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Irina Chugur
Researcher at National University of Distance Education
Publications - 12
Citations - 860
Irina Chugur is an academic researcher from National University of Distance Education. The author has contributed to research in topics: WordNet & EuroWordNet. The author has an hindex of 7, co-authored 12 publications receiving 856 citations.
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Proceedings Article
Indexing with WordNet synsets can improve text retrieval.
TL;DR: In this article, the classical vector space model for text retrieval is shown to give better results (up to 29% better in their experiments) if WordNet synsets are chosen as the indexing space, instead of word forms.
Posted Content
Indexing with WordNet synsets can improve Text Retrieval
TL;DR: In this article, the classical vector space model for text retrieval is shown to give better results (up to 29% better in their experiments) if WordNet synsets are chosen as the indexing space, instead of word forms.
Book ChapterDOI
Overview of RepLab 2013: Evaluating Online Reputation Monitoring Systems
Enrique Amigó,Jorge Carrillo de Albornoz,Irina Chugur,Adolfo Corujo,Julio Gonzalo,Tamara Martín,Edgar Meij,Maarten de Rijke,Damiano Spina +8 more
TL;DR: This paper summarizes the goals, organization, and results of the second RepLab competitive evaluation campaign for Online Reputation Management Systems RepLab 2013, which consists of more than 140,000 tweets annotated by a group of trained annotators supervised and monitored by reputation experts.
Book ChapterDOI
Overview of RepLab 2014: Author Profiling and Reputation Dimensions for Online Reputation Management
Enrique Amigó,Jorge Carrillo-de-Albornoz,Irina Chugur,Adolfo Corujo,Julio Gonzalo,Edgar Meij,Maarten de Rijke,Damiano Spina +7 more
TL;DR: The organisation and results of RepLab 2014 are described, which focused on two new tasks: reputation dimensions classification and author profiling, which complement the aspects of reputation analysis studied in the previous campaigns.
Journal ArticleDOI
Using eurowordnet in a concept-based approach to cross-language text retrieval
TL;DR: An approach to cross-language text retrieval based on the EuroWordNet (EWN) multilingual semantic database, which turns term weighting and query/document matching into language-independent tasks.