Implications of Computational Cognitive Models for Information Retrieval

and determine from that abstract text that they are not interested in reading the full text. A request for the full text is not necessarily a relevance judgment, but is an indication that the user wanted to read more of the document than just the abstract. For all of the approaches, the documents that the HAM-TMC users viewed were assigned a ranking score by one of the models in the experiments. The ranking scores were used to determine how many of the extracted pairwise judgments from the document download pairwise judgment data set or document click pairwise judgment data set were correctly ordered (e.g., documentA is preferred over documentB) based on the ranking scores. Figure 5.7. Experiment for computing information scent Query issued by user All documents viewed by user in response to query

[1]  John D. Lafferty,et al.  Document Language Models, Query Models, and Risk Minimization for Information Retrieval , 2001, SIGIR Forum.

[2]  J. Schreiber Foundations Of Statistics , 2016 .

[3]  Philippe A. Palanque,et al.  Proceedings of the SIGCHI Conference on Human Factors in Computing Systems , 2014, International Conference on Human Factors in Computing Systems.

[4]  Fredrik Sandin,et al.  Analogical mapping and inference with binary spatter codes and sparse distributed memory , 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

[5]  Yoshua Bengio,et al.  Modeling term dependencies with quantum language models for IR , 2013, SIGIR.

[6]  Peter Wittek,et al.  Combining Word Semantics within Complex Hilbert Space for Information Retrieval , 2013, QI.

[7]  Jerome R Busemeyer,et al.  Can quantum probability provide a new direction for cognitive modeling? , 2013, The Behavioral and brain sciences.

[8]  Rachel K. E. Bellamy,et al.  How Programmers Debug, Revisited: An Information Foraging Theory Perspective , 2013, IEEE Transactions on Software Engineering.

[9]  Hermann Ebbinghaus,et al.  Memory: a contribution to experimental psychology. , 1987, Annals of neurosciences.

[10]  Michael Symonds,et al.  A tensor encoding model of word meaning : theory and application to information retrieval , 2013 .

[11]  Lael J. Schooler,et al.  Mapping the Structure of Semantic Memory , 2013, Cogn. Sci..

[12]  John R. Anderson,et al.  Word Learning in Context - Metaphors and Neologisms , 2013 .

[13]  J. Stephen Downie,et al.  How Significant is Statistically Significant? The case of Audio Music Similarity and Retrieval , 2012, ISMIR.

[14]  Trevor Cohen,et al.  Discovery by scent: Discovery browsing system based on the Information Foraging Theory , 2012, 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops.

[15]  Rui Wang,et al.  Towards social user profiling: unified and discriminative influence model for inferring home locations , 2012, KDD.

[16]  Jerome R. Busemeyer,et al.  Quantum Models of Cognition and Decision , 2012 .

[17]  Rui Li,et al.  Multiple Location Profiling for Users and Relationships from Social Network and Content , 2012, Proc. VLDB Endow..

[18]  Todd R. Johnson,et al.  Focus on information retrieval: Predicting biomedical document access as a function of past use , 2012, J. Am. Medical Informatics Assoc..

[19]  Laurianne Sitbon,et al.  Quantum-like non-separability of concept combinations, emergent associates and abduction , 2012, Log. J. IGPL.

[20]  Vincenzo Crupi,et al.  On the conjunction fallacy and the meaning of and, yet again: A reply to Hertwig, Benz, and Krauss (2008) , 2012, Cognition.

[21]  Guido Zuccon,et al.  On the use of Complex Numbers in Quantum Models for Information Retrieval , 2011, ICTIR.

[22]  Dawei Song,et al.  Investigating Query-Drift Problem from a Novel Perspective of Photon Polarization , 2011, ICTIR.

[23]  M. Gerstein,et al.  The Spread of Scientific Information: Insights from the Web Usage Statistics in PLoS Article-Level Metrics , 2011, PloS one.

[24]  Massimo Melucci,et al.  Towards Predicting Relevance Using a Quantum-Like Framework , 2011, ECIR.

[25]  Ingo Schmitt,et al.  Towards Quantum-Based DB+IR Processing Based on the Principle of Polyrepresentation , 2011, ECIR.

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

[27]  Hernane Borges de Barros Pereira,et al.  Semantic networks based on titles of scientific papers , 2011 .

[28]  Filip Radlinski,et al.  Personalizing web search using long term browsing history , 2011, WSDM '11.

[29]  Richard E. West,et al.  Mendeley: Creating Communities of Scholarly Inquiry Through Research Collaboration , 2011 .

[30]  M. Couture The Lotus Flower , 2011 .

[31]  Emmanuel M. Pothos,et al.  A Quantum Probability Explanation for Violations of Symmetry in Similarity Judgments , 2011, CogSci.

[32]  Harald Atmanspacher,et al.  The Potential of Quantum Probability for Modeling Cognitive Processes , 2011, CogSci.

[33]  A. Fraser,et al.  On the impossibility of being expert , 2010, BMJ : British Medical Journal.

[34]  Md. Monjurul Islam,et al.  Automated essay scoring using Generalized Latent Semantic Analysis , 2010, 2010 13th International Conference on Computer and Information Technology (ICCIT).

