Abstract

This study presents a survey of information retrieval and its various methodologies. In today’s escalating world, tracking of information should be done with ease. Keeping that as a constraint, most of the qualms can be deciphered with the aid of Machine Learning (ML). ML can be envisioned as a tool, which identifies and disseminates all information through computerized systems, which can be integrated in the respective domains, in order to get a better and more proficient retrieval of content. This study summarizes the well-known methods used in feature extraction and for classification of text. ML can be portrayed as a major tracker for surveillance, with the aid of some trained ML algorithms. In order to strengthen the response policies for any queries, which is being surrounded with two main issues like policy matching and policy administration, can be prevailed over Joint Threshold Administration Model, JTAM (i.e., Principle of separation of duty). This study gives an overall review about tracking of information with respective to semantic as well as syntactic perspective. It revolves around some of the application as well as administrative mechanism involved in Information Retrieval for mining the data. Data mining techniques in various arenas has been explored; this survey explores the various techniques and evolution of mining in detail.

Keywords:

Data mining feature extraction, information retrieval, machine learning, syntactic and semantic perspective,

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Competing interests

The authors have no competing interests.

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