Learning to understand web site update requests

William W. Cohen, Einat Minkov, Anthony Tomasic

Research output: Contribution to journalConference articlepeer-review


Although Natural Language Processing (NLP) for requests for information has been well-studied, there has been little prior work on understanding requests to update information. In this paper, we propose an intelligent system that can process natural language website update requests semi-automatically. In particular, this system can analyze requests, posted via email, to update the factual content of individual tuples in a database-backed website. Users' messages are processed using a scheme decomposing their requests into a sequence of entity recognition and text classification tasks. Using a corpus generated by human-subject experiments, we experimentally evaluate the performance of this system, as well as its robustness in handling request types not seen in training, or user-specific language styles not seen in training.

Original languageEnglish
Pages (from-to)1028-1033
Number of pages6
JournalIJCAI International Joint Conference on Artificial Intelligence
StatePublished - 2005
Externally publishedYes
Event19th International Joint Conference on Artificial Intelligence, IJCAI 2005 - Edinburgh, United Kingdom
Duration: 30 Jul 20055 Aug 2005

ASJC Scopus subject areas

  • Artificial Intelligence


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