[35]  Ann Medaille,et al.  Mendeley , 2010 .

[36]  Pentti Kanerva,et al.  What We Mean When We Say "What's the Dollar of Mexico?": Prototypes and Mapping in Concept Space , 2010, AAAI Fall Symposium: Quantum Informatics for Cognitive, Social, and Semantic Processes.

[37]  C. J. van Rijsbergen,et al.  What can quantum theory bring to information retrieval , 2010, CIKM.

[38]  Pamela Effrein Sandstrom,et al.  Information Foraging Theory: Adaptive Interaction with Information , 2010, J. Assoc. Inf. Sci. Technol..

[39]  Patrick Simen,et al.  A symbolic/subsymbolic interface protocol for cognitive modeling , 2010, Log. J. IGPL.

[40]  Trevor Cohen,et al.  The Semantic Vectors Package: New Algorithms and Public Tools for Distributional Semantics , 2010, 2010 IEEE Fourth International Conference on Semantic Computing.

[41]  C. J. van Rijsbergen,et al.  Supporting polyrepresentation in a quantum-inspired geometrical retrieval framework , 2010, IIiX.

[42]  Luis Villaseñor Pineda,et al.  Concept Based Representations for Ranking in Geographic Information Retrieval , 2010, IceTAL.

[43]  Mark D. Smucker,et al.  Human performance and retrieval precision revisited , 2010, SIGIR.

[44]  Mark Sanderson,et al.  Do user preferences and evaluation measures line up? , 2010, SIGIR.

[45]  John Skvoretz,et al.  Node centrality in weighted networks: Generalizing degree and shortest paths , 2010, Soc. Networks.

[46]  Guido Zuccon,et al.  Using the Quantum Probability Ranking Principle to Rank Interdependent Documents , 2010, ECIR.

[47]  Hedderik van Rijn,et al.  Personal Publication Assistant: Abstract recommendations by a cognitive model , 2010, Cognitive Systems Research.

[48]  C. J. van Rijsbergen,et al.  Exploring a multidimensional representation of documents and queries , 2010, RIAO.

[49]  Ricard V. Solé,et al.  Language networks: Their structure, function, and evolution , 2007, Complex..

[50]  Alison Pease,et al.  Towards a cognitive model of conceptual blending , 2010, ICCM 2010.

[51]  Zhiyong Lu,et al.  Understanding PubMed® user search behavior through log analysis , 2009, Database J. Biol. Databases Curation.

[52]  Manuel Montes-y-Gómez,et al.  Representing Context Information for Document Retrieval , 2009, FQAS.

[53]  Craig MacDonald,et al.  The influence of the document ranking in expert search , 2009, CIKM.

[54]  Ulrik Brandes,et al.  Pure spreading activation is pointless , 2009, CIKM.

[55]  Emmanuel Haven,et al.  Quantum mechanics and violations of the sure-thing principle: The use of probability interference and other concepts , 2009 .

[56]  C. J. van Rijsbergen,et al.  The Quantum Probability Ranking Principle for Information Retrieval , 2009, ICTIR.

[57]  Kalervo Järvelin,et al.  Explaining User Performance in Information Retrieval: Challenges to IR Evaluation , 2009, ICTIR.

[58]  Aurelio López-López,et al.  Combining Text Vector Representations for Information Retrieval , 2009, TSD.

[59]  Gabriel Recchia,et al.  More data trumps smarter algorithms: Comparing pointwise mutual information with latent semantic analysis , 2009, Behavior research methods.

[60]  Jure Leskovec,et al.  Meme-tracking and the dynamics of the news cycle , 2009, KDD.

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

[62]  Mounia Lalmas,et al.  A Quantum-Based Model for Interactive Information Retrieval , 2009, ICTIR.

[63]  Ricard V. Solé,et al.  The Ontogeny of Scale-Free Syntax Networks: Phase Transitions in Early Language Acquisition , 2009, Adv. Complex Syst..

[64]  John M. Carroll,et al.  Enhancing information scent: identifying and recommending quality tags , 2009, GROUP.

[65]  Yue Chen,et al.  Towards an explanatory and computational theory of scientific discovery , 2009, J. Informetrics.

[66]  Peter Pirolli,et al.  Remembrance of things tagged: how tagging effort affects tag production and human memory , 2009, CHI.

[67]  Stefan M. Rüger,et al.  Integrating multiple windows and document features for expert finding , 2009, J. Assoc. Inf. Sci. Technol..

[68]  Mathieu Bastian,et al.  Gephi: An Open Source Software for Exploring and Manipulating Networks , 2009, ICWSM.

[69]  J. Zbilut,et al.  Mental States Follow Quantum Mechanics During Perception and Cognition of Ambiguous Figures , 2009, Open Syst. Inf. Dyn..

[70]  Diederik Aerts,et al.  Experimental Evidence for Quantum Structure in Cognition , 2008, QI.

[71]  Mark E. J. Newman,et al.  Power-Law Distributions in Empirical Data , 2007, SIAM Rev..

[72]  Peter Pirolli,et al.  Information Foraging , 2009, Encyclopedia of Database Systems.

