iMecho:一个上下文感知的桌面搜索系统

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI:10.1145/2009916.2010154

Jidong Chen, Hang Guo, Wentao Wu, Wei Wang

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引用次数: 4

摘要

在这个演示中，我们展示了iMecho，一个上下文感知的桌面搜索系统，可以帮助用户获得更多相关的结果。与其他桌面搜索引擎不同，iMecho不仅根据查询的内容对结果进行排名，还根据查询的上下文对结果进行排名。它采用基于隐马尔可夫模型(HMM)的用户模型，该模型从用户的活动日志中学习，在用户提交查询时估计查询上下文。关键字搜索的结果将根据它们与可接受开销的上下文的相关性重新排序。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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iMecho: a context-aware desktop search system

In this demo, we present iMecho, a context-aware desktop search system to help users get more relevant results. Different from other desktop search engines, iMecho ranks results not only by the content of the query, but also the context of the query. It employs an Hidden Markov Model (HMM)-based user model, which is learned from user's activity logs, to estimate the query context when he submits the query. The results from keyword search are re-ranked by their relevances to the context with acceptable overhead.

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Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval

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