Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Wikify!: linking documents to encyclopedic knowledge
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Context and Keyword Extraction in Plain Text Using a Graph Representation
SITIS '08 Proceedings of the 2008 IEEE International Conference on Signal Image Technology and Internet Based Systems
Using encyclopedic knowledge for automatic topic identification
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
WikiRelate! computing semantic relatedness using wikipedia
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Topic identification using Wikipedia graph centrality
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Word Sense Disambiguation Based on Wikipedia Link Structure
ICSC '09 Proceedings of the 2009 IEEE International Conference on Semantic Computing
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This paper presents an indexing support system that suggests for librarians a set of topics and keywords relevant to a pedagogical document. Our method of document indexing uses the Wikipedia category network as a conceptual taxonomy. A directed acyclic graph is built for each document by mapping terms (one or more words) to a concept in the Wikipedia category network. Properties of the graph are used to weight these concepts. This allows the system to extract so called important concepts from the graph and to disambiguate terms of the document. According to these concepts, topics and keywords are proposed. This method has been evaluated by the librarians on a corpus of french pedagogical documents.