---
title: "Learning to Understand Web Site Update Requests"
authors:
  - "William W. Cohen"
  - "Einat Minkov"
  - "Anthony Tomasic"
doi: ""
url: "https://ijcai.org/proceedings/2005/164"
pdf: "https://ijcai.org/proceedings/2005/0164.pdf"
venue: "Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence"
year: 2005
pages: "1028-1032"
track: ""
keywords:
---

# Learning to Understand Web Site Update Requests

William W. Cohen, Einat Minkov, Anthony Tomasic

*Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence*, pages 1028-1032.

## Abstract

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 databasebacked 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.