Semantic-Based Indexing Approaches for Medical Document Clustering Using Cognitive Search

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Author(s): Logeswari Shanmugam (Bannari Amman Institute of Technology, India)and Premalatha K. (Bannari Amman Institute of Technology, India)
Copyright: 2019
Pages: 24
Source title: Cognitive Social Mining Applications in Data Analytics and Forensics
Source Author(s)/Editor(s): Anandakumar Haldorai (Sri Eshwar College of Engineering, India)and Arulmurugan Ramu (Presidency University, India)
DOI: 10.4018/978-1-5225-7522-1.ch003

Keywords: Data Analysis & Statistics / Information Science Reference / Library & Information Science / Social Computing

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Abstract

Biomedical literature is the primary repository of biomedical knowledge in which PubMed is the most absolute database for collecting, organizing and analyzing textual knowledge. The high dimensionality of the natural language text makes the text data quite noisy and sparse in the vector space. Hence, the data preprocessing and feature selection are important processes for the text processing issues. Ontologies select the meaningful terms semantically associated with the concepts from a document to reduce the dimensionality of the original text. In this chapter, semantic-based indexing approaches are proposed with cognitive search which makes use of domain ontology to extract relevant information from big and diverse data sets for users.

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Semantic-Based Indexing Approaches for Medical Document Clustering Using Cognitive Search

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