Entity Query Feature Expansion using Knowledge Base Links

被引:140
作者
Dalton, Jeffrey [1 ]
Dietz, Laura [1 ]
Allan, James [1 ]
机构
[1] Univ Massachusetts, Sch Comp Sci, Ctr Intelligent Informat Retrieval, Amherst, MA 01003 USA
来源
SIGIR'14: PROCEEDINGS OF THE 37TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL | 2014年
关键词
Entities; Ontologies; Information Retrieval; Information Extraction;
D O I
10.1145/2600428.2609628
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recent advances in automatic entity linking and knowledge base construction have resulted in entity annotations for document and query collections. For example, annotations of entities from large general purpose knowledge bases, such as Freebase and the Google Knowledge Graph. Understanding how to leverage these entity annotations of text to improve ad hoc document retrieval is an open research area. Query expansion is a commonly used technique to improve retrieval effectiveness. Most previous query expansion approaches focus on text, mainly using unigram concepts. In this paper, we propose a new technique, called entity query feature expansion (EQFE) which enriches the query with features from entities and their links to knowledge bases, including structured attributes and text. We experiment using both explicit query entity annotations and latent entities. We evaluate our technique on TREC text collections automatically annotated with knowledge base entity links, including the Google Freebase Annotations (FACC1) data. We find that entity-based feature expansion results in significant improvements in retrieval effectiveness over state-of-the-art text expansion approaches.
引用
收藏
页码:365 / 374
页数:10
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