Combining automatic and manual index representations in probabilistic retrieval
Journal of the American Society for Information Science
Cluster-based language models for distributed retrieval
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Document language models, query models, and risk minimization for information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
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Information retrieval using meta data can be traced back to the early age of IR where documents are represented by the controlled vocabulary. In this paper, we explore the usage of meta-data information under the framework of language model. We present a new language model that is able to take advantage of the category information for documents to improve the retrieval accuracy. We compare the new language model with the traditional language model over the TREC4 dataset where the collection information for documents is obtained using the k-means clustering method. The new language model outperforms the traditional language model, which verifies our statement.