计算机应用研究Issue(1)：101-103,121,4.DOI:10.3969/j.issn.1001-3695.2016.01.023
基于层次评分函数的多粒度搜索算法研究
Hierarchical scoring function based multi-granularity searching method
摘要
Abstract
Online forums contains much useful information,which makes it convenient for users to retrieve necessary know-ledge,however,the hierarchical structure of forum data poses great challenges to content retrieve.In order to solve this prob-lem,this paper proposed a hierarchical scoring function based multi-granularity searching method.Firstly,it represented the forum data with trees,and gave a scoring function including topics,posts,sentences and words based on several considera-tions.Secondly,in order to avoid the replication of data in results of multi-granularity,it proposed a maximization model of re-sults with constraints.Finally,it transformed the maximization model of results into the problem of maximal independent sets, and gave a heuristic optimal algorithm.The experiments show that,the proposed method is more efficient and accurate that re-lated works while retrieving forum data.关键词
论坛/信息检索/层次评分函数/多粒度搜索Key words
forum/information retrieval/hierarchical scoring function/multi-granularity searching分类
信息技术与安全科学引用本文复制引用
姜攀,李跃新..基于层次评分函数的多粒度搜索算法研究[J].计算机应用研究,2016,(1):101-103,121,4.基金项目
湖北省国际交流与合作项目（2012IHA0140）；湖北省教育厅科学技术研究计划指导性项目 （）
