Year: 2016

“Exploiting Entity Linking in Queries for Entity Retrieval,” an upcoming ICTIR 2016 paper by Faegheh Hasibi, Svein Erik Bratsberg, and myself is available online now, along with the source code.

The premise of entity retrieval is to better answer search queries by returning specific entities instead of documents. Many queries mention particular entities; recognizing and linking them to the corresponding entry in a knowledge base is known as the task of entity linking in queries. In this paper we make a first attempt at bringing together these two, i.e., leveraging entity annotations of queries in the entity retrieval model. We introduce a new probabilistic component and show how it can be applied on top of any term-based entity retrieval model that can be emulated in the Markov Random Field framework, including language models, sequential dependence models, as well as their fielded variations. Using a standard entity retrieval test collection, we show that our extension brings consistent improvements over all baseline methods, includ- ing the current state-of-the-art. We further show that our extension is robust against parameter settings.

Update (16/09): Our paper received the Best Paper Honorable Mention Award at the conference. So it is definitely worth checking out ;)