Interactive Search Refinement Techniques for HARD Tasks
暂无分享,去创建一个
In our entry to the new HARD track, we have started by investigating two methods of interactively refining user search formulations. One method consists of asking the user to select a number of sentences that may represent relevant documents, and then using the documents, whose sentences were selected for query expansion. The second method is to show to the user a list of noun phrases, extracted from the initial document set, and then expanding the query with the terms from the phrases selected by the user. The results show that the second method is an effective means of interactive query expansion and yields significant performance improvements.
[1] Mitchell P. Marcus,et al. Text Chunking using Transformation-Based Learning , 1995, VLC@ACL.
[2] Kenneth Ward Church,et al. Using Statistics in Lexical Analysis , 2003, Lexical Acquisition: Exploiting On-Line Resources to Build a Lexicon.
[3] Eric Brill,et al. Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging , 1995, CL.
[4] Stephen E. Robertson,et al. Query Expansion with Long-Span Collocates , 2003, Information Retrieval.