发明名称 METHOD AND A SYSTEM FOR RECOMMENDING LIMITED CHOICES WHICH ARE PERSONALIZED AND RELEVANT TO A CUSTOMER
摘要 A method of recommending limited choices which are personalized and relevant to a customer in real-time, in which steps thereof are implemented by a computer, the method comprising: receiving data across different categories of products; configuring a taste graph based on the received data; calculating a net affinity between any two products in the taste graph and exporting them as taste scores to a taste table; understanding the customer based on context and behavior from different customer information sets; generating scores for the different customer information sets; determining different weightages for each score to calculate a net score associated with each product for the customer; and recommending limited choices which are personalized and relevant to the customer in real-time based on the descending order of the value of the net score associated with the product.
申请公布号 US2016148297(A1) 申请公布日期 2016.05.26
申请号 US201514613351 申请日期 2015.02.03
申请人 KASHYAP AJAY;SHANKAR SURESH VENUGOPALAN 发明人 KASHYAP AJAY;SHANKAR SURESH VENUGOPALAN
分类号 G06Q30/06;G06N5/04 主分类号 G06Q30/06
代理机构 代理人
主权项 1. A method for recommending limited, personalized and relevant choices to a customer in real-time, the method comprising: receiving data in relation to various categories of entities from various data sources; transforming the received data into structured data to determine affinities between pairs of entities; configuring a taste graph with entities as nodes and associated affinity between them as edges; calculating net affinity scores between all pairs of entities in the taste graph; exporting the net affinity scores as taste scores to a taste table; receiving customer input in form of context and behavior information sets; generating a plurality of scores for each entity based on the customer input information sets; determining weights for the plurality of scores and calculate a net score for each entity based on the plurality of scores of the entity; and recommending a list of entities as choices to customer based on descending order of values of the net scores.
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