Knowledge Graph-based Scholarly Search Engine (KGSSE) - George, Soumya
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The success of search engines depends heavily on the satisfaction of users. The main expectation of scholarly users is to search articles based on their research areas of interest, not merely based on subject, but by categories or subcategories. Knowledge Graph-based Scholarly Search Engine (KGSSE) is a Graph-based Academic Search Engine to meet the main expectation of academic search engine users to search an article through six levels, namely subject, categories, areas, disciplines, fields, and keywords. A sequence knowledge graph-based representation represents the contents of articles in…mehr

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Produktbeschreibung
The success of search engines depends heavily on the satisfaction of users. The main expectation of scholarly users is to search articles based on their research areas of interest, not merely based on subject, but by categories or subcategories. Knowledge Graph-based Scholarly Search Engine (KGSSE) is a Graph-based Academic Search Engine to meet the main expectation of academic search engine users to search an article through six levels, namely subject, categories, areas, disciplines, fields, and keywords. A sequence knowledge graph-based representation represents the contents of articles in sequence in a neat format that provides automatic subject labeling of articles at the indexing time itself using a six-level predefined taxonomy of a total of 81189 keywords.
Autorenporträt
Dr. Soumya George is an Asst. Professor of Dept. of Computer Applications at St. George¿s College, Aruvithura. She completed her Ph. D in Computer Science from Cochin University of Science and Technology. Her research areas of interest include data mining, information retrieval, etc. She had many journal and conference publications to her credit.