Review Summarization Based on Linguistic Knowledge
- Review Summarization Based on Linguistic Knowledge
- 박경미; 박호건; 김형곤; 고희동
- 리뷰 마이닝; 자연어 처리; 리뷰 요약; Domain-knowledge extraction; aspect-opinion extraction; linguistic knowledge; review summarization
- Issue Date
- International Workshop on Social Networks and Social Web Mining
- , 105-114
- In this paper, we present a review summarization method
based on linguistic knowledge in order to generate a relevant summary
from the product or service review. The review summarization task can
be divided into two subtasks: the domain-knowledge extraction which
identifies clue words through statistical techniques, and the aspect-opinion
extraction which determines positive/negative aspect-opinion pairs for a
new sentence. Through checking the binary association in a given re-
view, our system can automatically acquire an aspect-opinion list and
the ranked sentences including aspect-opinion pairs. In this study, in
order to appropriately represent a review summary, we try to incorpo-
rate linguistic knowledge into two steps of review summary reporting.
In the first step, we reduce the number of the aspect-opinion pairs by
using semantic similarity between clue words. In the second step, we esti-
mate the sentence scores by utilizing several features such as the number
of aspects and the number of opinions. Experimental results show that
the performance of the review summarization task can be improved by
utilizing such linguistic knowledge. As an experimental data, we utilize
Korean reviews of a restaurant domain and a movie domain.
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- KIST Publication > Conference Paper
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