Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Retrieving collocations from text: Xtract
Computational Linguistics - Special issue on using large corpora: I
Morphological rule induction for terminology acquistion
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Exploiting paraphrases in a Question Answering system
PARAPHRASE '03 Proceedings of the second international workshop on Paraphrasing - Volume 16
Complex structuring of term variants for Question Answering
MWE '03 Proceedings of the ACL 2003 workshop on Multiword expressions: analysis, acquisition and treatment - Volume 18
Text mining without document context
Information Processing and Management: an International Journal - Special issue: Informetrics
Multilingual term extraction from domain-specific corpora using morphological structure
EACL '06 Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations
Automatic acquisition of semantic relationships from morphological relatedness
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
A term normalization method for better performance of terminology construction
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Developing multilingual text mining workflows in UIMA and u-compare
NLDB'12 Proceedings of the 17th international conference on Applications of Natural Language Processing and Information Systems
A term normalization method for efficient knowledge acquisition through text processing
Multimedia Tools and Applications
| Hi-index | 0.00 |
After extracting terms from a corpus of titles and abstracts in English, syntactic variation relations are identified amongst them in order to detect research topics. Three types of syntactic variations were studied: permutation, expansion and substitution. These syntactic variations yield other relations of formal and conceptual nature. Basing on a distinction of the variation relations according to the grammatical function affected in a term - head or modifier - term variants are first clustered into connected components which are in turn clustered into classes. These classes relate two or more components through variations involving a change of head word, thus of topic. The graph obtained reveals the global organisation of research topics in the corpus. A clustering method has been built to compute such classes of research topics.