MORESQUE

MORESQUE (MORE Sense-tagged QUEries) is a dataset designed for evaluation of subtopic information retrieval. The dataset consists of 114 topics (i.e., queries), each with a set of subtopics and a list of 100 top-ranking documents.

Dataset

MORESQUE is designed as a complement for AMBIENT. We are releasing a package that contains four files:

topics.txt: contains topic ID and description
subTopics.txt: contains subtopic ID (formed by topic ID and subtopic number) and description
results.txt: contains result ID (formed by topic ID and search engine ranking of each result), URL, title, and snippet
STRel.txt contains subtopic ID (formed by topic ID and subtopic number) and result ID (formed by topic ID and search engine rank of result)

Downloads

MORESQUE dataset v1.0 (revision 24 February 2012).

References

When referring to the MORESQUE dataset, please cite the following paper:

Roberto Navigli, Giuseppe Crisafulli. Inducing Word Senses to Improve Web Search Result Clustering. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing (EMNLP 2010), MIT Stata Center, Massachusetts, USA, 9-11 October 2010, pp. 116-126.

Last update: 24 February 2012 by Roberto Navigli