A generic framework for extraction of knowledge from social web sources (social networking websites) for an online recommendation system

Mining social web data is a challenging task and finding user interest for personalized and non-personalized recommendation systems is another important task. Knowledge sharing among web users has become crucial in determining usage of web data and personalizing content in various social websites as...

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Autores principales:	Javubar Sathick, Jaya Venkat
Formato:	article
Lenguaje:	EN
Publicado:	Athabasca University Press 2015
Materias:	Knowledge Management Knowledge extraction Web mining Decision making system R tool Natural language processing Special aspects of education LC8-6691
Acceso en línea:	https://doaj.org/article/a6f5562835634cbb9dd077d3b2a7bfd4
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spelling	oai:doaj.org-article:a6f5562835634cbb9dd077d3b2a7bfd42021-12-02T17:00:37ZA generic framework for extraction of knowledge from social web sources (social networking websites) for an online recommendation system10.19173/irrodl.v16i2.20931492-3831https://doaj.org/article/a6f5562835634cbb9dd077d3b2a7bfd42015-04-01T00:00:00Zhttp://www.irrodl.org/index.php/irrodl/article/view/2093https://doaj.org/toc/1492-3831Mining social web data is a challenging task and finding user interest for personalized and non-personalized recommendation systems is another important task. Knowledge sharing among web users has become crucial in determining usage of web data and personalizing content in various social websites as per the user’s wish. This paper aims to design a framework for extracting knowledge from web sources for the end users to take a right decision at a crucial juncture. The web data is collected from various web sources and structured appropriately and stored as an ontology based data repository. The proposed framework implements an online recommender application for the learners online who pursue their graduation in an open and distance learning environment. This framework possesses three phases: data repository, knowledge engine, and online recommendation system. The data repository possesses common data which is attained by the process of acquiring data from various web sources. The knowledge engine collects the semantic data from the ontology based data repository and maps it to the user through the query processor component. Establishment of an online recommendation system is used to make recommendations to the user for a decision making process. This research work is implemented with the help of an experimental case study which deals with an online recommendation system for the career guidance of a learner. The online recommendation application is implemented with the help of R-tool, NLP parser and clustering algorithm.This research study will help users to attain semantic knowledge from heterogeneous web sources and to make decisions. Javubar SathickJaya VenkatAthabasca University PressarticleKnowledge ManagementKnowledge extractionWeb miningDecision making systemR toolNatural language processingSpecial aspects of educationLC8-6691ENInternational Review of Research in Open and Distributed Learning, Vol 16, Iss 2 (2015)
institution	DOAJ
collection	DOAJ
language	EN
topic	Knowledge Management Knowledge extraction Web mining Decision making system R tool Natural language processing Special aspects of education LC8-6691
spellingShingle	Knowledge Management Knowledge extraction Web mining Decision making system R tool Natural language processing Special aspects of education LC8-6691 Javubar Sathick Jaya Venkat A generic framework for extraction of knowledge from social web sources (social networking websites) for an online recommendation system
description	Mining social web data is a challenging task and finding user interest for personalized and non-personalized recommendation systems is another important task. Knowledge sharing among web users has become crucial in determining usage of web data and personalizing content in various social websites as per the user’s wish. This paper aims to design a framework for extracting knowledge from web sources for the end users to take a right decision at a crucial juncture. The web data is collected from various web sources and structured appropriately and stored as an ontology based data repository. The proposed framework implements an online recommender application for the learners online who pursue their graduation in an open and distance learning environment. This framework possesses three phases: data repository, knowledge engine, and online recommendation system. The data repository possesses common data which is attained by the process of acquiring data from various web sources. The knowledge engine collects the semantic data from the ontology based data repository and maps it to the user through the query processor component. Establishment of an online recommendation system is used to make recommendations to the user for a decision making process. This research work is implemented with the help of an experimental case study which deals with an online recommendation system for the career guidance of a learner. The online recommendation application is implemented with the help of R-tool, NLP parser and clustering algorithm.This research study will help users to attain semantic knowledge from heterogeneous web sources and to make decisions.
format	article
author	Javubar Sathick Jaya Venkat
author_facet	Javubar Sathick Jaya Venkat
author_sort	Javubar Sathick
title	A generic framework for extraction of knowledge from social web sources (social networking websites) for an online recommendation system
title_short	A generic framework for extraction of knowledge from social web sources (social networking websites) for an online recommendation system
title_full	A generic framework for extraction of knowledge from social web sources (social networking websites) for an online recommendation system
title_fullStr	A generic framework for extraction of knowledge from social web sources (social networking websites) for an online recommendation system
title_full_unstemmed	A generic framework for extraction of knowledge from social web sources (social networking websites) for an online recommendation system
title_sort	generic framework for extraction of knowledge from social web sources (social networking websites) for an online recommendation system
publisher	Athabasca University Press
publishDate	2015
url	https://doaj.org/article/a6f5562835634cbb9dd077d3b2a7bfd4
work_keys_str_mv	AT javubarsathick agenericframeworkforextractionofknowledgefromsocialwebsourcessocialnetworkingwebsitesforanonlinerecommendationsystem AT jayavenkat agenericframeworkforextractionofknowledgefromsocialwebsourcessocialnetworkingwebsitesforanonlinerecommendationsystem AT javubarsathick genericframeworkforextractionofknowledgefromsocialwebsourcessocialnetworkingwebsitesforanonlinerecommendationsystem AT jayavenkat genericframeworkforextractionofknowledgefromsocialwebsourcessocialnetworkingwebsitesforanonlinerecommendationsystem
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A generic framework for extraction of knowledge from social web sources (social networking websites) for an online recommendation system

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