Cognitive Science forWeb Usage Analysis

Web usage mining is the process of extracting patterns from web user’s preferences and browsing behavior. Furthermore, the web user behavior refers to the user’s activities in a web site. Cognitive science is a multi-disciplinary approach used for the understanding of human behavior, whose aims is to develop models of information processing in the real brain. Therefore, cognitive sciences can have direct application to web usage mining. In this chapter, some state-of-the-art psychology theories are presented in the context of web usage analysis. In spite of the complexity of neural processes in the brain, stochastic models based on diffusion can be used to explain a decision-making process, and this has been experimentally tested. Diffusion models and theirs application to describe web usage are reviewed in this chapter. An example of application of cognitive science to web usage mining is also presented.

[1]  Bipin Indurkhya,et al.  The role of content in addition to hyperlinks in user-clicking behavior , 2010, ECCE.

[2]  Pablo E. Román,et al.  Clustering-Based Learning Approach for Ant Colony Optimization Model to Simulate Web User Behavior , 2011, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

[3]  Roger Ratcliff,et al.  A Theory of Memory Retrieval. , 1978 .

[4]  M. Stone Models for choice-reaction time , 1960 .

[5]  A. Amos A Computational Model of Information Processing in the Frontal Cortex and Basal Ganglia , 2000, Journal of Cognitive Neuroscience.

[6]  M. Shadlen,et al.  Representation of Confidence Associated with a Decision by Neurons in the Parietal Cortex , 2009, Science.

[7]  Marco Winckler,et al.  Human-Computer Interaction - INTERACT 2009, 12th IFIP TC 13 International Conference, Uppsala, Sweden, August 24-28, 2009, Proceedings, Part I , 2009, INTERACT.

[8]  Avrim Blum,et al.  A Random-Surfer Web-Graph Model , 2006, ANALCO.

[9]  J. Gold,et al.  The neural basis of decision making. , 2007, Annual review of neuroscience.

[10]  D. McFadden Conditional logit analysis of qualitative choice behavior , 1972 .

[11]  M. A. Basso,et al.  Modulation of Neuronal Activity in Superior Colliculus by Changes in Target Probability , 1998, The Journal of Neuroscience.

[12]  R. O’Reilly The What and How of prefrontal cortical organization , 2010, Trends in Neurosciences.

[13]  Donald Laming,et al.  Information theory of choice-reaction times , 1968 .

[14]  James T. Townsend,et al.  Quantum dynamics of human decision-making , 2006 .

[15]  K. H. Britten,et al.  Responses of neurons in macaque MT to stochastic motion signals , 1993, Visual Neuroscience.

[16]  J. Schall On building a bridge between brain and behavior. , 2004, Annual review of psychology.

[17]  Dirk P. Kroese,et al.  Simulation and the Monte Carlo method , 1981, Wiley series in probability and mathematical statistics.

[18]  Rahul Telang,et al.  Does the Web Reduce Customer Service Cost? Empirical Evidence from a Call Center , 2012 .

[19]  Moshe Ben-Akiva,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .

[20]  Peter Brusilovsky,et al.  Social Navigation Support for Information Seeking: If You Build It, Will They Come? , 2009, UMAP.

[21]  Craig S. Miller,et al.  Modeling Information Navigation: Implications for Information Architecture , 2004, Hum. Comput. Interact..

[22]  K. Train Discrete Choice Methods with Simulation , 2003 .

[23]  Georgios Paliouras,et al.  Navigation , 2022 .

[24]  Timothy D. Hanks,et al.  Microstimulation of macaque area LIP affects decision-making in a motion discrimination task , 2006, Nature Neuroscience.

[25]  José Luis Cabral de Moura Borges,et al.  A data mining model to capture user web navigation patterns , 2000 .

[26]  P. Pirolli Information Foraging Theory: Adaptive Interaction with Information , 2007 .

[27]  M G Helander,et al.  Modeling the customer in electronic commerce. , 2000, Applied ergonomics.

[28]  Vasile Palade,et al.  A Knowledge Base for the maintenance of knowledge extracted from web data , 2007, Knowl. Based Syst..

[29]  Sriram Subramanian,et al.  Talking about tactile experiences , 2013, CHI.

