Document Retrieval Using Entity Based Language Models
We address the ad hoc document retrieval task by devising novel types of entity based language models. The models utilize information about single terms in the query and documents as well as term sequences marked as entities by some entity linking tool. The key principle of the language models is accounting, simultaneously, for the uncertainty inherent in the entity markup process and the balance between using entity based and term based information. Empirical evaluation demonstrates the merits of using the language models for retrieval. For example, the performance transcends that of a state of the art term proximity method. We also show that the language models can be effectively used for cluster based document retrieval and query expansion.
SIGIR