[73]  Sreenivasa Rao Jammalamadaka,et al.  Optimal Text Space Representation of Student Essays Using Latent Semantic Analysis , 2009 .

[74]  Simon D. Levy,et al.  A distributed basis for analogical mapping , 2009 .

[75]  L. Maanen Recommender Systems for Literature Selection : A Competition between Decision Making and Memory Models , 2009 .

[76]  Victor Henning,et al.  Mendeley - A Last.fm For Research? , 2008, 2008 IEEE Fourth International Conference on eScience.

[77]  Wai-Tat Fu The microstructures of social tagging: a rational model , 2008, CSCW.

[78]  Rachel K. E. Bellamy,et al.  Can information foraging pick the fix? A field study , 2008, 2008 IEEE Symposium on Visual Languages and Human-Centric Computing.

[79]  Gerhard Weikum,et al.  YAGO: A Large Ontology from Wikipedia and WordNet , 2008, J. Web Semant..

[80]  Krin A. Kay,et al.  The implications of human metabolic network topology for disease comorbidity , 2008, Proceedings of the National Academy of Sciences.

[81]  Catherine L. Smith,et al.  User adaptation: good results from poor systems , 2008, SIGIR '08.

[82]  Mark Sanderson,et al.  The good and the bad system: does the test collection predict users' effectiveness? , 2008, SIGIR '08.

[83]  ChengXiang Zhai,et al.  A general optimization framework for smoothing language models on graph structures , 2008, SIGIR '08.

[84]  Oren Kurland,et al.  Query-drift prevention for robust query expansion , 2008, SIGIR '08.

[85]  Stephen E. Robertson,et al.  Selecting good expansion terms for pseudo-relevance feedback , 2008, SIGIR '08.

[86]  Martin Rajman,et al.  Using Bibliographic Knowledge for Ranking in Scientific Publication Databases , 2008, JCKBSE.

[87]  Ed H. Chi,et al.  SparTag.us: a low cost tagging system for foraging of web content , 2008, AVI '08.

[88]  Dominic Widdows,et al.  Semantic Vectors: a Scalable Open Source Package and Online Technology Management Application , 2008, LREC.

[89]  Rachel K. E. Bellamy,et al.  Using information scent to model the dynamic foraging behavior of programmers in maintenance tasks , 2008, CHI.

[90]  D. H. Wedell,et al.  Testing boundary conditions for the conjunction fallacy: Effects of response mode, conceptual focus, and problem type , 2008, Cognition.

[91]  Nicholas J. Belkin,et al.  Some(what) grand challenges for information retrieval , 2008, SIGF.

[92]  Chris Eliasmith,et al.  Integrating Structure and Meaning: A New Method for Encoding Structure for Text Classification , 2008, ECIR.

[93]  N. Chater,et al.  The probabilistic mind: prospects for Bayesian cognitive science , 2008 .

[94]  ChengXiang Zhai,et al.  Statistical Language Models for Information Retrieval: A Critical Review , 2008, Found. Trends Inf. Retr..

[95]  Gert Storms,et al.  Word associations: Network and semantic properties , 2008, Behavior research methods.

[96]  Matthew E Falagas,et al.  Comparison of PubMed, Scopus, Web of Science, and Google Scholar: strengths and weaknesses , 2007, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

[97]  Using Cognitive Modeling to Understand the Roles of Prefrontal and Posterior Parietal Cortex in Algebra Problem Solving , 2008 .

[98]  Justin Zobel,et al.  An investigation on a community's web search variability , 2008, ACSC.

[99]  T. Griffiths,et al.  Google and the Mind , 2007, Psychological science.

[100]  Ryen W. White,et al.  Utilizing a geometry of context for enhanced implicit feedback , 2007, CIKM '07.

[101]  Michael T. Turvey,et al.  Human memory retrieval as Lévy foraging , 2007 .

[102]  Rachel K. E. Bellamy,et al.  Scents in Programs:Does Information Foraging Theory Apply to Program Maintenance? , 2007, IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC 2007).

[103]  John R. Anderson How Can the Human Mind Occur in the Physical Universe , 2007 .

[104]  Filip Radlinski,et al.  Active exploration for learning rankings from clickthrough data , 2007, KDD '07.

[105]  Pável Calado,et al.  A combined component approach for finding collection-adapted ranking functions based on genetic programming , 2007, SIGIR.

[106]  Ed H. Chi,et al.  Visual Foraging of Highlighted Text: An Eye-Tracking Study , 2007, HCI.

[107]  Fredrik Liljeros,et al.  Preferential attachment in sexual networks , 2007, Proceedings of the National Academy of Sciences.

[108]  John D. Lafferty,et al.  A correlated topic model of Science , 2007, 0708.3601.

[109]  Peter Pirolli,et al.  Modeling Information Scent: A Comparison of LSA, PMI and GLSA Similarity Measures on Common Tests and Corpora , 2007, RIAO.

[110]  Ryen W. White,et al.  WWW 2007 / Track: Browsers and User Interfaces Session: Personalization Investigating Behavioral Variability in Web Search , 2022 .

[111]  Filip Radlinski,et al.  Recommending related papers based on digital library access records , 2007, JCDL '07.

