A just-in-time keyword extraction from meeting transcripts using temporal and participant information
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- 作者：Hyun-Je Song ; Junho Go ; Seong-Bae Park…
- 关键词：Just ; In ; Time keyword extraction ; Graph ; Based keyword extraction ; Forgetting curve ; Keyword extraction from meeting transcripts
- 刊名：Journal of Intelligent Information Systems
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：48
- 期：1
- 页码：117-140
- 全文大小：
- 刊物类别：Computer Science
- 刊物主题：Information Storage and Retrieval; Data Structures, Cryptology and Information Theory; Artificial Intelligence (incl. Robotics); IT in Business; Document Preparation and Text Processing;
- 出版者：Springer US
- ISSN：1573-7675
- 卷排序：48
文摘
In a meeting, it is often desirable to extract the keywords from each utterance as soon as it is spoken. Therefore, this paper proposes a just-in-time keyword extraction from meeting transcripts. The proposed method considers three major factors that make it different from keyword extraction from normal texts. The first factor is the temporal history of the preceding utterances that grants higher importance to recent utterances than older ones, and the second is topic relevance, which focuses only on the preceding utterances relevant to the current utterance. The final factor is the participants. The utterances spoken by the current speaker should be considered more important than those spoken by other participants. The proposed method considers these factors simultaneously under a graph-based keyword extraction with some graph operations. Experiments on two data sets in English and Korean show that consideration of these factors results in improved performance in keyword extraction from meeting transcripts.