TAILIEUCHUNG - Báo cáo khoa học: "Named Entity Disambiguation in Streaming Data"

The named entity disambiguation task is to resolve the many-to-many correspondence between ambiguous names and the unique realworld entity. This task can be modeled as a classification problem, provided that positive and negative examples are available for learning binary classifiers. High-quality senseannotated data, however, are hard to be obtained in streaming environments, since the training corpus would have to be constantly updated in order to accomodate the fresh data coming on the stream. . | Named Entity Disambiguation in Streaming Data Alexandre Davis1 Adriano Veloso1 Altigran S. da Silva2 Wagner Meira Alberto H. F. Laender1 1Computer Science Dept. Federal University of Minas Gerais 2Computer Science Dept. Federal University of Amazonas agdavis adrianov meira laender @ alti@ Abstract The named entity disambiguation task is to resolve the many-to-many correspondence between ambiguous names and the unique real-world entity. This task can be modeled as a classification problem provided that positive and negative examples are available for learning binary classifiers. High-quality sense-annotated data however are hard to be obtained in streaming environments since the training corpus would have to be constantly updated in order to accomodate the fresh data coming on the stream. On the other hand few positive examples plus large amounts of unlabeled data may be easily acquired. Producing binary classifiers directly from this data however leads to poor disambiguation performance. Thus we propose to enhance the quality of the classifiers using finer-grained variations of the well-known ExpectationMaximization EM algorithm. We conducted a systematic evaluation using Twitter streaming data and the results show that our classifiers are extremely effective providing improvements ranging from 1 to 20 when compared to the current state-of-the-art biased SVMs being more than 120 times faster. 1 Introduction Human language is not exact. For instance an entity1 may be referred by multiple names . polysemy and also the same name may refer to different entities depending on the surrounding context . 1The term entity refers to anything that has a distinct separate materialized or not existence. 815 homonymy . The task of named entity disambiguation is to identify which names refer to the same entity in a textual collection Sarmento et al. 2009 Yosef et al. 2011 Hoffart et al. 2011 . The emergence of new communication technologies .

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