Recent developments in natural language text retrieval
Tomek Strzalkowski, Jose Perez Carballo · 1993
This paper reports on some recent developments in our natural language text retrieval system. The system uses advanced natural language processing techniques to enhance the effectiveness of term-based document retrieval. The backbone of our system is a traditional statistical engine which builds inverted index files from pre-processed documents, and then searches and ranks the documents in response to user queries. Natural language processing is used to (1) preprocess the documents in order to extract content-carrying terms, (2) discover inter-term dependencies and build a conceptual hierarchy specific to the database domain, and (3) process user's natural language requests into effective search queries. For the present TREC-2 effort, the total of 550 MBytes of Wall Street Journal articles (ad-hoc queries database) and 300 MBytes of San Jose Mercury articles (routing data) have been processed. In terms of text quantity this represents approximately 130 million words of English. Unlike ...