[112]  Filip Radlinski,et al.  Evaluating the accuracy of implicit feedback from clicks and query reformulations in Web search , 2007, TOIS.

[113]  Ed H. Chi,et al.  ScentIndex and ScentHighlights: Productive Reading Techniques for Conceptually Reorganizing Subject Indexes and Highlighting Passages∗ , 2007, Inf. Vis..

[114]  S. Harnad Symbol grounding problem , 1990, Scholarpedia.

[115]  Gene H. Golub,et al.  Singular value decomposition and least squares solutions , 1970, Milestones in Matrix Computation.

[116]  G. Caldarelli,et al.  Preferential attachment in the growth of social networks, the Internet encyclopedia wikipedia , 2007 .

[117]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[118]  N. Doidge The Brain That Changes Itself , 2007 .

[119]  Massimo Melucci Exploring a Mechanics for Context-Aware Information Retrieval , 2007, AAAI Spring Symposium: Quantum Interaction.

[120]  Duncan P. Brumby,et al.  Dialing while driving? A bounded rational analysis of concurrent multi-task behavior , 2007 .

[121]  Ryen W. White,et al.  Discovering Hidden Contextual Factors for Implicit Feedback , 2007, CIR.

[122]  Ed H. Chi,et al.  Scentindex: Conceptually Reorganizing Subject Indexes for Reading , 2006, 2006 IEEE Symposium On Visual Analytics Science And Technology.

[123]  Falk Scholer,et al.  User performance versus precision measures for simple search tasks , 2006, SIGIR.

[124]  A. Barabasi,et al.  Dynamics of information access on the web. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[125]  Filip Radlinski,et al.  Minimally Invasive Randomization for Collecting Unbiased Preferences from Clickthrough Logs , 2006, AAAI 2006.

[126]  Filip Radlinski,et al.  Evaluating the Robustness of Learning from Implicit Feedback , 2006, ArXiv.

[127]  Diana Inkpen,et al.  Second Order Co-occurrence PMI for Determining the Semantic Similarity of Words , 2006, LREC.

[128]  William R Hersh,et al.  Enhancing access to the Bibliome: the TREC 2004 Genomics Track , 2006, Journal of biomedical discovery and collaboration.

[129]  J. Burnham Scopus database: a review , 2006, Biomedical digital libraries.

[130]  Alan M. Frieze,et al.  Random graphs , 2006, SODA '06.

[131]  E. Garfield The history and meaning of the journal impact factor. , 2006, JAMA.

[132]  Peter Pirolli,et al.  Information Scent and Web Navigation : Theory , Models , and Automated Usability Evaluation , 2006 .

[133]  Arne Elofsson,et al.  Preferential attachment in the evolution of metabolic networks , 2005, BMC Genomics.

[134]  ChengXiang Zhai,et al.  Implicit user modeling for personalized search , 2005, CIKM '05.

[135]  A. Barabasi,et al.  Human dynamics: Darwin and Einstein correspondence patterns , 2005, Nature.

[136]  Peter Ingwersen,et al.  The Turn - Integration of Information Seeking and Retrieval in Context , 2005, The Kluwer International Series on Information Retrieval.

[137]  Magnus Sahlgren,et al.  An Introduction to Random Indexing , 2005 .

[138]  James Allan,et al.  When will information retrieval be "good enough"? , 2005, SIGIR '05.

[139]  Oren Kurland,et al.  PageRank without hyperlinks: structural re-ranking using links induced by language models , 2005, SIGIR '05.

[140]  John R. Anderson,et al.  Practice and Forgetting Effects on Vocabulary Memory: An Activation-Based Model of the Spacing Effect , 2005, Cogn. Sci..

[141]  Wessel Kraaij,et al.  Variations on language modeling for information retrieval , 2005, SIGF.

[142]  John D. Kelleher,et al.  The Annual Meeting of the Cognitive Science Society , 2005, Cognitive Systems Research.

[143]  Albert-László Barabási,et al.  The origin of bursts and heavy tails in human dynamics , 2005, Nature.

[144]  Peter Pirolli,et al.  Rational Analyses of Information Foraging on the Web , 2005, Cogn. Sci..

[145]  Yannis Manolopoulos,et al.  A new perspective to automatically rank scientific conferences using digital libraries , 2005, Inf. Process. Manag..

[146]  Ed H. Chi,et al.  ScentHighlights: highlighting conceptually-related sentences during reading , 2005, IUI.

[147]  A. Sousa Consensus formation on a triad scale-free network , 2004, cond-mat/0406390.

[148]  Joshua B. Tenenbaum,et al.  The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth , 2001, Cogn. Sci..

[149]  James Allan,et al.  An Investigation of Dirichlet Prior Smoothing's Performance Advantage , 2005 .

[150]  Karen Spärck Jones A statistical interpretation of term specificity and its application in retrieval , 2021, J. Documentation.

[151]  Ross W. Gayler Vector Symbolic Architectures answer Jackendoff's challenges for cognitive neuroscience , 2004, ArXiv.

[152]  Otis Gospodnetic,et al.  Lucene in Action , 2004 .

