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An Empirical Study of Corpus-Based Response Automation Methods for an E-mail-Based Help-Desk Domain
- Source :
- Computational Linguistics. 35:597-635
- Publication Year :
- 2009
- Publisher :
- MIT Press - Journals, 2009.
-
Abstract
- This article presents an investigation of corpus-based methods for the automation of help-desk e-mail responses. Specifically, we investigate this problem along two operational dimensions: (1) information-gathering technique, and (2) granularity of the information. We consider two information-gathering techniques (retrieval and prediction) applied to information represented at two levels of granularity (document-level and sentence-level). Document-level methods correspond to the reuse of an existing response e-mail to address new requests. Sentence-level methods correspond to applying extractive multi-document summarization techniques to collate units of information from more than one e-mail. Evaluation of the performance of the different methods shows that in combination they are able to successfully automate the generation of responses for a substantial portion of e-mail requests in our corpus. We also investigate a meta-selection process that learns to choose one method to address a new inquiry e-mail, thus providing a unified response automation solution.
- Subjects :
- Linguistics and Language
Information retrieval
business.industry
Process (engineering)
Computer science
Reuse
computer.software_genre
Automation
Automatic summarization
Language and Linguistics
Computer Science Applications
Domain (software engineering)
Empirical research
Artificial Intelligence
Granularity
Data mining
business
computer
Desk
Subjects
Details
- ISSN :
- 15309312 and 08912017
- Volume :
- 35
- Database :
- OpenAIRE
- Journal :
- Computational Linguistics
- Accession number :
- edsair.doi...........5932b2a2dbb7b7598a7122f74d558f59