Applying Transformation-Based Error-Driven Learning to Structured Natural Language Queries

Woodley, Alan P. & Geva, Shlomo (2005) Applying Transformation-Based Error-Driven Learning to Structured Natural Language Queries. In Kunni, Tosiyasu L., Hock Soon, Seah, & Sourin, Alexi (Eds.) International Conference on Cyberworlds, 23-25 November 2005, Singapore.

View at publisher


XML information retrieval (XML-IR) systems aim to provide users with highly exhaustive and highly specific results. To interact with XML-IR systems, users must express both their content and structural requirement, in the form of a structured query. Traditionally, these structured queries have been formatted using formal languages such as XPath or NEXI. Unfortunately, formal query languages are very complex and too difficult to be used by experienced, let alone casual users. Therefore, recent research has investigated the idea of specifying users’ content and structural needs via natural language queries (NLQs). In previous research we developed NLPX, a natural language interface to an XML-IR system. Here we present additions we have made to NLPX. The additions involve the application of transformation-based error-driven learning (TBL) to structured NLQs, to derive special connotations and group words into an atomic unit of information. TBL has successfully been applied to other areas of natural language processing; however, this paper presents the first time it has been applied to structured NLQs. Here, we investigate the applicability of TBL to NLQs and compare the TBL-based system, with our previous system and a system with a formal language interference. Our results show that TBL is effective for structured NLQs, and that structured NLQs a viable interface tor XML-IR systems.

Impact and interest:

1 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

169 since deposited on 11 Apr 2006
4 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 3834
Item Type: Conference Paper
Refereed: Yes
Keywords: Natural Language Queries, NLPX, XML, INEX, Information Retrieval, Search Engine Interfaces
DOI: 10.1109/CW.2005.19
ISBN: 0769523781
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Information Retrieval and Web Search (080704)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2005 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 11 Apr 2006 00:00
Last Modified: 29 Feb 2012 13:15

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page