INFORMATION CHANGE THE WORLD

International Journal of Intelligent Systems and Applications(IJISA)

ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online)

Published By: MECS Press

IJISA Vol.6, No.3, Feb. 2014

Temperament and Mood Detection Using Case-Based Reasoning

Full Text (PDF, 440KB), PP.50-61


Views:115   Downloads:1

Author(s)

Adebayo Kolawole John, Adekoya Adewale M., Ekwonna Chinnasa

Index Terms

CBR, Temperament; Mood, TAMDS, Artificial Intelligence

Abstract

Case-Based Reasoning (CBR) is a branch of AI that is employed to solving problems which emphasizes the use of previous solutions in solving similar new problems. This work presents TAMDS, a Temperament and Mood Detection system which employs Case-Based Reasoning technique. The proposed system is adapted to the field of psychology to help psychologists solve part of the problems in their complex domain. We have designed TAMDS to detect temperament and moods of individuals. A major aim of our system is to help individuals who are out of reach of a professional psychologist to manage their personality and moods because as humans, moods affect our perceptions, personal health, the way we view the world around us and the way we react to it.

Cite This Paper

Adebayo Kolawole John, Adekoya Adewale M., Ekwonna Chinnasa,"Temperament and Mood Detection Using Case-Based Reasoning", International Journal of Intelligent Systems and Applications(IJISA), vol.6, no.3, pp.50-61, 2014. DOI: 10.5815/ijisa.2014.03.05

Reference

[1]Agnar Aamodt and Enric Plaza: Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. In AI Communications, Vol. 7 Nr. 1, March 1994, pp 39-59

[2]KOLODNER, J. (1993), Case-Based Reasoning, Morgan Kaufmann, San Mateo, CA

[3]Kolodner, J. (1983): Maintaining organization in a dynamic long-term memory. Cognitive Science, Vol.7, pgs.243-280. 

[4]Schank, R. (1982): Dynamic memory; a theory of reminding and learning in computers and people. Cambridge University Press.

[5]Schank, R. and Leake, D. (1989): Creativity and learning in a case-based explainer. Artificial Intelligence, Vol. 40, no 1-3. pp 353-385.

[6]Aamodt, A., (1989) Towards robust expert systems that learn from experience - an architectural framework. In John Boose, Brian Gaines, Jean-Gabriel Ganascia (eds.): EKAW-89; Third European Knowledge Acquisition for Knowledge-Based Systems Workshop , Paris, July 1989. pp 311-326.

[7]Aamodt, A. (1991). A knowledge-intensive approach to problem solving and sustained learning, Ph.D. dissertation, University of Trondheim, Norwegian Institute of Technology, May 1991. (University Microfilms PUB 92-08460)

[8]Massie S. And Susan Craw And Nirmaliewiratunga (2006), Complexity-Guided Case Discovery for Case Based Reasoning. The Robert Gordon University Aberdeen, AB25 1HG, Scotland, UK

[9]Pantic Maja And Rothkrantz Leon, (2004), Case-Based Reasoning For User-Profiled Recognition Of Emotions From Face Images Delft University of Technology EEMCS / Mediamatics Dept. Delft, the Netherlands

[10]Burke Edmund K., Maccarthy Bart L., Petrovic Sanja, Rong Qu. (2006). Multiple-Retrieval Case-Based Reasoning for Course Timetabling Problems Automated Scheduling Optimization and Planning Research Group School of Computer Science and Information Technology, The University of Nottingham, Nottingham, NG8 1BB, U.K. Journal of Operations Research Society, 57(2): 148-162, 2006 

[11]Mobyen Uddin Ahmed, Shahina Begum, Peter Funk, Ning Xiong, Bo Von Schéele (2008). Case-based Reasoning for Diagnosis of Stress using Enhanced Cosineand Fuzzy Similarity. In Transactions on Case-Based Reasoning for Multimedia Data Vol.1, No 1 pg 3-19

[12]Souad Guessoum, M.Tayeb Laskri, Hayet djellali and M. Tarek Khadir (2012): Combining Case and Rule Based Reasoning for the Diagnosis and Therapy of Chronic Obstructive Pulmonary Disease. In International Journal of Hybrid Information Technology Vol. 5, No. 3, July, 2012

[13]Rainer Schmidt, Stefania Montani, Riccardo Bellazzi, Luigi Portinale, Lothar Gierl (2001): Cased-Based Reasoning for medical knowledge-based systems. In International Journal of Medical Informatics 64 (2001) 355–367

[14]Piero P Bonissone and Ramon Lopez de Mantaras: F4.3 Fuzzy Case-Based Reasoning Systems

[15]Nikolaidis Savvas and Lazos C: Fuzzy Case Identification in Case Based Reasoning SystemsHock, C., (2010) The Four Temperaments

[16]Watson I, Applying Case-Based Reasoning: Techniques for Enterprise systems, 1997

[17]Jim Prentzas and Ioannis Hatzilygeroudis, Combinations of Case-Based Reasoning with Other Intelligent Methods

[18]Amroush F. (2012), Proposing A Similarity Measure In Case Based Reasoning For Products Selection- An Experimental Evidence. In Proceedings of the 4th International Conference on Agents and Artificial Intelligence, pages 499-502

[19]Jim Prentzas, Ioannis Hatzilygeroudis, Integrations of Rule-Based and Case-Based Reasoning

[20]Jim Prentzas and Ioannis Hatzilygeroudis, Combinations of Case-Based Reasoning with Other Intelligent Methods

[21]A. HOLT and G. L. BENWELL, Applying case-based reasoning techniques in GIS in intl. journal of geographical information science,1999, vol.13, no.1,9 25.