A Trend Analysis of Information Retrieval Models
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Abstract
: Information retrieval technologies behind web search engines in the field of computer science were bought up in the year of 1950s. It is a process of retrieving the relevant documents based on the queries raised by the user. It deals with the representation, storage and access of information items. In this system, the generated outputs are ranked according to their relevance. The information retrieval (IR) uses data models that make a retrieval process easier when compared to the traditional IR database model. In this work, we analyse the most popular information retrieval models such as boolean, vector space, probabilistic and latent semantic analysis and evaluate the performance of the models by using the underlying parameters like concept, representation, word occurrence, information type, output, pros and cons of the models. This study aims to determine the appropriate model for different situations and additionally describes the indexing methods for decrementing search space and different probing (searching) techniques to retrieve the information.
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