The structure-mapping engine: algorithm and examples
Artificial Intelligence
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Mining Sequential Patterns by Pattern-Growth: The PrefixSpan Approach
IEEE Transactions on Knowledge and Data Engineering
Learning surface text patterns for a Question Answering system
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Corpus-based Learning of Analogies and Semantic Relations
Machine Learning
Similarity of Semantic Relations
Computational Linguistics
Expressing implicit semantic relations without supervision
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
The competence of sub-optimal theories of structure mapping on hard analogies
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Measuring semantic similarity by latent relational analysis
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Real time extraction of related terms by bi-directional lexico-syntactic patterns from the web
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication
Measuring the similarity between implicit semantic relations from the web
Proceedings of the 18th international conference on World wide web
Query by analogical example: relational search using web search engine indices
Proceedings of the 18th ACM conference on Information and knowledge management
Text relatedness based on a word thesaurus
Journal of Artificial Intelligence Research
Exploiting macro and micro relations toward web intelligence
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Improving relational similarity measurement using symmetries in proportional word analogies
Information Processing and Management: an International Journal
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Measuring relational similarity between words is important in numerous natural language processing tasks such as solving analogy questions and classifying noun-modifier relations. We propose a method to measure the similarity between semantic relations that hold between two pairs of words using a web search engine. First, each pair of words is represented by a vector of automatically extracted lexical patterns. Then a Support Vector Machine is trained to recognize word pairs with similar semantic relations. We evaluate the proposed method on SAT multiple-choice word-analogy questions. The proposed method achieves a score of 40% which is comparable with relational similarity measures which use manually created resources such as WordNet. The proposed method significantly reduces the time taken by previously proposed computationally intensive methods, such as latent relational analysis, to process 374 analogy questions from 8 days to less than 6 hours.