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Quality-Aware Collaborative Quality-Aware Collaborative Question Answering: Methods Question Answering: Methods
and Evaluationand Evaluation
Maggy Anastasia Suryanto, Ee-Peng Lim, Aixin Sun, and Roger H. L. Chiang.
In Proceedings of the Second ACM International Conference on Web Search and Data Mining
(Barcelona, Spain, February 9-12, 2009).
Prepared and Presented by Baichuan LiApril 19, 2023
OutlineOutlineIntroductionQuality-Aware FrameworkExpertise Based MethodsExperimentsConclusion
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IntroductionIntroductionCommunity-Based Question-
Answering (CQA) Services
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ObjectiveObjectiveAutomatically find good answers
for a user given questions from a community QA portal◦answer features◦user expertise of answers
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Expertise Based MethodsExpertise Based Methods
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Relevance score Quality score
Question Independent Question Independent ExpertiseExpertise
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EXHITS uses qscore_exhits(a) as the quality score of an answer a given in below equation:
authority
hub
Question Dependent Question Dependent ExpertiseExpertise
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EX_QD
EX_QD’
Answer Relevance ModelsAnswer Relevance ModelsAnswer ranking by Yahoo!
Answers Query likelihood retrieval model
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all answers and questions in the dataset
ExperimentsExperiments
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Methods Compared◦ BasicYA
BasicYA(subject + content) BasicYA(subject + content + best answers)
◦ BasicQL Adopts query likelihood retrieval model to score
the relevance of an answer
◦ NT (classification based on non-textual answer features) maximum entropy approach 9 features
EvaluationEvaluation
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The top 20 of the ranked answers of each methods were manually judged in terms of their relevance and quality.
The following evaluation metrics are used to evaluate the accuracy of the methods:
ConclusionConclusion Introduce a quality-aware QA framework that
considers both answer relevance and quality in selecting answers to be returned.
Develop several QA methods (namely, EXHITS, EXHITS QD, EX QD and EX QD') that consider answerer expertise to determine answer quality.
Conducted extensive experiments and these experiments showed that quality-aware methods can improve both quality and overall performance. Among them, the methods EX QD and EX QD' using question dependent answerer expertise have the best performance.
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