| Published
Research |
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| The genesis of Extractor was a
thesis exploring the application of artificial intelligence and machine
learning. Specifically, how the growing proliferation of information and
intellectual property, primarily via the World Wide Web, could be
refined and sourced with certainty and relevance. The application of
artificial intelligence married with the theories of machine learning
would prove effective. |
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| We know and
experience today the great results of Dr. Turney's research efforts, now
in version 7.2, Extractor is a proven solution providing developers with
the tool for better sourcing of information and most importantly its
contextual meaning. The scientific research that went into the creation
of the Extractor Technology is found in the following published
documentation: |
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¤ Turney, P.D. (2000).
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Learning algorithms for keyphrase extraction.
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Information Retrieval, 2 (4): 303-336.
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¤ Mathieu, J. (1999).
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Adaptation of a keyphrase extractor for Japanese text.
- Proceedings of the
27th Annual Conference of the Canadian Association for Information
Science (CAIS-99),
- Sherbrooke, Quebec,
pp. 182-189.
- ¤
Turney, P.D. (1999).
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Learning to Extract Keyphrases from Text.
- NRC Technical Report
ERB-1057, National Research Council Canada.
- ¤
Turney, P.D. (1997).
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Extraction of Keyphrases from Text: Evaluation of Four Algorithms.
- NRC Technical Report
ERB-1051, National Research Council Canada.
¤
Answering Subcognitive Turing Test Questions: A Reply to French
¤
Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL |
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