A comparative study of information-gathering approaches for answering help-desk email inquiries

  • Authors:
  • Ingrid Zukerman;Yuval Marom

  • Affiliations:
  • Faculty of Information Technology, Monash University, Clayton, Victoria, Australia;Faculty of Information Technology, Monash University, Clayton, Victoria, Australia

  • Venue:
  • AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
  • Year:
  • 2006

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Abstract

We present a comparative study of corpus-based methods for the automatic synthesis of email responses to help-desk requests. Our methods were developed by considering two operational dimensions: (1) information-gathering technique, and (2) granularity of the information. In particular, we investigate two techniques – retrieval and prediction – applied to information represented at two levels of granularity – sentence level and document level. We also developed a hybrid method that combines prediction with retrieval. Our results show that the different approaches are applicable in different situations, addressing a combined 72% of the requests with either complete or partial responses.