元搜索引擎中基于用户兴趣的查询结果合成研究

Personalized Results Merging Algorithm Based on User Profile for Meta Search Engine

元搜索引擎综合了多个搜索引擎的搜索结果,提高了搜索的覆盖率,但是它们返回的结果往往数目庞大,并且很多结果与用户查询并不相关,这直接影响了用户检索的质量,也大大提高了用户检索的代价。针对这一问题,文章提出了基于用户兴趣的结果合成算法。它根据用户兴趣对结果进行相似度计算和结果去重,从而为用户提供贴切的查询结果。实验表明,该算法提高了用户的检索效率和质量。

Meta search engines are proposed to increase the search coverage by combining several search engines. However, the problem of the information overload becomes more severe and most returned results are irrelevant to user＇s interests. That affects the retrieval quality and increases the user cost. For settling this problem, an algorithm of results merging based on user profiles is brought forward. It provides users with suitable results by removing the reduplicate results and estimating the similarity between results and user query. We build a system （PMSE）, researches and experiments are carried out on PMSE show the strategy can promotes the effectiveness and efficiency of retrieval.