Semantic analysis in cognitive UBIAS & E-UBIAS systems

This publication presents the use of semantic analysis in IT processes of data interpretation and understanding. These processes form a part of a field called cognitive informatics, which encompasses subjects related to the semantic analysis and interpretation of data leading to understanding the analysed data sets. Examples of applications of this type of analysis methods will be shown using the case of an IT system for the cognitive analysis of image data presenting X-ray images lesions. The presented UBIAS (Understanding Based Image Analysis Systems) designed for the cognitive analysis of image data are supplemented with processes of biometric analysis, identification and verification of persons. This type of solution can be introduced due to defining formalisms of linguistic data description proposed as part of E-UBIAS systems (Extended Understanding Based Image Analysis Systems). These systems are used for the personal and authentication analysis of an individual and form one of the main subjects of this publication. Semantic analysis dedicated to cognitive semantic interpretation solutions will be discussed using two different applications as examples. The first is about understanding medical image data showing lesions of foot bones. The second are the results of work on analysing palm bone lesions, which laid foundations for a new class of E-UBIAS systems for biometric verification and identification of persons.

[1]  J. Gabrieli.  Cognitive neuroscience of human memory. , 1998, Annual review of psychology.

[2]  Jerome Kagan,et al.  Unstable Ideas: Temperament, Cognition, and Self , 1989 .

[3]  Marek R. Ogiela,et al.  Cognitive Techniques in Visual Data Interpretation , 2009, Studies in Computational Intelligence.

[4]  S. Rapcsak,et al.  Anomia for Facial Expressions: Neuropsychological Mechanisms and Anatomical Correlates , 1993, Brain and Language.

[5]  M. Driscoll.  Psychology of Learning for Instruction , 1993 .

[6]  Marek R. Ogiela,et al.  Cognitive Computing in Intelligent Medical Pattern Recognition Systems , 2006 .

[7]  Robert A. Wilson,et al.  Book Reviews: The MIT Encyclopedia of the Cognitive Sciences , 2000, CL.

[8]  L. Ogiela,et al.  Innovation approach to cognitive medical image interpretation , 2008, 2008 International Conference on Innovations in Information Technology.

[9]  Lidia Ogiela,et al.  Cognitive Computational Intelligence in Medical Pattern Semantic Understanding , 2008, 2008 Fourth International Conference on Natural Computation.

[10]  D. Medin,et al.  The role of theories in conceptual coherence. , 1985, Psychological review.

[11]  João Branquinho.  The foundations of cognitive science , 2001 .

[12]  Marek R. Ogiela,et al.  Image languages in intelligent radiological palm diagnostics , 2006, Pattern Recognit..

[13]  Marek R. Ogiela,et al.  Cognitive techniques in medical information systems , 2008, Comput. Biol. Medicine.

[14]  Axel Cleeremans,et al.  Principles for Implicit Learning , 1997 .

[15]  Henri Cohen,et al.  Handbook of categorization in cognitive science , 2005 .

[16]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.

[17]  Hubert L. Dreyfus,et al.  What computers still can't do - a critique of artificial reason , 1992 .

[18]  A. Newell.  Unified Theories of Cognition , 1990 .

[19]  Lidia Ogiela,et al.  Modelling of Cognitive Processes for Computer Image Interpretation , 2008, 2008 Second UKSIM European Symposium on Computer Modeling and Simulation.

[20]  Marek R. Ogiela,et al.  Cognitive systems in medical data interpretation and image understanding , 2011, The 7th International Conference on Networked Computing and Advanced Information Management.

[21]  Lidia Ogiela,et al.  UBIAS systems for cognitive interpretation and analysis of medical images , 2009 .

[22]  John McCarthy,et al.  What Computers Still Can't Do , 1996, Artif. Intell..

[23]  Lotfi A. Zadeh,et al.  Toward Human Level Machine Intelligence - Is It Achievable? The Need for a Paradigm Shift , 2008, IEEE Computational Intelligence Magazine.

[24]  Lidia Ogiela,et al.  Computational Intelligence in Cognitive Healthcare Information Systems , 2010 .

[25]  David G. Stork,et al.  Pattern Classification , 1973 .

