A Markov random field model for term dependencies
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Formal models for expert finding in enterprise corpora
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Linear feature-based models for information retrieval
Information Retrieval
Proximity-based document representation for named entity retrieval
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
A simple and efficient sampling method for estimating AP and NDCG
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Overview of the INEX 2007 Entity Ranking Track
Focused Access to XML Documents
L3S at INEX 2007: Query Expansion for Entity Ranking Using a Highly Accurate Ontology
Focused Access to XML Documents
Named entity recognition in query
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Overview of the INEX 2008 Entity Ranking Track
Advances in Focused Retrieval
Overview of the INEX 2009 entity ranking track
INEX'09 Proceedings of the Focused retrieval and evaluation, and 8th international conference on Initiative for the evaluation of XML retrieval
Combining term-based and category-based representations for entity search
INEX'09 Proceedings of the Focused retrieval and evaluation, and 8th international conference on Initiative for the evaluation of XML retrieval
Query modeling for entity search based on terms, categories, and examples
ACM Transactions on Information Systems (TOIS)
The cluster hypothesis for entity oriented search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Learning joint query interpretation and response ranking
Proceedings of the 22nd international conference on World Wide Web
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In this work we present a general model for entity ranking that is based on the Markov Random Field approach for modeling various types of dependencies between the query and the entity. We show that this model actually extends existing approaches for entity ranking while aggregating all pieces of relevance evidences in a unified way. We evaluated the performance of our model using the INEX datasets. Our results show that our ranking model significantly out-performs leading INEX systems in the tracks of 2007 and 2008, and is equivalent to the best results achieved in the 2009 track.