Identifying the target types of entity-bearing queries can help improve retrieval performance as well as the overall search experience. In this work, we address the problem of automatically detecting the target types of a query with respect to a type taxonomy. We propose a supervised learning approach with a rich variety of features. Using a purpose-built test collection, we show that our approach outperforms existing methods by a remarkable margin. This is an extended version of the article published with the same title in the Proceedings of SIGIR'17.
@article{arxiv.1705.06056,
title = {Target Type Identification for Entity-Bearing Queries},
author = {Darío Garigliotti and Faegheh Hasibi and Krisztian Balog},
journal= {arXiv preprint arXiv:1705.06056},
year = {2017}
}