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Approach for microposts retrieval in microblogging platforms base | 33095
Journal of Information Technology & Software Engineering

Journal of Information Technology & Software Engineering
Open Access

ISSN: 2165- 7866

+44 1300 500008

Approach for microposts retrieval in microblogging platforms based on Semantic Web technologies and social network analysis


2nd Global Summit and Expo Multimedia & Applications

August 15-16, 2016 London, UK

El Habib Nfaoui

Sidi Mohamed Ben Abdellah University, Morocco

Scientific Tracks Abstracts: J Inform Tech Softw Eng

Abstract :

Microblogging platforms allow users to post short messages and content of interest, such as tweets and user statuses in friendship networks. Searching and mining microblog streams offer interesting technical challenges in many microblog search scenarios, and the goal is to determine what people are saying about concepts such as products, brands, persons, etc. However, retrieving short text and determining the subject of an individual micro post present a significant research challenge owing to several factors: creative language usage, high contextualization, the informal nature of micro blog posts and the limited length of this form of communication. Thus, micro blogging retrieval systems suffer from the problems of data sparseness and the semantic gap. To overcome these problems, recent studies on content-based microblog searching have focused on adding semantics to micro posts by linking short text to knowledge bases resources. Moreover, previous studies used bag-of-concepts representation by linking named entities to their corresponding knowledge base concepts. In the first part of this talk, we are going to review the drawbacks of these approaches. In the second part, we present a graph-of-concepts method that considers the relationships among concepts that match named entities in short text and their related concepts and contextualizes each concept in the graph by leveraging the linked nature of DBpedia as a Linked Open Data knowledge base and graph-based centrality theory. Finally, we introduce some experiment results, using a real Twitter dataset, to show the effectiveness of our approach.

Biography :

El Habib Nfaoui is currently an Associate Professor of Computer Science at the University of Sidi Mohammed Ben Abdellah. He obtained his PhD in Computer Science from University of Sidi Mohamed Ben Abdellah in Morocco and University of Lyon (LIESP Laboratory) in France under a COTUTELLE (co-advising) agreement. His current research interests are Information Retrieval, Semantic Web, Social Networks, Machine Learning, Web Services, Multi-Agent Systems, Decision-Making and Modeling. He is a Guest Editor of the International Journal of Intelligent Engineering Informatics (ACM, DBLP and so on). He Co-founded the International Conference on Intelligent Systems and Computer Vision (ISCV2015) and has served as Program Committee of various conferences. He has published several papers in reputed journals and presented at international conferences.

Email: elhabib.nfaoui@usmba.ac.ma

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