An adaptive search system using heterogeneous document vector spaces
An adaptive search system using heterogeneous document vector spaces
复制标题
DOI：
10.1109/pacrim.2009.5291375
复制
发表时间：
2009-10
期刊：
影响因子：
--
通讯作者：
Kosuke Takano;Xing Chen;Shuichi Kurabayashi;Y. Kiyoki
中科院分区：
文献类型：
--
作者：
Kosuke Takano;Xing Chen;Shuichi Kurabayashi;Y. Kiyoki
传统的数据库选择算法通过删除与查询无关的数据库，有助于改善搜索结果，减少网络开销和计算时间。然而，他们没有被设计为适应不断变化的兴趣和意图的用户在文件检索过程中。在本文中，我们提出了一个自适应搜索系统使用异构文档向量空间。我们的系统提供了一个基于向量空间模型的搜索引擎组件的动态构建功能。为了反映用户的当前工作环境中的组件的搜索引擎，我们的系统选择自适应预定义的集的特征项与不同的搜索域取决于用户的当前查看的文档。通过利用这种具有特定域的自适应和异构文档向量空间，我们的系统允许用户检索与其当前工作上下文相匹配的正确文档。此外，我们的系统实现了一个传统的数据库选择方法，以减少在每个文档向量空间的相似性计算的计算时间。在这项研究中，我们证实，我们的自适应搜索系统可以提高搜索结果的准确率以及计算时间的可扩展性，通过几个实验使用的实验检索系统在桌面环境中实现。
Conventional database selection algorithms are very helpful in improving search results and reducing network overhead and computation time by cutting off databases that are irrelevant to the queries. However, they have not been designed to adapt to the changing interest and intentions of users in the document retrieval process. In this paper, we propose an adaptive search system using heterogeneous document vector spaces. Our system provides a dynamic construction function of search engine components based on a vector space model. In order to reflect the user's current working contexts in the components of the search engine, our system selects adaptively pre-defined sets of feature terms with different search domains depending on the user's currently-viewed documents. By exploiting such adaptive and heterogeneous document vector spaces with specific domains, our system allows users to retrieve proper documents that match their current working contexts. Also, our system implements a conventional database selection method to reduce the computation time of the similarity calculations in each document vector space. In this study, we confirm that our adaptive search system can improve the precision rates of search results as well as the scalability of computation times, by several experiments using the experimental retrieval system implemented in the desktop environment.