Rada Mihalcea

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Rada Mihalcea is an author.


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Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Sense clustering using Wikipedia International Conference Recent Advances in Natural Language Processing, RANLP English 2013 In this paper, we propose a novel method for generating a coarse-grained sense inventory from Wikipedia using a machine learning framework. Structural and content-based features are employed to induce clusters of articles representative of a word sense. Additionally, multilingual features are shown to improve the clustering accuracy, especially for languages that are less comprehensive than English. We show the effectiveness of our clustering methodology by testing it against both manually and automatically annotated datasets. 0 0
Improving query expansion for image retrieval via saliency and picturability Lecture Notes in Computer Science English 2011 In this paper, we present a Wikipedia-based approach to query expansion for the task of image retrieval, by combining salient encyclopaedic concepts with the picturability of words. Our model generates the expanded query terms in a definite two-stage process instead of multiple iterative passes, requires no manual feedback, and is completely unsupervised. Preliminary results show that our proposed model is effective in a comparative study on the ImageCLEF 2010 Wikipedia dataset. 0 0
AAAI 2008 workshop reports AI Magazine English 2009 AAAI was pleased to present the AAAI-08 Workshop Program, held Sunday and Monday, July 13-14, in Chicago, Illinois, USA. The program included the following 15 workshops: Advancements in POMDP Solvers; AI Education Workshop Colloquium; Coordination, Organizations, Institutions, and Norms in Agent Systems, Enhanced Messaging; Human Implications of Human-Robot Interaction; Intelligent Techniques for Web Personalization and Recommender Systems; Metareasoning: Thinking about Thinking; Multidisciplinary Workshop on Advances in Preference Handling; Search in Artificial Intelligence and Robotics; Spatial and Temporal Reasoning; Trading Agent Design and Analysis; Transfer Learning for Complex Tasks; What Went Wrong and Why: Lessons from AI Research and Applications; and Wikipedia and Artificial Intelligence: An Evolving Synergy. Copyright © 2009, Association for the Advancement of Artificial Intelligence. All rights reserved. 0 0
Cross-lingual semantic relatedness using encyclopedic knowledge EMNLP 2009 - Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: A Meeting of SIGDAT, a Special Interest Group of ACL, Held in Conjunction with ACL-IJCNLP 2009 English 2009 In this paper, we address the task of crosslingual semantic relatedness. We introduce a method that relies on the information extracted from Wikipedia, by exploiting the interlanguage links available between Wikipedia versions in multiple languages. Through experiments performed on several language pairs, we show that the method performs well, with a performance comparable to monolingual measures of relatedness. 0 0
Topic Identification Using Wikipedia Graph Centrality English 2009 0 0
Using Encyclopedic Knowledge for Automatic Topic Identification English 2009 0 0
Linking Educational Materials to Encyclopedic Knowledge English 2007 0 0
Using Wikipedia for Automatic Word Sense Disambiguation English 2007 0 0
Using Wikipedia for automatic word sense disambiguation NAACL HLT 2007 - Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics, Proceedings of the Main Conference English 2007 This paper describes a method for generating sense-tagged data using Wikipedia as a source of sense annotations. Through word sense disambiguation experiments, we show that the Wikipedia-based sense annotations are reliable and can be used to construct accurate sense classifiers. 0 0
Wikify! Linking documents to encyclopedic knowledge Keyword extraction
Semantic annotation
Word sense disambiguation
International Conference on Information and Knowledge Management, Proceedings English 2007 This paper introduces the use of Wikipedia as a resource for automatic keyword extraction and word sense disambiguation, and shows how this online encyclopedia can be used to achieve state-of-the-art results on both these tasks. The paper also shows how the two methods can be combined into a system able to automatically enrich a text with links to encyclopedic knowledge. Given an input document, the system identifies the important concepts in the text and automatically links these concepts to the corresponding Wikipedia pages. Evaluations of the system show that the automatic annotations are reliable and hardly distinguishable from manual annotations. Copyright 2007 ACM. 0 0