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公开(公告)号：US20150142827A1
公开(公告)日：2015-05-21
申请号：US14606971
申请日：2015-01-27
Applicant: eBay Inc.
Inventor： Mohammad Al Hasan , Nishith Parikh , Gyanit Singh , Neelakantan Sundaresan , Brian Scott Johnson , Udayan Khurana
IPC: G06F17/30
CPC classification number: G06Q30/0625 , G06F17/30386 , G06F17/3053 , G06F17/3064 , G06F17/30646 , G06F17/30861 , G06Q30/02
Abstract: Query suggestions are provided using a query log including a number of user sessions that comprise training data. The training data includes a sequence of a plurality of sets of queries, some of the sets of queries including query transitions followed by a purchase related event. From a cleaned and normalized query log stationary scores and transition scores of at least some of the plurality of sets are generated. A set of query suggestions is built and similarity scores are computed for at least some of the set of query suggestions to determine whether individual ones of the at least some of the set of query suggestions meet a predetermined assurance level. Those that meet the assurance level are included as elements of the set of query suggestions. The set of query suggestions is mixed and ranked according to a user behavior that is sought to be influenced.
Abstract translation: 使用查询日志提供查询建议，包括包含训练数据的多个用户会话。 所述训练数据包括多组查询的序列，所述查询集合中的一些包括跟随购买相关事件的查询转换。 从清洁和归一化的查询日志中，生成多个集合中的至少一些的静态分数和转换分数。 构建一组查询建议，并且针对所述一组查询建议中的至少一些计算相似性分数，以确定所述一组查询建议中的至少一些是否满足预定保证级别。 满足保证级别的那些将作为查询建议集的元素。 一组查询建议根据受到影响的用户行为进行混合和排序。
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公开(公告)号：US09858608B2
公开(公告)日：2018-01-02
申请号：US15086921
申请日：2016-03-31
Applicant: eBay Inc.
Inventor： Mohammad Al Hasan , Nishith Parikh , Gyanit Singh , Neelakantan Sundaresan , Brian Scott Johnson , Udayan Khurana
CPC classification number: G06Q30/0625 , G06F17/30386 , G06F17/3053 , G06F17/3064 , G06F17/30646 , G06F17/30861 , G06Q30/02
Abstract: Query suggestions are provided using a query log including a number of user sessions that comprise training data. The training data includes a sequence of a plurality of sets of queries, some of the sets of queries including query transitions followed by a purchase related event. From a cleaned and normalized query log stationary scores and transition scores of at least some of the plurality of sets are generated. A set of query suggestions is built and similarity scores are computed for at least some of the set of query suggestions to determine whether individual ones of the at least some of the set of query suggestions meet a predetermined assurance level. Those that meet the assurance level are included as elements of the set of query suggestions. The set of query suggestions is mixed and ranked according to a user behavior that is sought to be influenced.
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公开(公告)号：US20160217521A1
公开(公告)日：2016-07-28
申请号：US15086921
申请日：2016-03-31
Applicant: eBay Inc.
Inventor： Mohammad Al Hasan , Nishith Parikh , Gyanit Singh , Neelakantan Sundaresan , Brian Scott Johnson , Udayan Khurana
CPC classification number: G06Q30/0625 , G06F17/30386 , G06F17/3053 , G06F17/3064 , G06F17/30646 , G06F17/30861 , G06Q30/02
Abstract: Query suggestions are provided using a query log including a number of user sessions that comprise training data. The training data includes a sequence of a plurality of sets of queries, some of the sets of queries including query transitions followed by a purchase related event. From a cleaned and normalized query log stationary scores and transition scores of at least some of the plurality of sets are generated. A set of query suggestions is built and similarity scores are computed for at least some of the set of query suggestions to determine whether individual ones of the at least some of the set of query suggestions meet a predetermined assurance level. Those that meet the assurance level are included as elements of the set of query suggestions. The set of query suggestions is mixed and ranked according to a user behavior that is sought to be influenced.
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公开(公告)号：US09323811B2
公开(公告)日：2016-04-26
申请号：US14606971
申请日：2015-01-27
Applicant: eBay Inc.
Inventor： Mohammad Al Hasan , Nishith Parikh , Gyanit Singh , Neelakantan Sundaresan , Brian Scott Johnson , Udayan Khurana
CPC classification number: G06Q30/0625 , G06F17/30386 , G06F17/3053 , G06F17/3064 , G06F17/30646 , G06F17/30861 , G06Q30/02
Abstract: Query suggestions are provided using a query log including a number of user sessions that comprise training data. The training data includes a sequence of a plurality of sets of queries, some of the sets of queries including query transitions followed by a purchase related event. From a cleaned and normalized query log stationary scores and transition scores of at least some of the plurality of sets are generated. A set of query suggestions is built and similarity scores are computed for at least some of the set of query suggestions to determine whether individual ones of the at least some of the set of query suggestions meet a predetermined assurance level. Those that meet the assurance level are included as elements of the set of query suggestions. The set of query suggestions is mixed and ranked according to a user behavior that is sought to be influenced.
Abstract translation: 使用查询日志提供查询建议，包括包含训练数据的多个用户会话。 所述训练数据包括多组查询的序列，所述查询集合中的一些包括跟随购买相关事件的查询转换。 从清洁和归一化的查询日志中，生成多个集合中的至少一些的静态分数和转换分数。 构建一组查询建议，并且针对所述一组查询建议中的至少一些计算相似性分数，以确定所述一组查询建议中的至少一些是否满足预定保证级别。 满足保证级别的那些将作为查询建议集的元素。 一组查询建议根据受到影响的用户行为进行混合和排序。
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