%Original file available from http://www.cs.odu.edu/~jbollen/bibliographies/bibtex/IR_RS.bib %Last update: Thursday 16 June 2005 %Current number of entries: 41 @inproceedings{linkpr:hunag2005, title = {Link Prediction Approach to Collaborative Filtering}, author = {Zan Huang and Xin Li and Hsinchun Chen}, year = 2005, booktitle = {{P}roceedings of the {J}oint {C}onference on {D}igital {L}ibraries ({JCDL05})}, month = {June}, location = {Denver, CO}, publisher = {{ACM}}, address = {Denver, CO}, } @inproceedings{spread:ziegler2004, title = {Spreading Activation Models for Trust Propagation}, author = {Cai-Nicolas Ziegler and Georg Lausen}, year = 2004, booktitle = {{P}roceedings of the 2004 {IEEE} {I}nternational {C}onference on e-{T}echnology, e-{C}ommerce and e-{S}ervice ({EEE}04)}, location = {Taipei, Taiwan}, pages = {83--97}, publisher = {{IEEE}}, } @inproceedings{webper:albanese2004, title = {Web Personalization Based on Static Information and Dynamic User Behavior}, author = {Massimiliano Albanese}, year = 2004, booktitle = {Proceedings of the 6th {ACM} international workshop on {W}eb {I}nformation and {D}ata {M}anagement ({WIDM04})}, location = {Washington, DC}, publisher = {ACM Press}, } @article{usingd:masseglia1999, author = {F. Masseglia and P. Poncelet and M. Teisseire}, title = {Using data mining techniques on Web access logs to dynamically improve hypertext structure}, journal = {SIGWEB Newsletter}, volume = {8}, number = {3}, year = {1999}, pages = {13--19}, doi = {http://80-doi.acm.org.proxy.lib.odu.edu/10.1145/951440.951443}, publisher = {ACM Press}, } @inproceedings{evalua:gery2003, author = {Mathias Gery and Hatem Haddad}, title = {Evaluation of web usage mining approaches for user's next request prediction}, booktitle = {Proceedings of the 5th ACM international workshop on Web information and data management}, year = {2003}, isbn = {1-58113-725-7}, pages = {74--81}, location = {New Orleans, Louisiana, USA}, doi = {http://80-doi.acm.org.proxy.lib.odu.edu/10.1145/956699.956716}, publisher = {ACM Press}, } @inproceedings{clicks:kim2004, title = {A Clickstream-Based Collaborative Filtering Personalization Model: Towards A Better Performance}, author = {Dong-Ho Kim and Il Im and Nabil Adam and Vijayalakshmi Atluri and Michael Bieber and Yelena Yesha}, year = 2004, booktitle = {Proceedings of the 6th {ACM} International Workshop on {W}eb {I}nformation and {D}ata {M}anagement ({WIDM} 2004)}, month = {November}, address = {Washington, DC}, year = 2004, } @article{automa:mobasher2000, author = {Bamshad Mobasher and Robert Cooley and Jaideep Srivastava}, title = {Automatic personalization based on Web usage mining}, journal = {Communication of the {ACM}}, volume = {43}, number = {8}, year = {2000}, issn = {0001-0782}, pages = {142--151}, doi = {http://80-doi.acm.org.proxy.lib.odu.edu/10.1145/345124.345169}, publisher = {ACM Press}, } @inproceedings{analys:jones1998, title = {An Analysis of Usage of a Digital Library}, author = {Steve Jones and Sally Jo Cunningham and Rodger J. McNab}, year = 1998, booktitle = {{E}uropean {C}onference on {D}igital {L}ibraries}, editor = {Christos Nikolaou and Constantine Stephanidis}, publisher = {Springer}, month = {September}, pages = {261--277}, } @article{combin:he2002, author = {Daqing He and Ayse G\&\#246;ker and David J. Harper}, title = {Combining evidence for automatic web session identification}, journal = {Inf. Process. Manage.}, volume = {38}, number = {5}, year = {2002}, issn = {0306-4573}, pages = {727--742}, doi = {http://dx.doi.org/10.1016/S0306-4573(01)00060-7}, publisher = {Pergamon Press, Inc.}, } @inproceedings{predic:chen2002, author = {Mao Chen and Andrea S. LaPaugh and Jaswinder Pal Singh}, title = {Predicting category accesses for a user in a structured information space}, booktitle = {Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval}, year = {2002}, isbn = {1-58113-561-0}, pages = {65--72}, location = {Tampere, Finland}, publisher = {ACM Press}, } @article{evalua:herlocker2004, author = {Jonathan L. Herlocker and Joseph A. Konstan and Loren G. Terveen and John T. Riedl}, title = {Evaluating collaborative filtering recommender systems}, journal = {ACM Trans. Inf. Syst.}, volume = {22}, number = {1}, year = {2004}, issn = {1046-8188}, pages = {5--53}, doi = {http://80-doi.acm.org.proxy.lib.odu.edu/10.1145/963770.963772}, publisher = {ACM Press}, } @article{applyi:huang2004, author = {Zan Huang and Hsinchun Chen and Daniel Zeng}, title = {Applying associative retrieval techniques to alleviate the sparsity problem in collaborative filtering}, journal = {ACM Trans. Inf. Syst.