منابع مشابه
Discovering filter keywords for company name disambiguation in twitter
A major problem in monitoring the online reputation of companies, brands, and other entities is that entity names are often ambiguous (apple may refer to the company, the fruit, the singer, etc.). The problem is particularly hard in microblogging services such as Twitter, where texts are very short and there is little context to disambiguate. In this paper we address the filtering task of deter...
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In this paper we describe the collaborative participation of UvA & UNED at RepLab 2013. We propose an active learning approach for the filtering subtask, using features based on the detected semantics in the tweet (using Entity Linking with Wikipedia), as well as tweetinherent features such as hashtags and usernames. The tweets manually inspected during the active learning process is at most 1%...
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The growth of digitization in the cultural heritage domain offers great possibilities to broaden the boundaries of historical research. With the ultimate aim of creating social networks of person names from news articles, we introduce a person name disambiguation method that exploits the relation between the ambiguity of a person name and the number of entities referred to by it. Modeled as a c...
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Using Twitter as an effective marketing tool has become a gold mine for companies interested in their online reputation. A quite significant research challenge related to the above issue is to disambiguate tweets with respect to company names. In fact, finding if a particular tweet is relevant or irrelevant to a company is an important task not satisfactorily solved yet; to address this issue i...
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ژورنال
عنوان ژورنال: Organic Process Research & Development
سال: 2002
ISSN: 1083-6160,1520-586X
DOI: 10.1021/op025541i