EDIUM: Improving Entity Disambiguation via User Modeling.

Entity Disambiguation is the task of associating entity name mentions in text to the correct referent entities in the knowledge base, with the goal of understanding and extracting useful information from the document. Entity disambiguation is a critical component of systems designed to harness information shared by users on microblogging sites like Twitter. However, noise and lack of context in tweets makes disambiguation a difficult task. In this paper, we describe an E ntity Di sambiguation system, EDIUM , which uses U ser interest M odels to disambiguate the entities in the user's tweets. Our system jointly models the user's interest scores and the context disambiguation scores, thus compensating the sparse context in the tweets for a given user. We evaluated the system's entity linking capabilities on tweets from multiple users and showed that improvement can be achieved by combining the user models and the context based models.