}, volume = {22}, number = {1}, year = {2004}, issn = {1046-8188}, pages = {116--142}, doi = {http://doi.acm.org/10.1145/963770.963775}, publisher = {ACM Press}, } @inproceedings{itemba:sarwar2001, author = {Badrul Sarwar and George Karypis and Joseph Konstan and John Reidl}, title = {Item-based collaborative filtering recommendation algorithms}, booktitle = {Proceedings of the {T}enth {I}nternational {C}onference on {W}orld {W}ide {W}eb}, year = {2001}, isbn = {1-58113-348-0}, pages = {285--295}, location = {Hong Kong, Hong Kong}, doi = {http://80-doi.acm.org.proxy.lib.odu.edu/10.1145/371920.372071}, publisher = {ACM Press}, } @ARTICLE{protot:hwang2003, author = {San-Yih Hwang and Wen-Chiang Hsiung and Wan-Shiou Yang}, title = {A prototype {WWW} literature recommendation system for digital libraries}, year = 2003, journal = {Online Information Review}, volume = 27, number = 3, pages = {169--182}, abstract = {This article describes a service for providing literature recommendations, which is part of a networked digital library project whose principal goal is to develop technologies for supporting digital services. The proposed literature recommendation system makes use of the Web usage logs of a literature digital library. The recommendation framework consists of three sequential steps: data preparation of the Web usage log, discovery of article associations, and article recommendations. We discuss several design alternatives for conducting these steps. These alternatives are evaluated using the Web logs of our university's electronic thesis and dissertation (ETD) system. The proposed literature recommendation system has been incorporated into our university's ETD system, and is currently operational}, } @inproceedings{effect:ioannou2000, author = {S. Ioannou and G. Moschovitis and K. Ntalianis and K. Karpouzis and S. Kollias}, title = {Effective access to large audiovisual assets based on user preferences}, booktitle = {Proceedings of the 2000 {ACM} workshops on multimedia}, year = {2000}, isbn = {1-58113-311-1}, pages = {227--232}, location = {Los Angeles, California, United States}, URL = {http://netserv.lib.odu.edu:2131/10.1145/357744.357948}, publisher = {ACM Press}, } @ARTICLE{i3r:croft1987, title = {I3R: A new approach to the design of document retrieval systems}, author = {W. B. Croft and R. H. Thompson}, journal = {Journal of the American Society for Information Science}, volume = 38, number = 6, year = 1987, pages = {389--404}, abstract={The most effective method of improving the retrieval performance of a document retrieval system is to acquire a detailed specification of the user's information need. The system described in this article, I3R, provides a number of facilities and search strategies based on this approach. The system uses a novel architecture to allow more than one system facility to be used at a given stage of a search session. Users influence the system actions by stating goals they wish to achieve, by evaluating system output, and by choosing particular facilities directly. The other main features of I3R are an emphasis on domain knowledge used for refining the model of the information need, and the provision of a browsing mechanism that allows the user to navigate through the knowledge base.}, } @ARTICLE{classi:juntae1993, title = {Classification and retrieval of knowledge on a parallel marker-passing architecture}, author = {Kim Jun-Tae and D. I. Moldovan}, year = 1993, pages = {753 -- 761}, volume = 5, issue = 5, journal = {IEEE Transactions on Knowledge and Data Engineering}, abstract = {Frame-based systems or semantic networks have been generally used for knowledge representation. In such a knowledge representation system, concepts in the knowledge base are organized based on the subsumption relation between concepts, and classification is a process of constructing a concept hierarchy according to the subsumption relationships. Since the classification process involves search and subsumption test between concepts, classification on a large knowledge base may become unacceptably slow, especially for real-time applications. In this paper, a massively parallel classification and property retrieval algorithm on a marker passing architecture is presented. The subsumption relation is first defined by using the set relationship, and the parallel classification algorithm is described based on that relationship. In this algorithm, subsumption test between two concepts is done by parallel marker passing and multiple subsumption tests are performed simultaneously. To investigate the performance of the algorithm, time complexities of sequential and parallel classification are compared. Simulation of the parallel classification algorithm was performed using the SNAP (Semantic Network Array Processor) simulator, and the influence of several factors on the execution time is discussed.