height of score;
Step 4, recommend business information around the user according to scoring and ordering, show in mobile client.
2. the local commerce services recommend method based on user interest as claimed in claim 1 is characterized in that, the user's of described step 1 interest distributes and also obtains by following steps:
The approach that the another kind of step 1 obtains the interest distribution is: from user's the interest of extracting the user the record of browsing, with each grouping of social network sites or the public homepage point of interest as the user, calling and obtaining user is browsed the information of each grouping or interest sites within a certain period of time, it is done statistics by the number of times that occurs, and sort according to the frequency of browsing, draw the user based on the interest information of browsing, data that draw in conjunction with the picture by the user and browse the information that record counts, wherein identical or similar part is classified as same interest, and the interest that provides the user again distributes.
3. the local commerce services recommend method based on user interest as claimed in claim 1, it is characterized in that, take all factors into consideration in the scoring process of described step 3 user interest and with two factors of distance of user, and user's interest factor compared user's the bigger ratio of distance, the recommendation information that draws so more meets user's interest.
4. local commerce services commending system based on user interest, it is characterized in that, this system comprises server and mobile client, wherein server comprises positional information collection module, user's picture library, user interest statistical module and image data base, these two modules realize the scoring of service recommendation as the foundation of service recommendation grading module; Mobile client comprises the display module of transmission module on position information acquisition module, the user profile and service recommendation.
5. the local commerce services commending system based on user interest as claimed in claim 4 is characterized in that described service recommendation grading module comprises following processing:
Geographic position and interest according to above user distribute, carry out service recommendation scoring and scoring ordering, when the user opens mobile client and connects network, client can send to server with user position information, and every setting-up time renewal customer location, the positional information of server meeting recording user obtains user's commerce services information of certain limit on every side; According to the size marking of commerce services and user distance, apart from the less mark that gives more far away; Interest distribution according to the user gives higher mark with the commerce services information relevant with user interest then, contact the lower lower mark that gives with user interest, the mark that gives for twice is merged as key word according to interest, and sort according to the height of score.
6. the local commerce services commending system based on user interest as claimed in claim 4, it is characterized in that, described user goes up transmission module also from user's the interest of extracting the user the record of browsing, with each grouping of social network sites or the public homepage point of interest as the user, calling and obtaining user is browsed the information of each grouping or interest sites within a certain period of time, it is done statistics by the number of times that occurs, and sort according to the frequency of browsing, drawing the user gives based on the interest information of browsing, data that draw in conjunction with the picture by the user and browse the information that record counts, wherein identical or similar part is classified as same interest, and the interest that provides the user again distributes.
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