LSA as a Theory of Meaning

Handbook of Latent Semantic Analysis

Volumn , Issue , 2007, Pages 3-34

  Landauer, Thomas K ^a  

^a Pearson Knowledge Technologies   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85145516455     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4324/9780203936399-5     Document Type: Chapter

References (58)

1. Barsalou, L. (1999). Perceptual symbol systems. Behavioral and Brain Sciences, 22, 577-660.
2. Bartlett, F. C. (1932). Remembering. Cambridge, England:Cambridge University Press.
3. Berry, M.W. (1992). Large scale singular value computations. International Journal of Supercomputer Applications, 6(1), 13-49.
4. Berry, M.W., Dumais, S. T., and O’Brien, G.W. (1995). Using linear algebra for intelligent information retrieval. SIAM: Review, 37(4), 573-595.
5. Bickerton, D. (1995). Language and human behavior. Seattle, WA: University ofWashington Press.
6. Bloom, P. (2000).Howchildren learn the meaning of words. Cambridge, MA:MITPress.
7. Chomsky, N. (1991a). Linguistics and adjacent fields: Apersonal view. In A. Kasher (Ed.), The Chomskyan turn (pp. 3-25). Oxford, England: Blackwell.
8. Chomsky, N. (1991b). Linguistics and cognitive science: Problems and mysteries. In A. Kasher (Ed.), TheChomskyan turn (pp. 26-53).Oxford, England: Basil Blackwell.
9. Deerwester, S., Dumais, S. T., Furnas, G.W., Landauer, T. K., andHarshman, R. (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6), 391-407.
10. Dennis, S. (2005). A memory-based theory of verbal cognition. Cognitive Science, 29(2), 145-193.
11. Dumais, S. T. (1991). Improving the retrieval of information from external sources. Behavior Research Methods, Instruments and Computers, 23(2), 229-236.
12. Dumais, S.T., Landauer, T. K., andLittman, M.L. (1996). Automatic cross-linguistic information retrieval using Latent Semantic Indexing. In SIGIR’96 -Workshop on Cross-Lingusitic Information Retrieval, (pp. 16-23).
13. Edelman, S. (1998). Representation is representation of similarity. Behavioral and Brain Sciences, 21, 449-498.
14. Edelman, S. (1999). Representation and recognition in vision. Cambridge, MA:MIT Press.
15. Elvevåg, B., Foltz, P.W., Weinberger, D. R., andGoldberg, T. E. (2005). Quantifying incoherence in speech: An automated methodology and novel application to schizophrenia. Manuscript submitted for publication.
16. Erosheva, E., Fienberg, S., andLafferty, J. (2004). Mixed-membership models of scientific publications. Proceedings of the National Academy of Sciences, 97(2), 11885-11892.
17. Fellbaum, C. (1998). Introduction. In C. Fellbaum (Ed.), WordNet: Anelectronic lexical database (pp. 1-19). Cambridge, MA: MIT Press.
18. Fodor, J. A. (1987). Psychosemantics. Cambridge, MA: MIT/Bradford.
19. Foltz, P.W., Kintsch, W., and Landauer, T. K. (1998). Analysis of text coherence using latent semantic analysis. Discourse Processes, 25, 285-307.
20. Furnas, G.W., Landauer, T. K., Gomez, L. M., andDumais, S. T. (1987). The vocabulary problem in human-system communication. Communications of the Association for Computing Machinery, 30(11), 964-971.
21. Gleitman, L. R. (1990). The structural sources of verb meanings. Language Acquisition, 1, 3-55.
22. Glenberg, A. M., and Robertson, D. A. (2000). Symbol grounding and meaning: A comparison of high-dimensional and embodied theories of meaning. Journal of Memory and Language, 43, 379-401.
23. Gold, E. M. (1967). Language identification in the limit. Information and Control, 10, 447-474.
24. Goldstone, R. L., and Rogosky, B. J. (2002). Using relations within conceptual systems to translate across conceptual systems. Cognition, 84, 295-320.
25. Griffiths, T., andSteyvers, M. (2003). Topic dynamics in knowledge domains. Proceedings of the National Academy of Sciences, 101(Suppl. 1), 5228-5235.
26. Harnad, S. (1990). The symbol grounding problem. Physica D, 42, 335-346.
27. Hart, B., andRisley, T.R. (1995). Meaningful differences in the everyday experience of young American children. Baltimore: Paul H. Brookes.
28. Jackendoff, R. (1992). Languages of the mind. Cambridge: Bradford/MIT Press.
29. Keller, H. (1905). The story of my life. New York: Doubleday, Page and Company.
30. Kintsch, W. (1974). The representation of meaning in memory. Hillsdale, NJ: Lawrence Erlbaum Associates.
