Usage of Mined Word Associations for Text Retrieval
暂无分享,去创建一个
In this paper, we evaluated the efficacy of mined association rules between words for measuring the similarity between documents to enhance the text retrieval. In our experiments, for each document relevant to a query, we formed a group of documents having at least one common frequent set of words with the answer document. Then we measured the precision of the documents in the same group as an answer set to the corresponding query. This experiment was performed using a corpus of the Text retrieval conference (TREC) and search results. Our experimental results show that the frequent sets of words mined from our test database are useful in ranking query result sets to improve the precision of retrieval.
[1] Susan T. Dumais,et al. Using Latent Semantic Indexing for Literature Based Discovery , 1998, J. Am. Soc. Inf. Sci..
[2] Gerard Salton,et al. Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer , 1989 .
[3] Soon Myoung Chung,et al. Parallel mining of association rules from text databases , 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..
[4] Ramakrishnan Srikant,et al. Fast algorithms for mining association rules , 1998, VLDB 1998.