@inproceedings{180575bbc5c54c46bad81f0864b3d033,
title = "Entity-based retrieval",
abstract = "We address the core challenge of the entity retrieval task: ranking entities in response to a query by their presumed relevance to the information need that the query represents. As an initial research direction we explored two models for entity ranking that were evaluated using the INEX entity ranking dataset and which posted promising performance. A natural future direction to explore is how to generalize these models to address various types of information needs that are associated with entities.",
keywords = "Cluster ranking, Entity retrieval, Markov random fields",
author = "Hadas Raviv",
year = "2014",
doi = "10.1145/2600428.2610378",
language = "English (US)",
isbn = "9781450322591",
series = "SIGIR 2014 - Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval",
publisher = "Association for Computing Machinery",
pages = "1277",
booktitle = "SIGIR 2014 - Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval",
note = "37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2014 ; Conference date: 06-07-2014 Through 11-07-2014",
}