When entities meet query recommender systems: semantic search shortcuts

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.