Information Extraction via Path Merging

Abstract. In this paper, we describe a new approach to information extraction that neatly integrates top-down hypothesis driven information with bottom-up data driven information. The aim of the kelp project is to combine a variety of natural language processing techniques so that we can extract useful elements of information from a collection of documents and then re-present this information in a manner that is tailored to the needs of a specific user. Our focus here is on how we can build richly structured data objects by extracting information from web pages; as an example, we describe our methods in the context of extracting information from web pages that describe laptop computers. Our approach, which we call path-merging, involves using relatively simple techniques for identifying what are normally referred to as named entities, then allowing more sophisticated and intelligent techniques to combine these elements of information: effectively, we view the text as providing a coll...

• Type: Conference
• Year: 2003
• Where: AUSAI
• Authors: Robert Dale, Cécile Paris, Marc Tilbrook
• Keywords: Artificial Intelligence, AUSAI 2003, Data Driven Information, Hypothesis Driven Information, Information Extraction