[153]  Stephen E. Robertson,et al.  Understanding inverse document frequency: on theoretical arguments for IDF , 2004, J. Documentation.

[154]  Gerardo Canfora,et al.  A Taxonomy of Information Retrieval Models and Tools , 2004 .

[155]  Massimo Marchiori,et al.  Error and attacktolerance of complex network s , 2004 .

[156]  Thorsten Joachims,et al.  Eye-tracking analysis of user behavior in WWW search , 2004, SIGIR '04.

[157]  E. Volz Random networks with tunable degree distribution and clustering. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[158]  Manfred Tscheligi,et al.  CHI '04 Extended Abstracts on Human Factors in Computing Systems , 2004, CHI 2004.

[159]  Mark Steyvers,et al.  Finding scientific topics , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[160]  A. Vespignani,et al.  The architecture of complex weighted networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[161]  Gábor Csányi,et al.  Structure of a large social network. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[162]  Fabio Crestani,et al.  Application of Spreading Activation Techniques in Information Retrieval , 1997, Artificial Intelligence Review.

[163]  B. Jack Copeland,et al.  On Alan Turing's anticipation of connectionism , 1996, Synthese.

[164]  C. J. van Rijsbergen,et al.  The geometry of information retrieval , 2004 .

[165]  Stuart M. Shieber Can Digital Computers Think , 2004 .

[166]  Marcelo Fiszman,et al.  The interaction of domain knowledge and linguistic structure in natural language processing: interpreting hypernymic propositions in biomedical text , 2003, J. Biomed. Informatics.

[167]  Essay Assessment with Latent Semantic Analysis , 2003 .

[168]  Jon M. Kleinberg,et al.  Overview of the 2003 KDD Cup , 2003, SKDD.

[169]  Troy D. Kelley,et al.  Symbolic and Sub-Symbolic Representations in Computational Models of Human Cognition , 2003 .

[170]  Atanas Kiryakov,et al.  Semantic Annotation, Indexing, and Retrieval , 2003, SEMWEB.

[171]  David Lusseau,et al.  The emergent properties of a dolphin social network , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[172]  Dominic Widdows,et al.  Orthogonal Negation in Vector Spaces for Modelling Word-Meanings and Document Retrieval , 2003, ACL.

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

[174]  E. Levanon,et al.  Preferential attachment in the protein network evolution. , 2003, Physical review letters.

[175]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[176]  Dirk van Rijn,et al.  Proceedings of the 31st annual conference of the Cognitive Science Society , 2003 .

[177]  Gianni Amati,et al.  Probability models for information retrieval based on divergence from randomness , 2003 .

[178]  Akiko Aizawa,et al.  An information-theoretic perspective of tf-idf measures , 2003, Inf. Process. Manag..

[179]  Edmund Fantino,et al.  The conjunction effect: new evidence for robustness. , 2003, The American journal of psychology.

[180]  S. Peters,et al.  Word Vectors and Quantum Logic Experiments with negation and disjunction , 2003 .

[181]  Thorsten Joachims,et al.  Evaluating Retrieval Performance Using Clickthrough Data , 2003, Text Mining.

[182]  C. J. van Rijsbergen,et al.  Probabilistic models of information retrieval based on measuring the divergence from randomness , 2002, TOIS.

[183]  Andrei Broder,et al.  A taxonomy of web search , 2002, SIGF.

[184]  John D. Lafferty,et al.  Two-stage language models for information retrieval , 2002, SIGIR '02.

[185]  David W. Moore Measuring New Types of Question-Order Effects: Additive and Subtractive , 2002 .

[186]  Riccardo Viale,et al.  On the reality of the conjunction fallacy , 2002, Memory & cognition.

[187]  S. Bornholdt,et al.  Scale-free topology of e-mail networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[188]  Beom Jun Kim,et al.  Growing scale-free networks with tunable clustering. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[189]  A. Barabasi,et al.  Evolution of the social network of scientific collaborations , 2001, cond-mat/0104162.

[190]  Hinrich Schütze,et al.  Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.

[191]  W. Bruce Croft Combining Approaches to Information Retrieval , 2002 .

[192]  John R. Anderson,et al.  Comprehending anaphoric metaphors , 2002, Memory & cognition.

[193]  John D. Lafferty,et al.  Model-based feedback in the language modeling approach to information retrieval , 2001, CIKM '01.

[194]  Peter D. Turney Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL , 2001, ECML.

[195]  Andrew Turpin,et al.  Why batch and user evaluations do not give the same results , 2001, SIGIR '01.

[196]  Andrew Turpin,et al.  Challenging conventional assumptions of automated information retrieval with real users: Boolean searching and batch retrieval evaluations , 2001, Inf. Process. Manag..

[197]  Chris Eliasmith,et al.  Integrating structure and meaning: a distributed model of analogical mapping , 2001, Cogn. Sci..

[198]  Robert W. Reeder,et al.  Information scent as a driver of Web behavior graphs: results of a protocol analysis method for Web usability , 2001, CHI.

[199]  Ed H. Chi,et al.  Using information scent to model user information needs and actions and the Web , 2001, CHI.

[200]  John R. Anderson,et al.  The role of background knowledge in sentence processing , 2001 .

