закладки (спрятать)4
- Measuring the similarity between semantic relations that hold among entities is an important and necessary step in various Web related tasks such as relation extraction, information retrieval and analogy detection. For example, consider the case in which a person knows a pair of entities (e.g. Google, YouTube), between which a partic- ular relation holds (e.g. acquisition). The person is interested in retrieving other such pairs with similar relations (e.g. Microsoft, Powerset). Existing keyword-based search engines cannot be ap- plied directly in this case because, in keyword-based search, the goal is to retrieve documents that are relevant to the words used in a query – not necessarily to the relations implied by a pair of words. We propose a relational similarity measure, using a Web search en- gine, to compute the similarity between semantic relations implied by two pairs of words. Our method has three components: repre- senting the various semantic relations that exist between a pair of words using automatically extracted lexical patterns, clustering the extracted lexical patterns to identify the different patterns that ex- press a particular semantic relation, and measuring the similarity between semantic relations using a metric learning approach. We evaluate the proposed method in two tasks: classifying semantic relations between named entities, and solving word-analogy ques- tions. The proposed method outperforms all baselines in a relation classification task with a statistically significant average precision score of 0.74. Moreover, it reduces the time taken by Latent Relational Analysis to process 374 word-analogy questions from 9 days to less than 6 hours, with an SAT score of 51%.
публикации (спрятать)15
- Journal of Applied Social Psychology, 37 (9): 2097-2129 (2007)
- INSEAD Business School Research Paper No. 2008/56/MKT/ISSRC, (апреля 2008)
- Behavior Research Methods, 40 (1): 213-231 (2008)
- ACM Transactions on Computer-Human Interaction, (2000)
- (2008)Proc. of the Third Int. Conference on Concept Mapping Tallinn, Estonia & Helsinki, Finland 2008 http://cmc.ihmc.us/cmc2008/cmc2008Program.html.
- International Journal on Semantic Web and Information Systems (IJSWIS), 4 (4): 56--84 (2008)
- PNAS, 101 (11): 3747--3752 (марта 2004)
- International Journal of Computer-Supported Collaborative Learning, 3 (2): 105--122 (июня 2008)doi=10.1007/s11412-007-9035-z.
- AVI '06: Proceedings of the working conference on Advanced visual interfaces, стр. 457--462. New York, NY, USA, ACM Press, (2006)
- Psychological Science, 2 (6): 396-408 (1991)
- Lawrence Erlbaum associates, Mahwah, New Jersey, (1998)
- CIKM '03: Proceedings of the twelfth international conference on Information and knowledge management, стр. 556--559. New York, NY, USA, ACM, (2003)
- FLAIRS'09: Proceedings of the 22th International Florida Artificial Intelligence Research Society Conference, стр. 384-389. AAAI Press, (2009)
- Proceedings of the International Conference of the Learning Sciences 2008(Bd. 2, S. 99-106). Utrecht, The Netherlands: International Society of the Learning Sciences, стр. 99-106. (2008)
- Inf. Process. Manage., 36 (4): 585-605 (2000)
