This site has been permanently archived. This is a static copy provided by the University of Southampton.
--- abstract: 'This paper presents a computational model of the incremental construction of an associative network from a corpus. It is aimed at modeling the development of the human semantic memory. It is not based on a vector representation, which does not well reproduce the asymmetrical property of word similarity, but rather on a network representation. Compared to Latent Semantic Analysis, it is incremental which is cognitively more plausible. It is also an attempt to take into account higher-order co-occurrences in the construction of word similarities. This model was compared to children association norms. A good correlation as well as a similar gradient of similarity were found.' altloc: - http://www.upmf-grenoble.fr/sciedu/blemaire/cogsci04_2.pdf chapter: ~ commentary: ~ commref: ~ confdates: 'August 5-7, 2004' conference: 26th Annual Meeting of the Cognitive Science Society confloc: Chicago contact_email: ~ creators_id: [] creators_name: - family: Lemaire given: Beno�t honourific: '' lineage: '' - family: Denhi�re given: Guy honourific: '' lineage: '' date: 2004 date_type: published datestamp: 2004-08-25 department: ~ dir: disk0/00/00/37/79 edit_lock_since: ~ edit_lock_until: ~ edit_lock_user: ~ editors_id: [] editors_name: - family: Forbus given: Kenneth honourific: '' lineage: '' - family: Gentner given: Dedre honourific: '' lineage: '' - family: Regier given: Terry honourific: '' lineage: '' eprint_status: archive eprintid: 3779 fileinfo: /style/images/fileicons/application_pdf.png;/3779/1/cogsci04_2.pdf full_text_status: public importid: ~ institution: ~ isbn: ~ ispublished: pub issn: ~ item_issues_comment: [] item_issues_count: 0 item_issues_description: [] item_issues_id: [] item_issues_reported_by: [] item_issues_resolved_by: [] item_issues_status: [] item_issues_timestamp: [] item_issues_type: [] keywords: 'associative network, corpus, semantic memory, LSA, Latent Semantic Analysis' lastmod: 2011-03-11 08:55:40 latitude: ~ longitude: ~ metadata_visibility: show note: ~ number: ~ pagerange: 825-830 pubdom: FALSE publication: ~ publisher: Lawrence Erlbaum Associates refereed: TRUE referencetext: |- Burgess, C. (1998). From simple associations to the building blocks of language: modeling meaning in memory with the HAL model. Behavior Research Methods, Instruments, & Computers, 30, 188-198. Burgess, C., Livesay, K & Lund, K. (1998). Explorations in context space: words, sentences, discourse. Discourse Processes, 25, 211-257. de la Haye, F. (2003). Normes d'associations verbales chez des enfants de 9, 10 et 11 ans et des adultes. L'Ann�e Psychologique, 103, 109-130. Edmonds, P. (1997). Choosing the word most typical in context using a lexical co-occurrence network. Meeting of the Association for Computational Linguistics, 507-509. Foltz, P. W. (1996). Latent Semantic Analysis for text-based research. Behavior Research Methods, Instruments and Computers, 28-2, 197-202. Frank, S.L., Koppen, M., Noordman, L.G.M. & Vonk, W. (2003). Modeling knowledge-based inferences in story comprehension. Cognitive Science 27(6), 875-910. Glenberg, A. M. & Robertson, D. A., (2000). Grounding symbols and computing meaning: a supplement to Glenberg & Robertson. Journal of Memory and Language, 43, 379-401. Kintsch, W. (1998). Comprehension: A Paradigm for Cognition. Cambridge University Press. Kontostathis, A. & Pottenger, W.M. (2002). Detecting patterns in the LSI term-term matrix. Workshop on the Foundation of Data Mining and Discovery, IEEE International Conference on Data Mining. Landauer T.K. (2002). On the computational basis of learning and cognition: Arguments from LSA. In N. Ross (Ed.), The psychology of Learning and Motivation, 41, 43-84. Landauer, T. K. & Dumais, S. T. (1997). A solution to Plato's problem : the Latent Semantic Analysis theory of acquisition, induction and representation of knowledge. Psychological Review, 104, 211-240. Lemaire, B. & Denhi�re, G. (submitted). Effects of higher-order co-occurrences on semantic similarity of words. Levy, J.P., Bullinaria, J.A. & Patel, M. (1998). Explorations in the derivation of semantic representations from word co-occurrence statistics. South Pacific Journal of Psychology, 10, 99-111. Levy, J.P., Bullinaria, J.A. (2001). Learning lexical properties from word usage patterns: which context words should be used? In R. French & J.P. Sougne (Eds)Connectionist Models of Learning, Development and Evolution: Proceedings of the Sixth Neural Computation and Psychology Workshop, 273-282. London:Springer. Lowe, W. & McDonald, S. (2000). The direct route: mediated priming in semantic space. In Gernsbacher, M. A. and Derry, S. D., editors, Proceedings of the 22nd Annual Meeting of the Cognitive Science Society, 675-680, New Jersey. Lawrence Erlbaum Associates. Prince, V. & Lafourcade, M. (2003). Mixing semantic networks and conceptual vectors: the case of hyperonymy. In Proc. of ICCI-2003 (2nd IEEE International Conference on Cognitive Informatics), South Bank University, London, UK, August 18 - 20, 121-128. Sahlgren, M. (2001). Vector-based semantic analysis: representing word meaning based on random labels. Semantic Knowledge Acquisition and Categorisation Workshop at ESSLLI '01, Helsinki, Finland. Sahlgren, M. (2002). Towards a flexible model of word meaning. AAAI Spring Symposium 2002. March 25-27, Stanford University, Palo Alto. Spence, D.P. & Owens K.C. (1990). Lexical co-occurrence and association strength. Journal of Psycholinguistic Research 19, 317-330. Steyvers, M., Shiffrin R.M., & Nelson, D.L. (in press). Word Association Spaces for predicting semantic similarity effects in episodic memory. In A. Healy (Ed.), Cognitive Psychology and its Applications: Festschrift in Honor of Lyle Bourne, Walter Kintsch, and Thomas Landauer. Washington DC: American Psychological Association. Steyvers, M., & Tenenbaum, J. (submitted). Graph theoretic analyses of semantic networks: small worlds in semantic networks. Tversky, A. (1977). Features of similarity. Psychological Review, 84(4), 327-352. Wolfe, M. B. W., Schreiner, M. E., Rehder, B., Laham, D., Foltz, P. W., Kintsch & W., Landauer, T. K. (1998).Learning from text: Matching readers and texts by Latent Semantic Analysis. Discourse Processes, 25, 309-336. relation_type: [] relation_uri: [] reportno: ~ rev_number: 12 series: ~ source: ~ status_changed: 2007-09-12 16:53:26 subjects: - comp-sci-stat-model - comp-sci-mach-learn - psy-ling succeeds: ~ suggestions: ~ sword_depositor: ~ sword_slug: ~ thesistype: ~ title: Incremental Construction of an Associative Network from a Corpus type: confpaper userid: 4300 volume: ~