Lexical analysis and stoplists
Information retrieval
A simple rule-based part of speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
Applying Transformation-Based Error-Driven Learning to Structured Natural Language Queries
CW '05 Proceedings of the 2005 International Conference on Cyberworlds
INEX'04 Proceedings of the Third international conference on Initiative for the Evaluation of XML Retrieval
GPX: gardens point XML information retrieval at INEX 2004
INEX'04 Proceedings of the Third international conference on Initiative for the Evaluation of XML Retrieval
INEX'04 Proceedings of the Third international conference on Initiative for the Evaluation of XML Retrieval
ACM SIGIR Forum
Refining Keyword Queries for XML Retrieval by Combining Content and Structure
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
FDIA'07 Proceedings of the 1st BCS IRSG conference on Future Directions in Information Access
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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 needs in the form of a structured query. Historically, 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 and are too closely bound to the underlying physical structure of the collection. Hence, recent research has investigated the idea of specifying users’ content and structural requirements via natural language queries (NLQs). The NLP track was established at INEX 2004 to promote research into this area, and QUT participated with the system NLPX. Here, we discuss changes we’ve made to the system since last year, as well as our participation in INEX 2005.