Towards Multi-modal Extraction and Summarization of Conversations

For many business intelligence applications, decision making depends critically on the information contained in all forms of “informal” text documents, such as emails, meeting summaries, attachments and web documents. For example, in a meeting, the topic of developing a new product was first raised. In subsequent follow-up emails, additional comments and discussions were added, which included links to web documents describing similar products in the market and user reviews on those products. A concise summary of this “conversation” is obviously valuable. However, existing technologies are inadequate in at least two fundamental ways. First, extracting “conversations” embedded in multi-genre documents is very challenging. Second, applying existing multi-document summarization techniques, where were designed mainly for formal documents, have proved to be highly ineffective when applied to informal documents like emails. In this talk, we first review some of the earlier works done on extracting email conversations. We also give an overview of email summarization and meeting summarization methods. We then present several open problems that need to be solved for multi-modal extraction and summarization of conversations to become a reality. Last but not least, we specifically focus on extraction and summarization of sentiments in emails and blogs.

Authors and Affiliations

1. University of British Columbia, Canada

   Raymond Ng

Editors and Affiliations

1. Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China

   Qing Li

2. Department of Computer Science & Technology, Tsinghua University, Beijing, China

   Ling Feng

3. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby BC, Canada

   Jian Pei

4. Department of Computer Science, University of Vermont, VT 05405, Burlington, USA

   Sean X. Wang

5. School of Information Technology and Electrical Engineering, The University of Queensland, QLD 4072, Brisbane, Australia

   Xiaofang Zhou

6. Jiangsu Provincial Key Lab of Computer Information Processing Technology School of Computer Science & Technology, Soochow University China, 1 shizi Street Suzhou, 215006, Jiangsu, China

   Qiao-Ming Zhu

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