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• 858 creator prithviraj-sen.
• 858 type InProceedings.
• 858 label "Context-Aware Topic Models for Entity Disambiguation".
• 858 sameAs 858.
• 858 abstract "A crucial step in adding structure to unstructured data is to identify references to entities and disambiguate them. Such disambiguated references can help enhance readability and draw similarities across different pieces of running text in an automated fashion. Previous research has tackled this problem by first forming a catalog of entities from a knowledge base such as Wikipedia and then using this catalog subsequently to disambiguate references in unseen text. However, most of the previously proposed models either do not use all text in the knowledge base thus potentially missing out on discriminative features or do not exploit word-entity proximity to learn high-quality catalogs. In this work, we propose topic models that keep track of the context of every word in the knowledge base so that entities appearing in the same context are more likely to be associated with the word. Thus, our topic models utilize all text present in the knowledge base and help learn high-quality, discerning catalogs. Our models also learn groups of co-occurring entities from the knowledge base thus allowing us to perform collective disambiguation. Unlike most previous topic models, our models are non-parametric and do not require the user to specify how many groups exist in the knowledge base. In experiments performed on an extract of Wikipedia containing almost 60,000 references, our models outperform SVM-based baselines by as much as 18\% in terms of disambiguation accuracy translating to an increment of almost 11,000 correctly disambiguated references.".
• 858 hasAuthorList authorList.
• 858 isPartOf proceedings.
• 858 keyword "Entity disambiguation".
• 858 keyword "Structured data".
• 858 keyword "Topic models".
• 858 title "Context-Aware Topic Models for Entity Disambiguation".