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Incorporating users location into snippet based Query recommendation system

机译:将用户位置整合到基于片段的查询推荐系统中

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As the access of web has been increased greatly for information retrieval and it is difficult to extract the relevant information in less time. Sometime Search engine does not able to understand user search intend behind query. Thus Query recommendation can be used to help user to state exactly their information need. Search engine can return appropriate result to meet users' information needs. There are various methods based on history of users and snippets to retrieve the information. But these methods fail to satisfy users need. Therefore in addition of history and snippets with users location information will produce better results. Snippet based method with incorporating users preferences and location results the URLs for given query, also it ranks the clicked URLs at the top of the result based on user profile. The performance of the system shows that the snippet based with incorporating users location give better and effective recommendation for all types queries as compared to previous methods including low frequency queries.
机译:由于为了获取信息而大大增加了Web的访问,并且很难在较短的时间内提取相关信息。有时搜索引擎无法理解查询背后的用户搜索意图。因此,查询推荐可用于帮助用户准确说明他们的信息需求。搜索引擎可以返回适当的结果,以满足用户的信息需求。有多种基于用户和摘要的历史记录来检索信息的方法。但是这些方法不能满足用户的需求。因此,除了具有用户位置信息的历史记录和摘要外,还会产生更好的结果。基于代码段的方法结合了用户的首选项和位置,可以生成给定查询的URL,还可以根据用户个人资料将点击的URL排在结果的顶部。系统的性能表明,与先前的方法(包括低频查询)相比,基于合并用户位置的代码段可为所有类型的查询提供更好,更有效的推荐。

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