Email overload at work: an analysis of factors associated with email strain
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
Detection of question-answer pairs in email conversations
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Extracting personal names from email: applying named entity recognition to informal text
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Summarizing email conversations with clue words
Proceedings of the 16th international conference on World Wide Web
Finding question-answer pairs from online forums
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Quality versus quantity: e-mail-centric task management and its relation with overload
Human-Computer Interaction
RADAR: a personal assistant that learns to reduce email overload
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Learning trees and rules with set-valued features
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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Question-answer pairs extracted from email threads can help construct summaries of the thread, as well as inform semantic-based assistance with email. Previous work dedicated to email threads extracts only questions in interrogative form. We extend the scope of question and answer detection and pairing to encompass also questions in imperative and declarative forms, and to operate at sentence-level fidelity. Building on prior work, our methods are based on learned models over a set of features that include the content, context, and structure of email threads. For two large email corpora, we show that our methods balance precision and recall in extracting question-answer pairs, while maintaining a modest computation time.