A Multiple-Stage Framework for Related Entity Finding: FDWIM at TREC 2010 Entity Track
Dong Wang, Qing Wu, Haiguang Chen, Junyu Niu · 2010
This paper describes a multiple-stage retrieval framework for the task of related entity finding on TREC 2010 Entity Track. In the document retrieval stage, search engine is used to improve the retrieval accuracy. In the entity extraction and filtering stage, we extract entity with NER tools, Wikipedia and text pattern recognition. Then stoplist and other rules are employed to filter entity. Deep mining of the authority pages is proved to be effective in this stage. In entity ranking stage, many factors including keywords from narrative, page rank, combined results of corpus-based association rules and search engine are considered. In the final stage, an improved feature-based algorithm is proposed for the entity homepage detection. 1