Markov Model Document Retrieval

Michael P. Perrone,Alessandro Vinciarelli

International Conference on Document Analysis and Recognition（2003）

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摘要

This paper presents a new probabilistic approachto document retrieval based on the assumption thata Markov process can explain the process by whichhumans rank the relevance of documents to queries.The model ranks documents for retrieval based on theirprobability of relevance. Two training methods are presented. The model is compared with Latent Semantic Analysis (LSA) on two publicly available databases.The results show that the new algorithm achieves Precision/Recall performance equivalent to or better than LSA.

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关键词

available databases,recall performance equivalent,new probabilistic approachto document,new algorithm,training method,Latent Semantic Analysis,assumption thata Markov process,Markov Model Document Retrieval

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