A predictive framework for retrieving the best answer

In a question answering (QA) system, each user interaction with the system is different and since there are a variety of arguably correct answers to complex questions, identifying factors for improving the quality of the retrieved answer is difficult. This research aims to develop a framework that identifies predictive variables for the best quality answer in a QA system. It was found that accuracy, completeness and relevance were predictors of best answer. We believe that these findings can serve to guide future developments in the answer extraction modules in the QA systems.

[1]  Tomek Strzalkowski,et al.  ILQUA--An IE-Driven Question Answering System , 2005, TREC.

[2]  Jacquelyn A. Burkell,et al.  Believe it or not: Factors influencing credibility on the Web , 2002, J. Assoc. Inf. Sci. Technol..

[3]  P. Resnick,et al.  The value of reputation on eBay: A controlled experiment , 2006 .

[4]  Don Fallis,et al.  Indicators of accuracy for answers to ready reference questions on the Internet , 2004, J. Assoc. Inf. Sci. Technol..

[5]  Dahui Li,et al.  Reputation distribution and consumer-to-consumer online auction market structure: an exploratory study , 2006, Decis. Support Syst..

[6]  Nina Wacholder,et al.  A model for quantitative evaluation of an end-to-end question-answering system , 2007, J. Assoc. Inf. Sci. Technol..

[7]  Qingtian Zeng,et al.  Semantic Pattern for User-Interactive Question Answering , 2006, SKG.

[8]  Qingtian Zeng,et al.  A user reputation model for a user‐interactive question answering system , 2006, Concurr. Comput. Pract. Exp..

[9]  Leah S. Larkey,et al.  Automatic essay grading using text categorization techniques , 1998, SIGIR '98.

[10]  Oren Etzioni,et al.  Scaling question answering to the Web , 2001, WWW '01.

[11]  Jimmy J. Lin,et al.  The role of context in question answering systems , 2003, CHI Extended Abstracts.

[12]  Diane M. Strong,et al.  Beyond Accuracy: What Data Quality Means to Data Consumers , 1996, J. Manag. Inf. Syst..

[13]  Dietrich Klakow,et al.  Exploring Correlation of Dependency Relation Paths for Answer Extraction , 2006, ACL.

[14]  Bernardo Magnini,et al.  Combining Linguistic Processing and Web Mining for Question Answering: ITC-irst at TREC 2004 , 2004, TREC.

[15]  N. Roberts,et al.  Value-added processes in information systems , 1986 .

[16]  W. Bruce Croft,et al.  A framework to predict the quality of answers with non-textual features , 2006, SIGIR.

[17]  Qingtian Zeng,et al.  Using a User-Interactive QA System to Capture Student's Interest and Authority About Course Content , 2006, ICWL.

[18]  Loren G. Terveen,et al.  Does “authority” mean quality? predicting expert quality ratings of Web documents , 2000, SIGIR '00.

[19]  Peter Haase,et al.  Question answering on top of the BT digital library , 2006, WWW '06.

[20]  Jimmy J. Lin,et al.  Answer Extraction, Semantic Clustering, and Extractive Summarization for Clinical Question Answering , 2006, ACL.

[21]  Keng Siau,et al.  Measuring information quality of web sites: development of an instrument , 1999, ICIS.

[22]  Ziming Liu,et al.  Evaluating the credibility of scholarly information on the web: A cross cultural study , 2005 .

[23]  Jimmy J. Lin,et al.  What Makes a Good Answer? The Role of Context in Question Answering , 2003, INTERACT.

[24]  Nicholas J. Belkin,et al.  Understanding Judgment of Information Quality and Cognitive Authority in the WWW , 1998 .

[25]  Diane M. Strong,et al.  Data quality in context , 1997, CACM.

[26]  Soo Young Rieh.  Judgement of information quality and cognitive authority in the Web , 2002 .

[27]  Soo Young Rieh.  Judgment of information quality and cognitive authority in the Web , 2002, J. Assoc. Inf. Sci. Technol..