Distributional Semantic Models (ESSLLI 2009)

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• 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
• 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, U., Padó S. & K. Erk (2007), "Flexible, corpusbased modelling of human plausibility judgements"
in Proceedings EMNLP 2007: 400–409

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

JonesItalic Text, 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