[26]  James S. Albus,et al.  Engineering of Mind: An Introduction to the Science of Intelligent Systems , 2001 .

[27]  Lidia Ogiela,et al.  Syntactic Approach to Cognitive Interpretation of Medical Patterns , 2008, ICIRA.

[28]  H. K. Huang.  Pacs: Picture Archiving and Communication Systems in Biomedical Imaging , 1996 .

[29]  R. Davidson.  Prolegomenon to the structure of emotion: Gleanings from neuropsychology , 1992 .

[30]  Lidia Ogiela,et al.  Cognitive Systems for Medical Pattern Understanding and Diagnosis , 2008, KES.

[31]  Yingxu Wang,et al.  On System Algebra: A Denotational Mathematical Structure for Abstract System Modeling , 2008, Int. J. Cogn. Informatics Nat. Intell..

[32]  Marek R. Ogiela,et al.  Intelligent Semantic Information Retrieval in Medical Pattern Cognitive Analysis , 2005, ICCSA.

[33]  Marek R. Ogiela,et al.  Cognitive approach to bio-inspired medical image understanding , 2010, 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA).

[34]  Eiichi Tanaka,et al.  Theoretical aspects of syntactic pattern recognition , 1995, Pattern Recognit..

[35]  Yingxu Wang,et al.  Deductive Semantics of RTPA , 2008, Int. J. Cogn. Informatics Nat. Intell..

[36]  Jeffrey O. Kephart,et al.  The Vision of Autonomic Computing , 2003, Computer.

[37]  Witold Kinsner.  Towards Cognitive Machines: Multiscale Measures and Analysis , 2007, Int. J. Cogn. Informatics Nat. Intell..

[38]  Yingxu Wang.  On Visual Semantic Algebra (VSA) and the cognitive process of pattern recognition , 2008, 2008 7th IEEE International Conference on Cognitive Informatics.

[39]  D. Berry.  How implicit is implicit learning , 1997 .

[40]  Srinivas Narayanan,et al.  Reasoning About Actions in Narrative Understanding , 1999, IJCAI.

[41]  Edward A. Bender,et al.  Mathematical methods in artificial intelligence , 1996 .

[42]  Alexander M. Meystel,et al.  Intelligent Systems: Architecture, Design, and Control , 2000 .

[43]  Yingxu Wang,et al.  On Concept Algebra: A Denotational Mathematical Structure for Knowledge and Software Modeling , 2008, Int. J. Cogn. Informatics Nat. Intell..

[44]  Marek R. Ogiela,et al.  Semantic Analysis Processes in UBIAS Systems for Cognitive Data Interpretation , 2011, 2011 Fifth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing.

[45]  Lotfi A. Zadeh.  Toward Human-Level Machine Intelligence , 2007, 2007 2nd International Workshop on Soft Computing Applications.

[46]  Paul D. Franzon,et al.  A multichip module design process for notebook computers , 1993, Computer.

[47]  P. Zelazo,et al.  What is Cognitive Control , 2013 .

[48]  Lidia Ogiela,et al.  Cognitive Informatics in Automatic Pattern Understanding and Cognitive Information Systems , 2010 .

[49]  Marek R. Ogiela,et al.  Graph image language techniques supporting radiological, hand image interpretations , 2006, Comput. Vis. Image Underst..

[50]  Carla H. Lagorio,et al.  Psychology , 1929, Nature.

[51]  J. Borod,et al.  Interhemispheric and intrahemispheric control of emotion: a focus on unilateral brain damage. , 1992, Journal of consulting and clinical psychology.

[52]  Yingxu Wang,et al.  On Cognitive Informatics , 2002, Proceedings First IEEE International Conference on Cognitive Informatics.

[53]  Naim Dahnoun,et al.  Studies in Computational Intelligence , 2013 .

[54]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[55]  Larry S. Davis.  Foundations of Image Understanding , 2001 .

[56]  James S. Albus,et al.  Intelligent Systems: Architectures, Design, Control , 2002 .

[57]  P. Todd,et al.  Simple Heuristics That Make Us Smart , 1999 .

[58]  Marek R. Ogiela,et al.  Cognitive Categorizing in UBIAS Intelligent Medical Information Systems , 2008 .