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A novel technique for inferring user search using feedback sessions

机译:一种使用反馈会话推断用户搜索的新颖技术

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Web search engines have become a resource pool to gain information. We submit queries to search engines to retrieve search results. These queries basically depict information needs of users. But there are situations in which these queries do not represent user's specific information needs as varied users have different needs with respect to same query. There are many search engines like Google, Yahoo, Amazon that retrieve search results for users based on their ranking algorithm. It should also be noted that while inferring user search goals, fulfillment of user's desire is very important. So a Novel Technique to Infer User Search Goal using Feedback Session is proposed. The basic step of Inferring user search goals is generation of feedback session through user click-through logs. Feedback session distinguishes between what user requires and what the user does not require. Keywords in the query will determine whether a document satisfies the user's needs. The initial search results will later be restructured based on users' needs and manually Average Precision would be used to examine the performance of users. The main objective of this technique is to improve information retrieval by generating feedback sessions and rank the results list based on user's domain of interest. These re ranked results will be categorization based which will be dependent on the keywords generated.
机译:Web搜索引擎已成为获取信息的资源池。我们向搜索引擎提交查询以检索搜索结果。这些查询基本上描述了用户的信息需求。但是在某些情况下,这些查询不能代表用户的特定信息需求,因为不同的用户对于同一查询有不同的需求。有许多搜索引擎,例如Google,Yahoo,Amazon,它们根据用户的排名算法为他们检索搜索结果。还应注意,在推断用户搜索目标的同时,满足用户需求非常重要。因此,提出了一种利用反馈会话来推断用户搜索目标的新技术。推断用户搜索目标的基本步骤是通过用户点击日志生成反馈会话。反馈会话区分用户需求和用户需求。查询中的关键字将确定文档是否满足用户的需求。最初的搜索结果将在以后根据用户需求进行重组,并且将使用手动平均精度来检查用户的效果。该技术的主要目标是通过生成反馈会话并根据用户的关注域对结果列表进行排序来改善信息检索。这些重新排序的结果将基于分类,这将取决于生成的关键字。

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