Open AccessData Science Recommendation System using Semantic Technology
Author(s) -
Vishal Shah,
S Shridevi
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a9375.109119
Subject(s) - computer science , ontology , semantic web , world wide web , field (mathematics) , service (business) , documentation , data science , interface (matter) , web service , information retrieval , philosophy , mathematics , economy , epistemology , bubble , maximum bubble pressure method , parallel computing , pure mathematics , economics , programming language
Data Science is a field in which multidisciplinary blend of data inference, algorithm development, and technology are combined in order to solve analytically complex problems. Data science field tend to focus on a complex and large algorithmic technological problem having data at the core. Students at the starting of the learning phase don’t know all the technological and algorithmic aspects related to data science. Consulting through faculty or knowing from external source helps them to proceed towards the needed expertise that they want to gain. Data science recommendation system using semantic web data-science ontology and service-oriented architecture is proposed in our work to recommend students the appropriate resources for their queries. Recommending student significant information concerning books, on-line documentation, software tools, public code repositories, and experts, tutors to be contacted based on student query or previous exam scores is the main objective of the work. Ontology based service-oriented web platform with a conversational user interface that use NLP (Natural Language Processing) to recommend possible resources is proposed and tested to be efficient