ACTraversal: Ranking crowdsourced commonsense assertions and certifications

Tao Hsuan Chang*, Yen Ling Kuo, Jane Yung Jen Hsu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Building commonsense knowledge bases is a challenging undertaking. While we have witnessed the successful collection of large amounts of commonsense knowledge by either automatic text mining or games with a purpose (GWAP), such data are of limited precision. Verifying data is typically done with repetition, which works better for very large data sets. Our research proposes a novel approach to data verification by coupling multiple data collection methods. This paper presents ACTraversal, a graph traversal algorithm for ranking data collected from GWAP and text mining. Experiments on aggregating data from two GWAPs, i.e. Virtual Pets and Top10, with two text mining tools, i.e. SEAL and Google Distance, showed significant improvements.

Original languageEnglish
Title of host publicationAgents in Principle, Agents in Practice - 14th International Conference, PRIMA 2011, Proceedings
Pages234-246
Number of pages13
DOIs
StatePublished - 2011
Externally publishedYes
Event14th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2011 - Wollongong, NSW, Australia
Duration: 16 11 201118 11 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7047 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2011
Country/TerritoryAustralia
CityWollongong, NSW
Period16/11/1118/11/11

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