Abstract
Information retrieval is described in terms of predictive text mining. The methods can be considered variations of similarity-based nearest-neighbor methods. Both key word search and full document matching are examined. Different methods of measuring similarity are considered including cosine similarity. Classical information retrieval has evolved from retrieval of documents stored in databases to web or intranet based documents. These document have richer representations with links among documents. Link analysis for ranking similarity of documents is described. Some performance issues for computing similarity are considered including the specification of inverted lists for indexing documents.
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Weiss, S.M., Indurkhya, N., Zhang, T. (2010). Information Retrieval and Text Mining. In: Fundamentals of Predictive Text Mining. Texts in Computer Science. Springer, London. https://doi.org/10.1007/978-1-84996-226-1_4
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DOI: https://doi.org/10.1007/978-1-84996-226-1_4
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