TY - GEN
T1 - Compare&contrast
T2 - 16th International World Wide Web Conference, WWW2007
AU - Liu, Jiahui
AU - Wagner, Earl
AU - Birnbaum, Lawrence A
PY - 2007
Y1 - 2007
N2 - Comparing and contrasting is an important strategy people employ to understand new situations and create solutions for new problems. Similar events can provide hints for problem solving, as well as larger contexts for understanding the specific circumstances of an event. Lessons can leaned from past experience, insights can be gained about the new situation from familiar examples, and trends can be discovered among similar events. As the largest knowledge base for human beings, the Web provides both an opportunity and a challenge to discover comparable cases in order to facilitate situation analysis and problem solving. In this paper, we present Compare & Contrast, a system that uses the Web to discover comparable cases for news stories, documents about similar situations but involving distinct entities. The system analyzes a news story given by the user and builds a model of the story. With the story model, the system dynamically discovers entities comparable to the main entity in the original story and uses these comparable entities as seeds to retrieve web pages about comparable cases. The system is domain independent, does not require any domain-specific knowledge engineering efforts, and deals with the complexity of unstructured text and noise on the web in a robust way. We evaluated the system with an experiment on a collection of news articles and a user study.
AB - Comparing and contrasting is an important strategy people employ to understand new situations and create solutions for new problems. Similar events can provide hints for problem solving, as well as larger contexts for understanding the specific circumstances of an event. Lessons can leaned from past experience, insights can be gained about the new situation from familiar examples, and trends can be discovered among similar events. As the largest knowledge base for human beings, the Web provides both an opportunity and a challenge to discover comparable cases in order to facilitate situation analysis and problem solving. In this paper, we present Compare & Contrast, a system that uses the Web to discover comparable cases for news stories, documents about similar situations but involving distinct entities. The system analyzes a news story given by the user and builds a model of the story. With the story model, the system dynamically discovers entities comparable to the main entity in the original story and uses these comparable entities as seeds to retrieve web pages about comparable cases. The system is domain independent, does not require any domain-specific knowledge engineering efforts, and deals with the complexity of unstructured text and noise on the web in a robust way. We evaluated the system with an experiment on a collection of news articles and a user study.
KW - Comparable case
KW - Intelligent information retrieval
KW - Knowledge discovery
KW - Query formulation
UR - http://www.scopus.com/inward/record.url?scp=35348816211&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=35348816211&partnerID=8YFLogxK
U2 - 10.1145/1242572.1242646
DO - 10.1145/1242572.1242646
M3 - Conference contribution
AN - SCOPUS:35348816211
SN - 1595936548
SN - 9781595936547
T3 - 16th International World Wide Web Conference, WWW2007
SP - 541
EP - 550
BT - 16th International World Wide Web Conference, WWW2007
Y2 - 8 May 2007 through 12 May 2007
ER -