[30]  Jonathan D. Cohen,et al.  The physics of optimal decision making: a formal analysis of models of performance in two-alternative forced-choice tasks. , 2006, Psychological review.

[31]  Michael L. Scott,et al.  Programming Language Pragmatics , 1999 .

[32]  Vanishree K. null,et al.  Logit and Probit: Ordered and Multinomial Models , 2001 .

[33]  James L. McClelland Toward a theory of information processing in graded, random, and interactive networks , 1993 .

[34]  Colin Camerer,et al.  Neuroeconomics: decision making and the brain , 2008 .

[35]  Edward Cutrell,et al.  What are you looking for?: an eye-tracking study of information usage in web search , 2007, CHI.

[36]  M. Shadlen,et al.  Decision-making with multiple alternatives , 2008, Nature Neuroscience.

[37]  M. Philiastides,et al.  Spatiotemporal characteristics of perceptual decision making in the human brain , 2009 .

[38]  Christopher D. Wickens,et al.  Multiple Resources and Mental Workload , 2008, Hum. Factors.

[39]  R. C. Tees Review of The organization of behavior: A neuropsychological theory. , 2003 .

[40]  Peter Pirolli Powers of 10: Modeling Complex Information-Seeking Systems at Multiple Scales , 2009, Computer.

[41]  Thierry Baccino,et al.  A Model to Simulate Web Users' Eye Movements , 2009, INTERACT.

[42]  John R Anderson,et al.  An integrated theory of the mind. , 2004, Psychological review.

[43]  M. Shadlen,et al.  Response of Neurons in the Lateral Intraparietal Area during a Combined Visual Discrimination Reaction Time Task , 2002, The Journal of Neuroscience.

[44]  S. Grossberg,et al.  Neural dynamics of decision making under risk: affective balance and cognitive-emotional interactions. , 1988, Psychological review.

[45]  Daniel Gopher,et al.  On the Economy of the Human Processing System: A Model of Multiple Capacity. , 1977 .

[46]  Mark Levene,et al.  An Heuristic to Capture Longer User Web Navigation Patterns , 2000, EC-Web.

[47]  J. Wolfowitz,et al.  Optimum Character of the Sequential Probability Ratio Test , 1948 .

[48]  D. LaBerge A recruitment theory of simple behavior , 1962 .

[49]  S. K. Gupta,et al.  Modeling the KDD Process , 2009, Encyclopedia of Data Warehousing and Mining.

[50]  A. Tversky,et al.  Prospect Theory : An Analysis of Decision under Risk Author ( s ) : , 2007 .

[51]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .

[52]  Jennifer S Trueblood,et al.  A quantum theoretical explanation for probability judgment errors. , 2011, Psychological review.

[53]  Pedro M. Domingos,et al.  Web Site Personalizers for Mobile Devices , 2001 .

[54]  Langche Zeng,et al.  A Heteroscedastic Generalized Extreme Value Discrete Choice Model , 2000 .

[55]  R. Romo,et al.  Neural codes for perceptual discrimination in primary somatosensory cortex , 2005, Nature Neuroscience.

[56]  Jeffrey D. Schall Frontal Eye Fields , 2009 .

[57]  L. Haan,et al.  Extreme value theory : an introduction , 2006 .

[58]  Amaury Habrard,et al.  A Polynomial Algorithm for the Inference of Context Free Languages , 2008, ICGI.

[59]  Pablo E. Román,et al.  Stochastic Simulation of Web Users , 2010, 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[60]  Dirk P. Kroese,et al.  Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics) , 1981 .

[61]  Ennio Cascetta,et al.  Transportation Systems Engineering: Theory and Methods , 2001 .

[62]  Adele Diederich,et al.  Survey of decision field theory , 2002, Math. Soc. Sci..

[63]  Vani K. Borooah,et al.  Logit and Probit , 2002 .

[64]  S. Resnick Adventures in stochastic processes , 1992 .

[65]  Gary H. McClelland,et al.  The effect of site design and interattribute correlations on interactive web-based decisions , 2005 .

[66]  Christopher D. Wickens,et al.  Multiple resources and performance prediction , 2002 .

[67]  Phillip L. Emerson,et al.  Simple reaction time with markovian evolution of gaussian discriminal processes , 1970 .

[68]  Huberman,et al.  Strong regularities in world wide web surfing , 1998, Science.

