Question and Answering System through Search Result Summarization of Q&A Documents


KIPS Transactions on Software and Data Engineering, Vol. 3, No. 4, pp. 149-154, Apr. 2014
10.3745/KTSDE.2014.3.4.149, Full Text:

Abstract

A user should pick up relevant answers by himself from various search results when using user participation question answering community like Knowledge-iN. If refined answers are automatically provided, usability of question answering community must be improved. This paper divides questions in Q&A documents into 4 types(word, list, graph and text), then proposes summarizing methods for each question type using document statistics. Summarized answers for word, list and text type are obtained by question clustering and calculating scores for words using frequency, proximity and confidence of answers. Answers for graph type is shown by extracting user opinion from answers.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from September 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[IEEE Style]
H. A. Lee and D. H. Yoo, "Question and Answering System through Search Result Summarization of Q&A Documents," KIPS Transactions on Software and Data Engineering, vol. 3, no. 4, pp. 149-154, 2014. DOI: 10.3745/KTSDE.2014.3.4.149.

[ACM Style]
Hyun Ah Lee and Dong Hyun Yoo. 2014. Question and Answering System through Search Result Summarization of Q&A Documents. KIPS Transactions on Software and Data Engineering, 3, 4, (2014), 149-154. DOI: 10.3745/KTSDE.2014.3.4.149.