Knowledge lean word-sense disambiguation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Ontology Learning and Its Application to Automated Terminology Translation
IEEE Intelligent Systems
The interaction of knowledge sources in word sense disambiguation
Computational Linguistics
Introduction to the special issue on word sense disambiguation: the state of the art
Computational Linguistics - Special issue on word sense disambiguation
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
New Techniques for Disambiguation in Natural Language and Their Application to Biological Text
The Journal of Machine Learning Research
Discovering corpus-specific word senses
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
Structural Semantic Interconnections: A Knowledge-Based Approach to Word Sense Disambiguation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Resolving abbreviations to their senses in Medline
Bioinformatics
Journal of the American Society for Information Science and Technology
Word Sense Disambiguation: Algorithms and Applications (Text, Speech and Language Technology)
Word Sense Disambiguation: Algorithms and Applications (Text, Speech and Language Technology)
Clustering large software systems at multiple layers
Information and Software Technology
Hierarchical density-based clustering of categorical data and a simplification
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Semantic techniques for the web
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With more and more genomes being sequenced, a lot of effort isdevoted to their annotation with terms from controlled vocabulariessuch as the GeneOntology. Manual annotation based on relevantliterature is tedious, but automation of this process is difficult.One particularly challenging problem is word sense disambiguation.Terms such as 'development' can refer to developmental biology orto the more general sense. Here, we present two approaches toaddress this problem by using term co-occurrences and documentclustering. To evaluate our method we defined a corpus of 331documents on development and developmental biology. Termco-occurrence analysis achieves an F-measure of 77%. Additionally,applying document clustering improves precision to 82%. We appliedthe same approach to disambiguate 'nucleus', 'transport', and'spindle', and we achieved consistent results. Thus, our method isa viable approach towards the automation of literature-based genomeannotation.