SemanticDriven Knowledge Extraction And Classification For User Behaviour Analysis In Digital Library

Abstract

ABSTRACT newline newlineWorld Wide Web has become a universal environment for human interface, collaboration, communication, data storage and data sharing. More number of websites is growing rapidly due to the growth of e-learning, e- commerce and other business activities. Due to unprecedented growth of information and size of World Wide Web, it becomes difficult to search and extract the pertinent information from web. Information retrieval is a technique to understand the text in the web pages. The purpose of Semantic Web is to allow the Machines to advance knowledge itself by recognizing its meaning. Resources are annotated on the Semantic Web using Ontologies. It is used to assign meaning to the text on the web. Ontology serves as a knowledge base domain by instantiating its concepts and semantic query language retrieves the information from the domain. newline newline newlineThe essential intention of this research is to predict variation in the directional behaviour of the digital library user based on their recommended data. The significance of this research lies in enlightening the user behaviour in digital library using semantic driven approach. An important contribution of this research work corresponds to retrieve accurate data from websites by using semantically enhanced various algorithms. This research concerns on identifying educational digital library web userand#8223;s behaviour. newline newline newlineThe user behaviour unstructured data are pre-processed and semantically extracted using suggested weighted TF-IDF normalization method. Then the extracted features are selected using Improved newline newline newline newlineEnsemble based FS method. A fuzzy based ontology is designed with the selected features by combining gravitational search optimization algorithm to enhance the fuzzy rules that are being created for ontology generation. The studentand#8223;s explored behaviour ontology is automatically spawned using protégé editor 4.3. newline newline newlineThe proposed semantic similarity-based Improved J48 newline newlineInduction Learning algorithm facilitates the system to identify patterns and re