- Title
- iTopic: influential topic discovery from information networks via keyword query
- Creator
- Li, Jianxin; Liu, Chengfei; Chen, Lu; He, Zhenying; Datta, Amitava; Xia, Feng
- Date
- 2017
- Type
- Text; Conference proceedings
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/183846
- Identifier
- vital:16381
- Identifier
- http://dx.doi.org/10.1145/3041021.3054719
- Identifier
- ISBN:978-1-4503-4914-7/17/04
- Abstract
- The 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.
- Publisher
- International World Wide Web Conferences Steering CommitteeRepublic and Canton of GenevaSwitzerland
- Relation
- WWW '17: 26th International World Wide Web Conference Perth Australia; April 3 - 7, 2017 p. 231-235
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- https://creativecommons.org/licenses/by/4.0/
- Rights
- Copyright 2017 International World Wide Web Conference Committe (IW3C2)ACM published under Creative Commons CC BY 4.0 License.
- Rights
- Open Access
- Subject
- Information network; Topic discovery; Keyword query
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