Abstract
In this paper we describe our participation in the INEX 2010 ad-hoc track. We participated in three retrieval tasks (restricted focused task, relevant-in-context, restricted relevant-in-context) and report our findings based on a single set of measure for all tasks. In this year’s participation, we evaluate the performance of the standard language model that is more focused on a fixed number of relevant characters than on relevant paragraphs. Our findings are: 1) the simplest language model for document retrieval performs relatively well in the restricted focused task when using a fixed offset that is close to the average character distance from the beginning of a document to its main content; 2) a good result of document ranking does improve the performance of snippet retrieval; 3) stemming and stopword removal can further boost performance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Li, R.M., van der Weide, T.P.: Language Models for XML Element Retrieval. In: Proceedings of INEX (2009)
Zhai, C.X., Lafferty, J.: A Study of Smoothing Methods for Language Models Applied to Information Retrieval. ACM Trans. on Information Systems. 22(2), 179–214 (2004)
Schenkel, R., Suchanek, F.M., Kasneci, G.: YAWN: A Semantically Annotated Wikipedia XML Corpus. In: 12. GI-Fachtagung für Datenbanksysteme in Business, Technologie und Web, Aachen, Germany (March 2007)
Strohman, T., Metzler, D., Turtle, H., Croft, W.B.: Indri: A Language-model Based Search Engine for Complex Queries. In: Proceedings of ICIA (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, R., van der Weide, T. (2011). Extended Language Models for XML Element Retrieval. In: Geva, S., Kamps, J., Schenkel, R., Trotman, A. (eds) Comparative Evaluation of Focused Retrieval. INEX 2010. Lecture Notes in Computer Science, vol 6932. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23577-1_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-23577-1_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23576-4
Online ISBN: 978-3-642-23577-1
eBook Packages: Computer ScienceComputer Science (R0)