Email is a stage: discovering people roles from email archives
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Using Speech Acts to Categorize Email and Identify Email Genres
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 03
Improving "email speech acts" analysis via n-gram selection
ACTS '09 Proceedings of the HLT-NAACL 2006 Workshop on Analyzing Conversations in Text and Speech
Automatically selecting answer templates to respond to customer emails
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Segmenting email message text into zones
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Detecting emails containing requests for action
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
| Hi-index | 0.00 |
The volume of email that help-desks receive every day is very high and often queries are repeated. Any kind of automation in processing of emails requires good understanding of the emails. In the current work we propose a schema for tagging author composed sentences in help-desk emails by the intent of the author. We have created a corpus taking email data from two help-desks and annotated them at sentence level. We have achieved significant accuracies in learning to automatically tag the sentences using n-gram features and some hand-picked lexical features. At every stage right from choice of schema to choice of features, we have tried to be domain independent or keep domain related information as a separate component. Automation of Tagging of Discourse Segments (TODS) in email, we propose is a significant step towards finding the discourse parse of emails.