[201]  Ron Sun,et al.  Artificial Intelligence: Connectionist and Symbolic Approaches , 2001 .

[202]  P. ERDbS ON THE STRENGTH OF CONNECTEDNESS OF A RANDOM GRAPH , 2001 .

[203]  John D. Lafferty,et al.  A study of smoothing methods for language models applied to Ad Hoc information retrieval , 2001, SIGIR '01.

[204]  Djoerd Hiemstra,et al.  A probabilistic justification for using tf×idf term weighting in information retrieval , 2000, International Journal on Digital Libraries.

[205]  Fabio Crestani,et al.  Searching the web by constrained spreading activation , 2000, Inf. Process. Manag..

[206]  W. Kintsch Metaphor comprehension: A computational theory , 2000, Psychonomic bulletin & review.

[207]  Ed H. Chi,et al.  The scent of a site: a system for analyzing and predicting information scent, usage, and usability of a Web site , 2000, CHI.

[208]  L. Rips,et al.  The Psychology of Survey Response , 2000 .

[209]  Tony A. Plate,et al.  Analogy retrieval and processing with distributed vector representations , 2000, Expert Syst. J. Knowl. Eng..

[210]  Eleanor G. Rieffel,et al.  J an 2 00 0 An Introduction to Quantum Computing for Non-Physicists , 2002 .

[211]  R. Selten,et al.  Bounded rationality: The adaptive toolbox , 2000 .

[212]  Thomas D. Wilson,et al.  Human Information Behavior , 2000, Informing Sci. Int. J. an Emerg. Transdiscipl..

[213]  Stephen E. Robertson,et al.  A probabilistic model of information retrieval: development and comparative experiments - Part 2 , 2000, Inf. Process. Manag..

[214]  Djoerd Hiemstra,et al.  Relating the new language models of information retrieval to the traditional retrieval models , 2000 .

[215]  Iain Campbell,et al.  The ostensive model of developing information needs , 2000 .

[216]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[217]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[218]  Richard M. Schwartz,et al.  A hidden Markov model information retrieval system , 1999, SIGIR '99.

[219]  John R. Anderson,et al.  The fan effect: New results and new theories. , 1999 .

[220]  Fabio Crestani,et al.  WebSCSA: Web search by constrained spreading activation , 1999, Proceedings IEEE Forum on Research and Technology Advances in Digital Libraries.

[221]  Michael J. Witbrock,et al.  Improving the suitability of imperfect transcriptions for information retrieval from spoken documents , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[222]  D. Goldstein,et al.  How good are simple heuristics , 1999 .

[223]  J R Anderson,et al.  Practice and retention: a unifying analysis. , 1999, Journal of experimental psychology. Learning, memory, and cognition.

[224]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[225]  Stuart K. Card,et al.  Information foraging models of browsers for very large document spaces , 1998, AVI '98.

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

[227]  S. Glucksberg Understanding Metaphors , 1998 .

[228]  Walter Kintsch,et al.  Comprehension: A Paradigm for Cognition , 1998 .

[229]  Djoerd Hiemstra,et al.  Twenty-One at TREC7: Ad-hoc and Cross-Language Track , 1998, TREC.

[230]  W. Bruce Croft,et al.  A language modeling approach to information retrieval , 1998, SIGIR '98.

[231]  Peter W. Foltz,et al.  The Measurement of Textual Coherence with Latent Semantic Analysis. , 1998 .

[232]  Russell Beale,et al.  Applying connectionist models to information retrieval , 1998 .

[233]  Cyril Cleverdon,et al.  The Cranfield tests on index language devices , 1997 .

[234]  T. Landauer,et al.  A Solution to Plato's Problem: The Latent Semantic Analysis Theory of Acquisition, Induction, and Representation of Knowledge. , 1997 .

[235]  Dik Lun Lee,et al.  Document Ranking and the Vector-Space Model , 1997, IEEE Softw..

[236]  J. Fodor Connectionism and the problem of systematicity (continued): why Smolensky's solution still doesn't work , 1997, Cognition.

[237]  James Edward Pitkow,et al.  Characterizing World Wide Web ecologies , 1997 .

[238]  Frederick Jelinek,et al.  Statistical methods for speech recognition , 1997 .

[239]  Mimi Recker,et al.  Predicting document access in large multimedia repositories , 1996, TCHI.

[240]  Gloria Bordogna,et al.  A user-adaptive neural network supporting a rule-based relevance feedback , 1996, Fuzzy Sets Syst..

[241]  Chris Buckley,et al.  Pivoted Document Length Normalization , 1996, SIGIR Forum.

[242]  Katia Sycara,et al.  Learning Text Filtering Preferences , 1996 .

[243]  Graeme S. Halford,et al.  Solving Proportional Analogy Problems using Tensor Product Networks with Random Representations , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[244]  David J. C. MacKay,et al.  A hierarchical Dirichlet language model , 1995, Natural Language Engineering.

[245]  Gary Marchionini,et al.  Information Seeking in Electronic Environments , 1995 .

[246]  Stuart K. Card,et al.  Information foraging in information access environments , 1995, CHI '95.