[69]  Francesco Ricci,et al.  User Modeling, Adaptation, and Personalization , 2014, Lecture Notes in Computer Science.

[70]  A. Hill Excitation and Accommodation in Nerve , 1936 .

[71]  Ajith Abraham,et al.  Web usage mining using artificial ant colony clustering and linear genetic programming , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[72]  J. Townsend,et al.  Decision field theory: a dynamic-cognitive approach to decision making in an uncertain environment. , 1993, Psychological review.

[73]  Takashi R Sato,et al.  Search Efficiency but Not Response Interference Affects Visual Selection in Frontal Eye Field , 2001, Neuron.

[74]  A. Tversky,et al.  Context-dependent preferences , 1993 .

[75]  R. Audley,et al.  SOME ALTERNATIVE STOCHASTIC MODELS OF CHOICE1 , 1965 .

[76]  Pablo E. Román,et al.  Analysis of the Web User Behavior with a Psychologically-Based Diffusion Model , 2009, AAAI Fall Symposium: Biologically Inspired Cognitive Architectures.

[77]  J. Busemeyer,et al.  Extending the Bounds of Rationality: Evidence and Theories of Preferential Choice , 2006 .

[78]  S. Petersen,et al.  Frontal cortex contributes to human memory formation , 1999, Nature Neuroscience.

[79]  James T. Townsend,et al.  Building bridges between neural models and complex decision making behaviour , 2006, Neural Networks.

[80]  A. Tversky,et al.  "Preference trees": Correction to Tversky and Sattath , 1980 .

[81]  P. Rousseeuw,et al.  Wiley Series in Probability and Mathematical Statistics , 2005 .

[82]  M. Shadlen,et al.  Neural correlates of a decision in the dorsolateral prefrontal cortex of the macaque , 1999, Nature Neuroscience.

[83]  Pablo E. Román,et al.  Web Usage Mining , 2010 .

[84]  Jeffrey D. Schall,et al.  Neural basis of deciding, choosing and acting , 2001, Nature Reviews Neuroscience.

[85]  J. Busemeyer,et al.  A quantum probability explanation for violations of ‘rational’ decision theory , 2009, Proceedings of the Royal Society B: Biological Sciences.

[86]  In-Young Ko,et al.  Cognitive Resource Aware Service Provisioning , 2011, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

[87]  David E. Irwin,et al.  The dynamics of cognition and action: mental processes inferred from speed-accuracy decomposition. , 1988, Psychological review.

[88]  Eric L. Schwartz,et al.  Computational Neuroscience , 1993, Neuromethods.

[89]  L. Tremblay,et al.  Handbook of reward and decision making , 2009 .

[90]  Leslie G. Ungerleider,et al.  The neural systems that mediate human perceptual decision making , 2008, Nature Reviews Neuroscience.

[91]  Graham K. Rand,et al.  Quantitative Applications in the Social Sciences , 1983 .

[92]  Pablo E. Román,et al.  A Dynamic Stochastic Model Applied to the Analysis of the Web User Behavior , 2010 .

[93]  R. Ratcliff,et al.  Connectionist and diffusion models of reaction time. , 1999, Psychological review.

[94]  Ilya Segal,et al.  Solutions manual for Microeconomic theory : Mas-Colell, Whinston and Green , 1997 .

[95]  P. Zarembka Frontiers in econometrics , 1973 .

[96]  D. Kahneman MAPS OF BOUNDED RATIONALITY: A PERSPECTIVE ON INTUITIVE JUDGMENT AND CHOICE , 2003 .

[97]  T. Wickens Elementary Signal Detection Theory , 2001 .

[98]  Wai-Tat Fu,et al.  SNIF-ACT: A Model of Information Foraging on the World Wide Web , 2003, User Modeling.

[99]  Steven H. Strogatz,et al.  Complex systems: Romanesque networks , 2005, Nature.

[100]  Georgios Paliouras,et al.  MODELING WEB NAVIGATION USING GRAMMATICAL INFERENCE , 2008, Appl. Artif. Intell..

[101]  A. Tversky,et al.  The framing of decisions and the psychology of choice. , 1981, Science.

[102]  James L. McClelland,et al.  The time course of perceptual choice: the leaky, competing accumulator model. , 2001, Psychological review.