Intraconcept similarity and its implications for interconcept similarity
Similarity and analogical reasoning
CYC: a large-scale investment in knowledge infrastructure
Communications of the ACM
A model for standardization in the definition and form of associative, interconcept links
A model for standardization in the definition and form of associative, interconcept links
Computational Linguistics - Summarization
Expanding the Type Hierarchy with Nonlexical Concepts
AI '00 Proceedings of the 13th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Lexical cohesion computed by thesaural relations as an indicator of the structure of text
Computational Linguistics
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
Automatic Discovery of Part-Whole Relations
Computational Linguistics
Identifying semantic relations and functional properties of human verb associations
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Improving interaction with virtual globes through spatial thinking: helping users ask "why?"
Proceedings of the 13th international conference on Intelligent user interfaces
Learning semantic relatedness from term discrimination information
Expert Systems with Applications: An International Journal
Unsupervised recognition of literal and non-literal use of idiomatic expressions
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Comparing Wikipedia and German wordnet by evaluating semantic relatedness on multiple datasets
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
Using wiktionary for computing semantic relatedness
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Using readers to identify lexical cohesive structures in texts
ACLstudent '05 Proceedings of the ACL Student Research Workshop
Automatically creating datasets for measures of semantic relatedness
LD '06 Proceedings of the Workshop on Linguistic Distances
Web-based annotation of anaphoric relations and lexical chains
LAW '07 Proceedings of the Linguistic Annotation Workshop
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Wisdom of crowds versus wisdom of linguists – measuring the semantic relatedness of words
Natural Language Engineering
From frequency to meaning: vector space models of semantics
Journal of Artificial Intelligence Research
Bootstrapping location relations from text
Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem - Volume 47
Fast supervised feature extraction by term discrimination information pooling
Proceedings of the 20th ACM international conference on Information and knowledge management
A new approach to use concepts definitions for semantic relatedness measurement
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Clustering and understanding documents via discrimination information maximization
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Computing text semantic relatedness using the contents and links of a hypertext encyclopedia
Artificial Intelligence
Language Resources and Evaluation
SALDO: a touch of yin to WordNet's yang
Language Resources and Evaluation
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NLP methods and applications need to take account not only of "classical" lexical relations, as found in WordNet, but the less-structural, more context-dependent "non-classical" relations that readers intuit in text. In a reader-based study of lexical relations in text, most were found to be of the latter type. The relationships themselves are analyzed, and consequences for NLP are discussed.