[247]  Tony A. Plate,et al.  Holographic reduced representations , 1995, IEEE Trans. Neural Networks.

[248]  Stephen E. Robertson,et al.  Okapi at TREC-4 , 1995, TREC.

[249]  Carolyn J. Crouch,et al.  Associative and adaptive retrieval in a connectionist system , 1994 .

[250]  Pentti Kanerva,et al.  The Spatter Code for Encoding Concepts at Many Levels , 1994 .

[251]  E. Shafir Uncertainty and the difficulty of thinking through disjunctions , 1994, Cognition.

[252]  Quentin L. Burrell,et al.  A model for library book circulations incorporating loan periods , 1994 .

[253]  M. Dawson,et al.  Connectionism, Confusion and Cognitive Science , 1994 .

[254]  James E. Pitkow,et al.  Yet Robust Caching Algorithm Based on Dynamic Access Patterns , 1994, WWW Spring 1994.

[255]  Tony Plate,et al.  Estimating Analogical Similarity by Dot-Products of Holographic Reduced Representations , 1993, NIPS.

[256]  Yiyu Yao,et al.  Computation of term associations by a neural network , 1993, SIGIR.

[257]  R. Horton Rules and representations , 1993, The Lancet.

[258]  Anne Wilson,et al.  Linking Symbolic and Subsymbolic Computing , 1993 .

[259]  Janet Wiles,et al.  Parallel distributed processing approaches to creative reasoning: Tensor models of memory and analog , 1993 .

[260]  Nicholas J. Belkin,et al.  Interaction with Texts: Information Retrieval as Information-Seeking Behavior , 1993, Information Retrieval.

[261]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[262]  Arthur B. Markman,et al.  Analogy-- Watershed or Waterloo? Structural alignment and the development of connectionist models of analogy , 1992, NIPS 1992.

[263]  A. Tversky,et al.  Thinking through uncertainty: Nonconsequential reasoning and choice , 1992, Cognitive Psychology.

[264]  A. Tversky,et al.  The Disjunction Effect in Choice under Uncertainty , 1992 .

[265]  Andrew Jennings,et al.  A browser with a neural network user model , 1992 .

[266]  Peter Ingwersen,et al.  Information Retrieval Interaction , 1992 .

[267]  John R. Anderson,et al.  Reflections of the Environment in Memory Form of the Memory Functions , 2022 .

[268]  J. Kie,et al.  Foraging behavior by mule deer : the influence of cattle grazing , 1991 .

[269]  John R. Anderson Is human cognition adaptive? , 1991, Behavioral and Brain Sciences.

[270]  Kui-Lam Kwok,et al.  Query modification and expansion in a network with adaptive architecture , 1991, SIGIR '91.

[271]  Ross Wilkinson,et al.  Using the cosine measure in a neural network for document retrieval , 1991, SIGIR '91.

[272]  I. Gavanski,et al.  Representativeness and conjoint probability. , 1991, Journal of personality and social psychology.

[273]  Richard Reviewer-Granger Unified Theories of Cognition , 1991, Journal of Cognitive Neuroscience.

[274]  W. Bruce Croft,et al.  Evaluation of an inference network-based retrieval model , 1991, TOIS.

[275]  Geoffrey E. Hinton Tensor Product Variable Binding and the Representation of Symbolic Structures in Connectionist Systems , 1991 .

[276]  Geoffrey E. Hinton,et al.  Lesioning an attractor network: investigations of acquired dyslexia. , 1991, Psychological review.

[277]  Richard A. Harshman,et al.  Indexing by Latent Semantic Analysis , 1990, J. Am. Soc. Inf. Sci..

[278]  B. MacWhinney,et al.  The Child Language Data Exchange System: an update , 1990, Journal of Child Language.

[279]  John Cocke,et al.  A Statistical Approach to Machine Translation , 1990, CL.

[280]  J. Fodor,et al.  Connectionism and the problem of systematicity: Why Smolensky's solution doesn't work , 1990, Cognition.

[281]  Haruo Kimoto,et al.  Construction of a dynamic Thesaurus and its use for associated information retrieval , 1989, SIGIR '90.

[282]  John R. Anderson,et al.  Human memory: An adaptive perspective. , 1989 .

[283]  James L. McClelland,et al.  A distributed, developmental model of word recognition and naming. , 1989, Psychological review.

[284]  Kui-Lam Kwok A neural network for probabilistic information retrieval , 1989, SIGIR '89.

[285]  Jean,et al.  The Computer and the Brain , 1989, Annals of the History of Computing.

[286]  Marcia J. Bates,et al.  The design of browsing and berrypicking techniques for the online search interface , 1989 .

[287]  Richard K. Belew,et al.  Adaptive information retrieval: using a connectionist representation to retrieve and learn about documents , 1989, SIGIR '89.

[288]  W. Bruce Croft,et al.  Inference networks for document retrieval , 1989, SIGIR '90.

[289]  P. Smolensky THE CONSTITUENT STRUCTURE OF CONNECTIONIST MENTAL STATES: A REPLY TO FODOR AND PYLYSHYN , 2010 .

[290]  Jack M. Feldman,et al.  Self-generated validity and other effects of measurement on belief, attitude, intention, and behavior. , 1988 .

