TY - GEN
T1 - Organizing information on the web through agreement-conflict relation classification
AU - Mizuno, Junta
AU - Nichols, Eric
AU - Watanabe, Yotaro
AU - Inui, Kentaro
PY - 2012
Y1 - 2012
N2 - The vast amount of information on the Web makes it difficult for users to comprehensively survey the various viewpoints on topics of interest. To help users cope with this information overload, we have developed an Information Organization System that applies state-of-theart technology from Recognizing Textual Entailment to automatically detect Web texts that are relevant to natural language queries and organize them into agreeing and conflicting groups. Users are presented with a bird's-eye-view visualization of the viewpoints on their queries that makes it easier to gain a deeper understanding of an issue. In this paper, we describe the implementation of our Information Organization System and evaluate our system through empirical analysis of the semantic relation recognition system that classifies texts and through a large-scale usability study. The empirical evaluation and usability study both demonstrate the usefulness of our system. User feedback further shows that by exposing our users to differing viewpoints promotes objective thinking and helps to reduce confirmation bias.
AB - The vast amount of information on the Web makes it difficult for users to comprehensively survey the various viewpoints on topics of interest. To help users cope with this information overload, we have developed an Information Organization System that applies state-of-theart technology from Recognizing Textual Entailment to automatically detect Web texts that are relevant to natural language queries and organize them into agreeing and conflicting groups. Users are presented with a bird's-eye-view visualization of the viewpoints on their queries that makes it easier to gain a deeper understanding of an issue. In this paper, we describe the implementation of our Information Organization System and evaluate our system through empirical analysis of the semantic relation recognition system that classifies texts and through a large-scale usability study. The empirical evaluation and usability study both demonstrate the usefulness of our system. User feedback further shows that by exposing our users to differing viewpoints promotes objective thinking and helps to reduce confirmation bias.
KW - Agreement and conflict relations
KW - Information organization
KW - Natural language processing
KW - Recognizing textual entailment
UR - http://www.scopus.com/inward/record.url?scp=84871564271&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84871564271&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-35341-3_11
DO - 10.1007/978-3-642-35341-3_11
M3 - Conference contribution
AN - SCOPUS:84871564271
SN - 9783642353406
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 126
EP - 137
BT - Information Retrieval Technology - 8th Asia Information Retrieval Societies Conference, AIRS 2012, Proceedings
T2 - 8th Asia Information Retrieval Societies Conference, AIRS 2012
Y2 - 17 December 2012 through 19 December 2012
ER -