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iTopic: influential topic discovery from information networks via keyword query
conference contribution
posted on 2017-01-01, 00:00 authored by Jianxin LiJianxin Li, Chengfei Liu, Lu Chen, Zhenying He, Amitava Datta, Feng XiaThe rapid growth of information networks provides a significant opportunity for people to learn the world and find useful information for decision making. To find influential topics in a given context, instead of searching widely over the whole information network, normally it is wise to find the related communities first and then identify the influential topics in those communities. In this demonstration, we present a novel framework to compute the correlated sub-networks from a large information network such as CiteSeerX based on a user's keyword query, and to extract the influential topics from each correlated network. To help users understand the influential topics as a whole, we utilize a word cloud to represent the discovered topics for each correlated network. As such, multiple word clouds can be generated for different correlated networks, by which users can easily pick up their interested ones by reading the visualized topic descriptions over word clouds. To determine the sizes of different terms in a word cloud, we introduce a scoring scheme for assessing the influence of these terms in the corresponding networks. We demonstrate the functionality of our influential topic system, called iTopic, using the CiteSeerX information network data.
History
Event
International World Wide Web Conferences Steering Committee. Conference (26th : 2017 : Perth, W.A.)Series
International World Wide Web Conferences Steering Committee ConferencePagination
231 - 235Publisher
International World Wide Web Conferences Steering CommitteeLocation
Perth, W.A.Place of publication
Geneva, SwitzerlandPublisher DOI
Start date
2017-04-03End date
2017-04-07ISBN-13
978-1-4503-4914-7Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2017, International World Wide Web Conference CommitteeEditor/Contributor(s)
[Unknown]Title of proceedings
WWW '17 : Proceedings of the 26th International Conference on World Wide Web CompanionUsage metrics
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