Natural Language Processing and XML Retrieval
Woodley, Alan P. (2006) Natural Language Processing and XML Retrieval. In HCSNet SummerFest 06 Program, Information and Abstracts Book, 27/11/06 - 1/12/06, Sydney.
Traditional information retrieval systems respond to users’ queries with a ranked list of relevant documents. XML documents differ from flat text documents by explicitly separating content and structure. XML-IR systems aspire to exploit the additional resources of XML documents by providing users with more specific information than at the document level. However, in order to interact with XML-IR systems users require an interface that is powerful enough to capture their content and structural information need while also been user friendly. The standard interface for document-level IR systems are keywords, however, these only capture users’ content needs. Historically, formal languages, such as the XPath-like NEXI, have been used for XML-IR, however, they have proven too difficult to use by experts in XML-IR, let alone users less familiar with the domain. Natural language interfaces provide a novel approach that is both powerful enough to full capture users’ content and structural needs and user-friendly enough that it can be used intuitively. Furthermore, the success of applying natural language in information seeking fields that focus on a finer granularity of information than documents (such as question and answering) showcases the exciting potential for end-users if the fields of NLP and XMl-IR collaborate.
Citation countsare sourced monthly fromand 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 theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloadsdisplays 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.
|Item Type:||Conference Item (Poster)|
|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 2006 (please consult author)|
|Deposited On:||25 Sep 2007|
|Last Modified:||09 Jun 2010 22:46|
Repository Staff Only: item control page