Abstract
Information retrieval involves similarity estimation of the documents in a repository. It is the measure of the closeness of documents which can be in general measured as a similarity/distance score for the user entered query. This score is used to rank and retrieve the documents from the repository based on user need. Distance-based similarity algorithms are generally of the order O(n) rather than O(n\(^{2}\)). A similarity measure finds its usage not only in estimating similarity score for document retrieval but also clustering and classification. Researchers in the past have suggested numerous similarity measures. This paper presents a new and efficient Information retrieval algorithm using Bray–Curtis Distance-based information retrieval from OHSUMED. Detailed analysis shows that the Bray–Curtis Distance-based similarity measure used for Information retrieval outperforms the other prevailing similarity methods.
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Thakur, N., Mehrotra, D., Bansal, A., Bala, M. (2019). Analysis and Implementation of the Bray–Curtis Distance-Based Similarity Measure for Retrieving Information from the Medical Repository. In: Bhattacharyya, S., Hassanien, A., Gupta, D., Khanna, A., Pan, I. (eds) International Conference on Innovative Computing and Communications. Lecture Notes in Networks and Systems, vol 56. Springer, Singapore. https://doi.org/10.1007/978-981-13-2354-6_14
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DOI: https://doi.org/10.1007/978-981-13-2354-6_14
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