WikiTrends: Unstructured wikipedia-based text analytics framework

Gerguis, Michel Naim; Salama, Cherif; El-Kharashi, M. Watheq;

Abstract


WikiTrends is a new analytics framework for Wikipedia articles. It adds the temporal/spatial dimensions to Wikipedia to visualize the extracted information converting the big static encyclopedia to a vibrant one by enabling the generation of aggregated views in timelines or heat maps for any user-defined collection from unstructured text. Data mining techniques were applied to detect the location, start and end year of existence, gender, and entity class for 4.85 million pages. We evaluated our extractors over a small manually tagged random set of articles. Heat maps of notable football players’ counts over history or dominant occupations in some specific era are samples of WikiTrends maps while timelines can easily illustrate interesting fame battles over history between male and female actors, music genres, or even between American, Italian, and Indian films. Through information visualization and simple configurations, WikiTrends starts a new experience in answering questions through a figure.


Other data

Title WikiTrends: Unstructured wikipedia-based text analytics framework
Authors Gerguis, Michel Naim; Salama, Cherif ; El-Kharashi, M. Watheq
Keywords Data mining | Entity analytics | Entity classification | Finegrained classification | Text analytics | Text classification | Text understanding | Wikipedia
Issue Date 1-Jan-2017
Publisher SPRINGER INTERNATIONAL PUBLISHING AG
Journal Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 
ISBN 9783319595689
ISSN 03029743
DOI 10.1007/978-3-319-59569-6_6
Scopus ID 2-s2.0-85021723448
Web of science ID WOS:000434206800006

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