Word association norms, mutual information, and lexicography
Computational Linguistics
Use of syntactic context to produce term association lists for text retrieval
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Conceptual Information Retrieval: A Case Study in Adaptive Partial Parsing
Conceptual Information Retrieval: A Case Study in Adaptive Partial Parsing
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Corpus-based learning of semantic relations by the ILP system, Asium
Learning language in logic
EKAW '99 Proceedings of the 11th European Workshop on Knowledge Acquisition, Modeling and Management
Robustness beyond shallowness: incremental deep parsing
Natural Language Engineering
Improving domain ontologies by mining semantics from text
APCCM '04 Proceedings of the first Asian-Pacific conference on Conceptual modelling - Volume 31
Reformulation of queries using similarity thesauri
Information Processing and Management: an International Journal
Automatic thesaurus construction
ACSC '08 Proceedings of the thirty-first Australasian conference on Computer science - Volume 74
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Reformulation of queries using similarity thesauri
Information Processing and Management: an International Journal
A case-based approach to knowledge acquisition for domain-specific sentence analysis
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Journal of Biomedical Informatics
A word at a time: computing word relatedness using temporal semantic analysis
Proceedings of the 20th international conference on World wide web
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For a very long time, it has been considered that the only way of automatically extracting similar groups of words from a text collection for which no semantic information exists is to use document co-occurrence data. But, with robust syntactic parsers that are becoming more frequently available, syntactically recognizable phenomena about word usage can be confidently noted in large collections of texts. We present here a new system called SEXTANT which uses these parsers and the finer-grained contexts they produce to judge word similarity.