Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/103149
Title: Search results clustering without external resources
Authors: Staff, Chris
Azzopardi, Joel
Layfield, Colin
Mercieca, Dan
Keywords: Search engines
Latent semantic indexing
Natural language processing (Computer science)
Issue Date: 2015
Publisher: Institute of Electrical and Electronics Engineers
Citation: Staff, C., Azzopardi, J., Layfield, C., & Mercieca, D. (2015, September). Search results clustering without external resources. 26th International Workshop on Database and Expert Systems Applications (DEXA), Spain. 276-280.
Abstract: Our unsupervised Search Results Clustering (SRC) system partitions into clusters the top-n results returned by a search engine. We present the results of experiments with our SRC system that performs incremental clustering on document titles and snippets only and does not use external resources, yet which outperforms the best performers to date on the SemEval2013 Task 11 gold standard. We include Latent Semantic Analysis (LSA) as an optional step, using the snippets themselves as the background corpus. We demonstrate that better results are achieved by leaving the query terms out of the clustering process, and that currently, the version without LSA outperforms the version with LSA.
URI: https://www.um.edu.mt/library/oar/handle/123456789/103149
Appears in Collections:Scholarly Works - FacICTAI

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