Paper Info
Title
Model Fusion Experiments for the Cross Language Speech Retrieval Task at CLEF 2007.
Abstract
This paper presents the participation of the University of Ottawa group in the Cross-Language Speech Retrieval (CL-SR) task at CLEF 2007. We present the results of the submitted runs for the English collection. We have used two Information Retrieval systems in our experiments: SMART and Terrier, with two query expansion techniques: one based on a thesaurus and the second one based on blind relevant feedback. We proposed two novel data fusion methods for merging the results of several models (retrieval schemes available in SMART and Terrier). Our experiments showed that the combination of query expansion methods and data fusion methods helps to improve the retrieval performance. We also present cross-language experiments, where the queries are automatically translated by combining the results of several online machine translation tools. Experiments on indexing the manual summaries and keywords gave the best retrieval results.
Year
Venue
Keywords
2007
CLEF (Working Notes)
data fusion,retrieval models,query expansion
Field
DocType
Citations 
Language speech,Query expansion,Computer science,Machine translation,Search engine indexing,Fusion,Sensor fusion,Natural language processing,Artificial intelligence,Merge (version control),Clef
Conference
2
PageRank 
References 
Authors
0.39
11
2
Name
Order
Citations
PageRank
Muath Alzghool1264.64
Diana Inkpen2105987.92