Document - When entities meet query recommender systems: semantic search shortcuts

2013

Conference article Open Access

When entities meet query recommender systems: semantic search shortcuts

Ceccarelli D., Gordea S., Lucchese C., Nardini F. M., Perego R.

Entity Query suggestion Diversity Relatedness E.m Data. MISCELLANEOUS 68P20

The Web of Data is growing in popularity and dimension, and entities are gaining importance in many research fields. In this paper, we explore the use of entities that can be extracted from a query log to enhance query recommendation. In particular, we use a large query log recorded by the Europeana portal, a central access point to the descriptions of more than 20 million cultural heritage objects, and we extend a state-of-the-art query recommendation algorithm to take into account the semantic information associated with the submitted queries. Our novel method generates highly related and diversified suggestions. We assess it by means of a new evaluation technique. The manually annotated dataset used for performance comparisons has been made available to the research community to favor the repeatability of the experiments.

Source: SAC '13 - 28th Annual ACM Symposium on Applied Computing, pp. 933–938, Coimbra, Portogallo, 18 - 22 marzo 2013

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@inproceedings{oai:it.cnr:prodotti:277742,
	title = {When entities meet query recommender systems: semantic search shortcuts},
	author = {Ceccarelli D. and Gordea S. and Lucchese C. and Nardini F.  M. and Perego R.},
	doi = {10.1145/2480362.2480540},
	booktitle = {SAC '13 - 28th Annual ACM Symposium on Applied Computing, pp. 933–938, Coimbra, Portogallo, 18 - 22 marzo 2013},
	year = {2013}
}