Search Results Clustering without External Resources

摘要

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 SemEval-2013 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.