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comRAT-C: A computational compound Remote Associates Test solver based on language data and its comparison to human performance.

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Title: comRAT-C: A computational compound Remote Associates Test solver based on language data and its comparison to human performance.
Authors: Olteţeanu, Ana-Maria1 amo_odu@yahoo.com, Falomir, Zoe1 zfalomir@informatik.uni-bremen.de
Source: Pattern Recognition Letters. Dec2015 Part 1, Vol. 67, p81-90. 10p.
Subjects: Remote associates test, Computational linguistics, Performance technology, Cognitive computing, Problem solving
Abstract: Discovering the processes and types of knowledge organization which are involved in the creative process is a challenge up to this date. Human creativity is usually measured by psychological tests, such as the Remote Associates Test (RAT). In this paper, an approach based on a specific type of knowledge organization and processes which enables automatic solving of RAT queries is implemented (comRAT) as a part of a more general cognitive theoretical framework for creative problem-solving (CreaCogs). This aims to study: (a) whether a convergence process can be used to solve such queries and (b) if frequency of appearance of the test items in language data may influence knowledge association or discovery in solving such problems. The comRAT uses a knowledge base of language data extracted from the Corpus of Contemporary American English. The results obtained are compared to results obtained in empirical tests with humans. In order to explain why some answers might be preferred over others, frequencies of appearance of the queries and solutions are analyzed. The difficulty encountered by humans when solving RAT queries is expressed in response times and percentage of participants solving the query, and a significant moderate correlation between human data on query difficulty and the data provided by this approach is obtained. [ABSTRACT FROM AUTHOR]
Copyright of Pattern Recognition Letters is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: comRAT-C: A computational compound Remote Associates Test solver based on language data and its comparison to human performance.
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  Data: <searchLink fieldCode="AR" term="%22Olteţeanu%2C+Ana-Maria%22">Olteţeanu, Ana-Maria</searchLink><relatesTo>1</relatesTo><i> amo_odu@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Falomir%2C+Zoe%22">Falomir, Zoe</searchLink><relatesTo>1</relatesTo><i> zfalomir@informatik.uni-bremen.de</i>
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  Data: <searchLink fieldCode="JN" term="%22Pattern+Recognition+Letters%22">Pattern Recognition Letters</searchLink>. Dec2015 Part 1, Vol. 67, p81-90. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Remote+associates+test%22">Remote associates test</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+linguistics%22">Computational linguistics</searchLink><br /><searchLink fieldCode="DE" term="%22Performance+technology%22">Performance technology</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+computing%22">Cognitive computing</searchLink><br /><searchLink fieldCode="DE" term="%22Problem+solving%22">Problem solving</searchLink>
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  Label: Abstract
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  Data: Discovering the processes and types of knowledge organization which are involved in the creative process is a challenge up to this date. Human creativity is usually measured by psychological tests, such as the Remote Associates Test (RAT). In this paper, an approach based on a specific type of knowledge organization and processes which enables automatic solving of RAT queries is implemented (comRAT) as a part of a more general cognitive theoretical framework for creative problem-solving (CreaCogs). This aims to study: (a) whether a convergence process can be used to solve such queries and (b) if frequency of appearance of the test items in language data may influence knowledge association or discovery in solving such problems. The comRAT uses a knowledge base of language data extracted from the Corpus of Contemporary American English. The results obtained are compared to results obtained in empirical tests with humans. In order to explain why some answers might be preferred over others, frequencies of appearance of the queries and solutions are analyzed. The difficulty encountered by humans when solving RAT queries is expressed in response times and percentage of participants solving the query, and a significant moderate correlation between human data on query difficulty and the data provided by this approach is obtained. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Pattern Recognition Letters is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.patrec.2015.05.015
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      – Code: eng
        Text: English
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        PageCount: 10
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    Subjects:
      – SubjectFull: Remote associates test
        Type: general
      – SubjectFull: Computational linguistics
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      – SubjectFull: Performance technology
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      – SubjectFull: Cognitive computing
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              Text: Dec2015 Part 1
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