31. Kintsch, W. (1998). Comprehension: A paradigm for cognition. New York: Cambridge University Press.
32. Kintsch, W. (2000). Metaphor comprehension:Acomputational theory. Psychonomic Bulletin and Review, 7, 257-266.
33. Kintsch, W. (2001). Predication. Cognitive Science, 25, 173-202.
34. Laham, D. (1997). Latent semantic analysis approaches to categorization. In M. G. Shafto and P. Langley (Eds.), Proceedings of the 19th Annual Meeting of the Cognitive Science Society (p. 979). Mawhwah, NJ: Lawrence Erlbaum Associates.
35. Laham, D. (2000). Automated content assessment of text using latent semantic analysis to simulate human cognition. Unpublished doctoral dissertation, University of Colorado, Boulder.
36. Landau, B., and Gleitman, L. (1985). Language and experience: Evidence from the blind child. Cambridge, MA: Harvard University Press.
37. Landauer, T. K. (2002a). On the computational basis of cognition: Arguments from LSA. In B. H. Ross (Ed.), The psychology of learning and motivation (pp. 43-84).New York: Academic Press.
38. Landauer, T. K. (2002b). Single representations of multiple meanings in latent semantic analysis. In D. Gorfein (Ed.), On the consequences of meaning selection (pp. 217-232). Washington, DC: American Psychological Association.
39. Landauer, T. K., and Dumais, S. T. (1997). Asolution to Plato’s problem: The latent semantic analysis theory of the acquisition, induction, and representation of knowledge. Psychological Review, 104(2), 211-240.
40. Landauer, T. K., Foltz, P. W., and Laham, D. (1998). Introduction to latent semantic analysis. Discourse Processes, 25, 259-284.
41. Landauer, T. K., Laham, D., andFoltz, P.W. (2003a). Automated essay assessment. Assessment in Education: Principles, Policy and Practice, 10(3), 295-308.
42. Landauer, T. K., Laham, D., and Foltz, P.W. (2003b). Automated scoring and annotation of essays with the Intelligent Essay Assessor. In M.D. Shermis, andJ. Burstein (Eds.), Automated essay scoring: A cross-disciplinary perspective (pp. 87-112). Mahwah, NJ: Lawrence Erlbaum Associates.
43. Lund, K., andBurgess, C. (1996). Producing high-dimensional semantic spaces fromlexical co-occurrence. Behavioral ResearchMethods, Instruments, and Computers, 28, 203-208.
44. Lund, K., Burgess, C., and Atchley, R. A. (1995). Semantic and associative priming in high-dimensional semantic space. In J. D. Moore and J. F. Lehman (Eds.), Cognitive sciences society (pp. 660-665). Pittsburgh, PA: Lawrence Erlbaum Associates.
45. O’Reilly, R., and Munakata, Y. (2000). Computational explorations in cognitive neuroscience: Understanding the mind by simulating the brain. Cambridge, MA:MITPress.
46. Osherson, D., Stob, M., and Weinstein, S. (1984). Learning theory and natural language. Cognition, 17, 1-28.
47. Pinker, S. (1994). The language instinct. New York: HarperCollins.
48. Pylyshyn, Z. W. (1980). Computation and cognition: Issues in the foundations of cognitive sciences. Behavioral and Brain Sciences, 3(1), 111-169.
49. Quine, W. O. (1960).Word and object. Cambridge, MA: MIT Press.
50. Rehder, B., Schreiner, M. E., Wolfe, M. B.W., Laham, D., Landauer, T. K., and Kintsch, W. (1998). Using latent semantic analysis to assess knowledge: Some technical considerations. Discourse Processes, 25, 337-354.
51. Ridley, M. (1994). TheRed Queen:Sex and the evolution of humanbehavior. London:Penguin.
52. Rosenfeld, R. (1996). Amaximumentropy approach to adaptive statistical language modeling. Computer Speech and Language, 10, 187-228.
53. Searle, J. R. (1982). The Chinese room revisited. Behavioral and Brain Sciences, 5, 345-348.
54. Skinner, B. F. (1957). Verbal behavior. East Norwalk, CT: Appleton-Century-Crofts.
55. Stokes, D. E. (1997). Pasteur’s quadrant: Basic science and technological innovation. Washington, DC: Brookings Institution Press.
56. Valentine, D., Abdi, H., andOtoole, A. (1994). Categorization and identification of human face images by neural networks: A review of linear autoassociative and principal component approaches. Journal of Biological Systems, 2, 412-423.
57. Wittgenstein, L. (1953). Philosophical investigations. Oxford, England: Blackwell.
58. Wolfe, M.B.W., Schreiner, M. E., Rehder, B., Laham, D., Foltz, P.W., Kintsch, W., et al. (1998). Learning from text: Matching readers and text by latent semantic analysis. Discourse Processes, 25, 309-336.