Scott Deerwester
Scott Craig Deerwester is an American computer scientist and computer engineer who created the mathematical and natural language processing (NLP) technique known as Latent Semantic Analysis (LSA).[1][2]
Early life
Deerwester was born in Rossville, Indiana, United States in January, 1956.[3] He is the son of Kenneth F. Deerwester (July 8, 1927 – March 3, 2013) and Donna Stone.[4]
Scientific career
Deerwester began his academic career in the United States, contributing to the development of LSA[5] during his time at Colgate University and the University of Chicago.[6] He published his first research paper, The Retrieval Expert Model of Information Retrieval,[7] at Purdue University in 1984.[8]
Publications and research work
Deerwester co-authored a research paper on Latent Semantic Analysis (LSA) in 1988[9] proposing an improvement to information retrieval systems process textual information through deriving a semantic structure for the text. This aids the matching of user requests by addressing issues related to polysemy (words with multiple meanings) and synonymy (different words with similar meanings).[10]
According to Deerwester's 1988 paper, LSA enabled search engines to retrieve relevant documents even when they did not contain the exact keywords, which led to a more user-friendly and contextual retrieval mechanism.[1] His research advanced the development of Latent Dirichlet Allocation (LDA) and probabilistic models, which are widely used in topic modeling and semantic analysis.[2]
LSA is used in natural language processing applications, including chatbots and automatic translation services, and has the ability to emulate some human traits such as word sorting and category assessment.[11] Deerwester's work has found applications in data mining, recommended systems, and business intelligence tools.[2]
References
- ^ a b Deerwester, Scott; Dumais, Susan T.; Furnas, George W.; Landauer, Thomas K.; Harshman, Richard (September 1990). "Indexing by latent semantic analysis". Journal of the American Society for Information Science. 41 (6): 391–407. doi:10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9. ISSN 0002-8231.
- ^ a b c Dumais, S. T.; Furnas, G. W.; Landauer, T. K.; Deerwester, S.; Harshman, R. (1988-05-01). "Using latent semantic analysis to improve access to textual information". Proceedings of the SIGCHI conference on Human factors in computing systems – CHI '88. New York, NY, USA: Association for Computing Machinery. pp. 281–285. doi:10.1145/57167.57214. ISBN 978-0-201-14237-2.
- ^ "Scott Craig DEERWESTER personal appointments - Find and update company information - GOV.UK". find-and-update.company-information.service.gov.uk. Retrieved 2024-12-26.
- ^ "Obituary information for Kenneth F. Deerwester". www.gundersonfh.com. Retrieved 2025-01-04.
- ^ Deerwester, Scott; Dumais, Susan T.; Furnas, George W.; Landauer, Thomas K.; Harshman, Richard (1990). "Indexing by latent semantic analysis". Journal of the American Society for Information Science. 41 (6): 391–407. doi:10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9. ISSN 1097-4571.
- ^ Scott, Deerwester. "Scott Deerwester | LinkedIn". LinkedIn.
- ^ "THE RETRIEVAL EXPERT MODEL OF INFORMATION RETRIEVAL - ProQuest". www.proquest.com. Retrieved 2024-12-26.
- ^ Deerwester, Scott (1984). "The retrieval expert model of information retrieval". Google Scholar. Retrieved 18 October 2024.
- ^ Dumais, S. T.; Furnas, G. W.; Landauer, T. K.; Deerwester, S.; Harshman, R. (1988). "Using latent semantic analysis to improve access to textual information". Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '88. Washington, D.C., United States: ACM Press. pp. 281–285. doi:10.1145/57167.57214. ISBN 978-0-201-14237-2.
- ^ Hurtado, Jose L.; Agarwal, Ankur; Zhu, Xingquan (14 April 2016). "Topic discovery and future trend forecasting for texts". Journal of Big Data. 3. doi:10.1186/s40537-016-0039-2.
- ^ Foltz, Peter W. (1996-06-01). "Latent semantic analysis for text-based research". Behavior Research Methods, Instruments, & Computers. 28 (2): 197–202. doi:10.3758/BF03204765. ISSN 1532-5970.