Distributional Semantic Models (ESSLLI 2009)

Start page – Schedule – Downloads & Links – Bibliography

• Curran, J.R. (2004), From Distributional to Semantic Similarity, PhD thesis, University of Edinburgh
• Harris, Z.S. (1954), “Distributional structure”, Word, 10/2-3, 1954: 146-62
  [reprinted in Harris, Z.S., Papers in Structural and Transformational Linguistics, Dordrecht, Reidel: 775-794]
• Landauer, Th. K. & S.T. Dumais (1997), “A Solution to Plato's problem: the latent semantic analysis theory of acquisition, induction and representation of knowledge”, Psychological Review, 104/2: 211-240
• Landauer, Th.K., McNamara, D.S., Dennis S., & W. Kintsch (eds.) (2007), Handbook of Latent Semantic Analysis, Mahwah NJ, Lawrence Erlbaum
• Lenci, A. (2008), “ Distributional semantics in linguistic and cognitive research”, in Lenci A. (ed.), From context to meaning: Distributional models of the lexicon in linguistics and cognitive science, special issue of the Italian Journal of Linguistics, 20/1: 1-30
• Lin, D. (1998), “Automatic retrieval and clustering of similar words”, Proceedings of ACL 1998:768–774
• Lund, K. & C. Burgess (1996), “Producing high-dimensional semantic spaces from lexical cooccurrence”, Behaviour Research Methods, 28: 203–208
• Miller G. A. & W.G. Charles (1991), “Contextual correlates of semantic similarity”, Language and Cognitive Processes, 6: 1-28
• Padó, S. & M. Lapata (2007), “Dependency-based construction of semantic space models”, Computational Linguistics, 33/2:161-199
• Sahlgren, M. (2006), The Word Space Model, Ph.D. dissertation, Stockholm University, Stockholm
• Schütze, H. (1992), “Dimensions of meaning”, in Proceedings of Supercomputing ’92, IEEE Computer Society Press: 787–796
• Schütze, H. (1998), “Automatic word sense discrimination”, Computational Linguistics 24/1: 97–123
• Turney, P. (2006), “Similarity of semantic relations”, Computational Linguistics, 32(3): 379–416
• Widdows, D. (2004), Geometry and Meaning, Stanford, CA, CSLI

• Baroni, M. & A. Lenci (2009), “One semantic memory, many semantic tasks” in Proceedings of the EACL Workshop on GEometrical Models of Natural Language Semantics, Athens, 31st March
• Erk, K. (2009), “Supporting inferences in semantic space: representing words as regions”, in Proceedings of IWCS 2009
• Erk, K. & S. Padó (2008), “A Structured Vector Space Model for Word Meaning in Context”, in Proceedings of EMNLP 2008
• Hare, J., Samangooei, S., Lewis, P. & M. Nixon (2008), “Semantic spaces revisited: investigating the performance of auto-annotation and semantic retrieval using semantic spaces”, in CIVR '08: The 2008 international conference on Content-based image and video retrieval, Niagara Falls
• Jones, M.N. & D.J.K. Mewhort (2007), “Representing word meaning and order information in a composite holographic lexicon”, Psychological Review, 114/1:1-37
• Mitchell, M. & M. Lapata (2008), “Vector-based models of semantic composition”, in Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics: 236-244
• Padó, S., Padó U. & K. Erk (2007), “Flexible, corpusbased modelling of human plausibility judgements”, in Proceedings EMNLP 2007: 400–409
• Plate, T. (2003), Holographic Reduced Representation, number 150 of CSLI Lecture Notes, CSLI Publications, Stanford, CA
• Rubinstein, H. & J.B. Goodenough (1965), “Contextual correlates of synonymy”, Computational Linguistics, 8: 627-633
• Griffiths, T.L., Steyvers, M. & J.B.T. Tenenbaum (2007), “Topics in Semantic Representation”, Psychological Review, 114(2): 211-244
• Turney, P. (2008), “A uniform approach to analogies, synonyms, antonyms and associations”, in Proceedings of COLING 2008: 905–912

• Andrews, M., Vigliocco, G. & D. Vinson (2009), “Integrating experiential and distributional data to learn semantic representations”, Psychological Review, 116/3
• Baroni M., Lenci A., & L. Onnis (2007), “ISA meets Lara: A fully incremental word space model for cognitively plausible simulations of semantic learning”, in Proceedings of the ACL Workshop on Cognitive Aspects of Language Acquisition: 49-56
• Barsalou, L.W., Santos, A., Simmons, W.K. & C.D. Wilson (2008), “Language and simulation in conceptual processing”, in De Vega, M., Glenberg, A.M. & A.C. Graesser (eds.), Symbols, Embodiment and Meaning, Oxford, Oxford University Press: 245-283
• Borovsky, A. & J.L. Elman (2006), “Language input and semantic categories: A relation between cognition and early word learning”, Journal of Child Language, 33: 759-790
• Bullinaria, J.A. & J.P. Levy (2007), “Extracting Semantic Representations from Word Co-occurrence Statistics: A Computational Study”, Behavior Research Methods, 39: 510-526
• Farkas, I. & P. Li (2001), “A self-organizing neural network model of the acquisition of word meaning”, in Proceedings of the 4th International Conference on Cognitive Modeling
• Glenberg, A.M. & D.A. Robertson (2000), “Symbol grounding and meaning: a comparison of high-dimensional and embodied theories of meaning”, Journal of Memory and Language, 43/3: 379-401
• Jones, M. N., Kintsch, W. & D.J.K. Mewhort (2006), “High dimensional semantic space accounts of priming”, Journal of memory and Language, 55: 534-552
• Kintsch, W. (2001), “Predication”, Cognitive Science, 25: 173-202
• Li, P., Burgess, C. & K. Lund (2000), “The acquisition of word meaning through global lexical co-occurrences”, in Proceedings of the 31st Child Language Research Forum: 167-178
• Mitchell T., Shinkareva S., Carlson A., Chang K., Malave V., Mason R. & M. Just (2008), "Predicting human brain activity associated with the meanings of nouns", Science, 320: 1191-1195
• Rogers, T.T., Lambon Ralph, M.A., Garrard, P., Bozeat, S., McClelland, J.L., Hodges, J.R., & K. Patterson (2004), “The structure and deterioration of semantic memory: A neuropsychological and computational investigation”, Psychological Review, 111/1: 205-235
• Shaoul, C. & C. Westbury (2006), "Word Frequency Effects in High-Dimensional Co-Occurrence Models: A New Approach", Behavior Research Methods, 38/2: 190–195