[291]  John R. Anderson,et al.  The place of cognitive architectures in a rational analysis , 1988 .

[292]  Gerard Salton,et al.  On the use of spreading activation methods in automatic information , 1988, SIGIR '88.

[293]  J. Fodor,et al.  Connectionism and cognitive architecture: A critical analysis , 1988, Cognition.

[294]  Karen Spärck Jones A Look Back and a Look Forward , 1988, SIGIR Forum.

[295]  James L. McClelland,et al.  James L. McClelland, David Rumelhart and the PDP Research Group, Parallel distributed processing: explorations in the microstructure of cognition . Vol. 1. Foundations . Vol. 2. Psychological and biological models . Cambridge MA: M.I.T. Press, 1987. , 1989, Journal of Child Language.

[296]  Patricia A. Herman,et al.  Breadth and depth of vocabulary knowledge: Implications for acquisition and instruction. , 1987 .

[297]  WILLIAM P. JONES,et al.  On the Applied Use of Human Memory Models: The Memory Extender Personal Filing System , 1986, Int. J. Man Mach. Stud..

[298]  G S Dell,et al.  A spreading-activation theory of retrieval in sentence production. , 1986, Psychological review.

[299]  W. P. Jones The memory extender personal filing system , 1986, CHI '86.

[300]  James L. McClelland,et al.  On learning the past-tenses of English verbs: implicit rules or parallel distributed processing , 1986 .

[301]  John R. Anderson,et al.  The role of practice in fact retrieval. , 1985 .

[302]  S. Presser,et al.  Questions and Answers in Attitude Surveys: Experiments on Question Form, Wording, and Context , 1996 .

[303]  R. Huey,et al.  Locomotor capacity and foraging behaviour of kalahari lacertid lizards , 1984, Animal Behaviour.

[304]  B. Bollobás The evolution of random graphs , 1984 .

[305]  P. Erdos,et al.  On the evolution of random graphs , 1984 .

[306]  John R. Anderson A spreading activation theory of memory. , 1983 .

[307]  Quentin L. Burrell,et al.  The Analysis of Library Data , 1982 .

[308]  William E. Nagy,et al.  The Number of Words in Printed School English. Technical Report No. 253. , 1982 .

[309]  John McCarthy,et al.  SOME PHILOSOPHICAL PROBLEMS FROM THE STANDPOINT OF ARTI CIAL INTELLIGENCE , 1987 .

[310]  Peretz Shoval Expert/Consultation System for a Retrieval Data-Base with Semantic Network of Concepts , 1981, SIGIR.

[311]  Scott Everett Preece A spreading activation network model for information retrieval , 1981 .

[312]  Richard F. Green,et al.  Bayesian birds: A simple example of Oaten's stochastic model of optimal foraging , 1980 .

[313]  John R. Searle,et al.  Minds, brains, and programs , 1980, Behavioral and Brain Sciences.

[314]  QUENTIN BURRELL,et al.  A Simple stochastic Model for Library loans , 1980, J. Documentation.

[315]  K. Waddington,et al.  Optimal Foraging: On Flower Selection by Bees , 1979, The American Naturalist.

[316]  A. Tversky Features of Similarity , 1977 .

[317]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[318]  Allen Newell,et al.  Computer science as empirical inquiry: symbols and search , 1976, CACM.

[319]  Allan Collins,et al.  A spreading-activation theory of semantic processing , 1975 .

[320]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[321]  G. Bower,et al.  Human Associative Memory , 1973 .

[322]  Manfred Kochen,et al.  On the economics of information , 1972, J. Am. Soc. Inf. Sci..

[323]  P. Bonacich Factoring and weighting approaches to status scores and clique identification , 1972 .

[324]  Allen Newell,et al.  Computer Structures: Readings and Examples, , 1971 .

[325]  Gerard Salton,et al.  The SMART Retrieval System—Experiments in Automatic Document Processing , 1971 .

[326]  Cyril W. Cleverdon,et al.  Factors determining the performance of indexing systems , 1966 .

[327]  D. Hebb Distinctive features of learning in the higher animal , 1961 .

[328]  C. W. Cleverdon,et al.  The ASLIB CRANFIELD RESEARCH PROJECT ON The COMPARATIVE EFFICIENCY OF INDEXING SYSTEMS , 1960 .

[329]  Allen Newell,et al.  The logic theory machine-A complex information processing system , 1956, IRE Trans. Inf. Theory.

[330]  H. Simon,et al.  ON A CLASS OF SKEW DISTRIBUTION FUNCTIONS , 1955 .

[331]  Zellig S. Harris,et al.  Distributional Structure , 1954 .

[332]  A. M. Turing,et al.  Computing Machinery and Intelligence , 1950, The Philosophy of Artificial Intelligence.

[333]  George Kingsley Zipf,et al.  Human behavior and the principle of least effort , 1949 .

[334]  D. Hebb,et al.  HUMAN BEHAVIOR AFTER EXTENSIVE BILATERAL REMOVAL FROM THE FRONTAL LOBES , 1940 .

[335]  M. Manosevitz,et al.  High-Speed Scanning in Human Memory , 2022 .