O2o recommendation method based on customer flow
A recommendation method and customer technology, applied in the field of recommendation systems, can solve problems such as insufficient offline information, and achieve the effect of optimizing display and realizing user personalization.
Inactive Publication Date: 2018-01-09
HEFEI UNIV OF TECH
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Problems solved by technology
[0003] With the development of recommendation systems, although the problem of online information overload has been partially solved, offline information is still insufficient in the o2o scenario
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[0015] like figure 1 As shown, an o2o recommendation method based on customer flow, based on part of o2o offline customer flow information, extracts customer information and fuses traditional online information, and processes the fused data through the recommendation system to ensure user personalization in real time.
[0016] The offline part of customer information includes user ID, arrival time, travel route, browsed product ID, and purchase list.
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The invention discloses an o2o recommendation method based on a customer flow. The method extracts o2o offline customer flow information, fuses the customer flow information with traditional online information, processed the fused data by a recommendation system to ensure the user personalization in real time. The offline customer flow information includes a user ID, arrival time, a traveling route, viewed product IDs and a purchase list. The invention discloses the o2o recommendation method based on a customer flow. By fusing the offline acquired customer information with the traditional online information, a recommendation system can accurately achieve user personalization and optimizes the display and logistics of the offline commodities under a mobile Internet scenario.
Description
technical field [0001] The present invention relates to the technical field of recommendation systems, in particular to an o2o recommendation method based on customer flow, specifically an optimized recommendation algorithm based on information such as the travel route and stay time of customer flow in an o2o offline store, and provides member users with personalized Serve. Background technique [0002] The recommendation system is to use e-commerce to provide customers with product information and suggestions, help users decide which products to buy, and simulate a shopping guide to help customers complete the purchase process. The recommendation system is based on the user's interest characteristics and purchase behavior, recommending information and products that the user is interested in. [0003] With the development of recommendation systems, although the problem of online information overload has been partially solved, offline information is still insufficient in the...
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IPC IPC(8): G06Q30/02G06F17/30G06Q30/06
Inventor 刘征宇汤临春张建军毕翔吴家伟
Owner HEFEI UNIV OF TECH