NLPX at INEX 2006

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Abstract

XML information retrieval (XML-IR) systems aim to better fulfil users' information needs than traditional IR systems by returning results lower than the document level. In order to use XML-IR systems users must encapsulate their structural and content information needs in a structured query. Historically, these structured queries have been formatted using formal languages such as 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. INEX's NLP task investigates the potential of using natural language to specify structured queries. QUT has participated in the NLP task with our system NLPX since its inception. Here, we discuss the changes we've made to NLPX since last year, including our efforts to port NLPX to Wikipedia. Second, we present the results from the 2006 INEX track where NLPX was the best performing participant in the Thorough and Focused tasks. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Woodley, A., & Geva, S. (2007). NLPX at INEX 2006. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4518 LNCS, pp. 302–311). Springer Verlag. https://doi.org/10.1007/978-3-540-73888-6_30

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