Information Retrieval and Text Mining

Abstract

Information retrieval is described as a predictive text-mining task. The methods for retrieval 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-based documents. These documents have richer representations with links among documents. Link analysis for ranking similarity of documents is reviewed. Some performance issues for computing similarity are considered including the specification of inverted lists for indexing documents.