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首页> 外文期刊>IAENG Internaitonal journal of computer science >Time Dependent Approach for Query and URL Recommendations Using Search Engine Query Logs
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Time Dependent Approach for Query and URL Recommendations Using Search Engine Query Logs

机译：使用搜索引擎查询日志的时间和方法的查询和URL推荐

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摘要

Search engine retrieves the significant and essential information from the web, based on the query keyword given by the user. Query log file is a repository contains every query request and its navigation in the search engine and maintained either in the system desktop or in the proxy server. This paper has proposed an algorithm for query and URL recommendation which is based on the user's search histories and a click through data. A new framework is constructed here based on the navigation time. First, the proposed algorithm identifies frequently accessed Queries and URLs from the log file using the frequent pattern generation algorithms. Next hub and authority weights are calculated for the frequent items. The similar queries are clustered; it uses the temporal characteristics of historical click-through data. The intuition is to reveal that more accurate semantic similarity of queries can be obtained by considering the timestamps of the log data. The cluster generated in this approach is used to provide query and URL recommendations to the user. Finally the method has been evaluated using real data set from the search engine query log.
机译：搜索引擎根据用户给出的查询关键字从网络中检索重要的重要信息。查询日志文件是一个存储库，包含每个查询请求及其在搜索引擎中的导航，并在系统桌面或代理服务器中维护。本文提出了一种基于用户的搜索历史和点击数据的查询和URL推荐算法。在此基于导航时间构造了一个新框架。首先，所提出的算法使用频繁模式生成算法从日志文件中识别频繁访问的查询和URL。为频繁项目计算下一个中心和权限权重。相似的查询被聚类；它使用历史点击数据的时间特征。直觉是通过考虑日志数据的时间戳可以获取更准确的查询语义相似性。用这种方法生成的集群用于向用户提供查询和URL建议。最终，使用来自搜索引擎查询日志的真实数据集对方法进行了评估。

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