A fundamental issue with current truth discovery methods is that they generally assume only one true value for each object, while in reality objects may have multiple true values. We propose a graph-based approach, called SmartMTD, to relax this assumption in truth discovery. SmartMTD models and quantifies two types of source relations to estimate source reliability precisely and to detect malicious agreement among sources for multi-truth discovery. Two graphs are constructed based on the modeled source relations, which are further used to derive two aspects of source reliability via random walk computation.
|Title of host publication||26th International World Wide Web Conference 2017, WWW 2017 Companion|
|Publisher||International World Wide Web Conferences Steering Committee|
|Number of pages||2|
|Publication status||Published - 2017|
|Event||26th International World Wide Web Conference, WWW 2017 Companion - Perth, Australia|
Duration: 3 Apr 2017 → 7 Apr 2017
|Conference||26th International World Wide Web Conference, WWW 2017 Companion|
|Period||3/04/17 → 7/04/17|
Bibliographical noteCopyright 2017 International World Wide Web Conference Committee (IW3C2). Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.
- Copy Detection
- Multi-Truth Discovery
- Object Popularity