}, } @ARTICLE{bayesi:savoy1992, author = {J. Savoy}, title = {Bayesian-inference networks and spreading activation in hypertext systems}, year = 1992, journal = {Information Processing and Management}, volume = 28, number = 3, pages = {389--406}, abstract = {Browsing is the foremost method in searching through information in a hypertext or hypermedia system. However, as the number of nodes and links increases, this technique is far from satisfactory, and other search mechanisms must be provided. Classical search techniques such as menu selection hierarchies, string matching, Boolean query, etc., are already available, but they treat nodes as independent entities rather than considering the link semantics between nodes. Moreover, in order to write a query the users often encounter many problems such as how to find the appropriate terms that describe the information needs, how to correctly write a query in a language using artificial syntax, etc. This paper describes an alternative based on a Bayesian network that structures the indexing terms and stores the user's information needs. In our approach, the user does not have to write a formal query because the computation required is accomplished automatically and without any prior information or constraint. Moreover, using a constrained spreading activation, our solution uses link semantics to search relevant starting points for browsing.}, } @ARTICLE{querym:boughanem1997, title = {Query modification based on relevance back-propagation in an ad hoc environment}, author = {M. Boughanem and C. Chrisment and C. SouleDupuy}, year = 1999, journal = {Information Processing and Management}, volume = 35, number = 2, pages = {121 -- 139}, month = {March}, } @INPROCEEDINGS{search:yuwono1996, author = {B. Yuwono and D. L. Lee}, title = {Search and ranking algorithms for locating resources on the World Wide Web}, year = 1996, booktitle = {Proceedings of the {T}welfth {I}nternational {C}onference on {D}ata {E}ngineering}, editor = {S.Y.W. Su}, volume = 1996, number = 2602, pages = {164 -- 171}, address = {New Orleans, LA}, publisher = {IEEE}, } @ARTICLE{inform:cohen1987, author = {Paul R. Cohen and Rick Kjeldsen}, title = {Information Retrieval by Constrained Spreading Activation in Semantic Networks}, year = 1987, journal = {Information Processing and Management}, volume = 23, number = 4, pages = {255--268}, abstract = {GRANT is an expert system for finding sources of funding given research proposals. Its search method - constrained spreading activation - makes inferences about the goals of the user and thus fins information that the user did not explicitly request but is likely to find useful. The architecture of GRANT and the implementation of CSA are described, and GRANT's performance is evaluated}, } @ARTICLE{inform:lucarella1993, author = {D. Lucarella and A. Zanzi}, title = {Information Retrieval from Hypertext: an Approach using Plausible Inference}, year = 1993, journal = {Information Processing and Management}, volume = 29, number = 3, pages = {299--312}, abstract = {The authors discuss a method of applying inference to a hypertext network that is regarded as an inference network where nodes are propositions and links rules. A spreading activation technique is discussed and evaluated for these networks}, } @ARTICLE{retrie:croft1993, author = {W. Bruce Croft and Howard R. Turtle}, title = {Retrieval Strategies for Hypertext}, year = 1993, journal = {Information Processing and Management}, volume = 29, number = 3, pages = {313--324}, abstract = {Croft and Turtle demonstrate a method using inference networks for retrieval from hypertext networks, and show that it is equivalent to using spreading activation in terms of retrieval efficiency}, } @INPROCEEDINGS{enhanc:woodruff2000, title = {Enhancing a digital book with a reading recommender}, author = {Allison Woodruff and Rich Gossweiler and James Pitkow and Ed H. Chi and Stuart K. Card}, year = 2000, booktitle = {Proceedings of the {CHI} 2000 conference on {H}uman {F}actors in {C}omputing {S}ystems}, conference = {Conference on Human Factors and Computing Systems}, pages = {153--160}, month = {April}, address = {The Hague, Netherlands}, } @INPROCEEDINGS{usespr:salton1988, author = {G. Salton and C. Buckley}, title = {On the use of spreading activation methods in automatic information retrieval}, year = 1988, booktitle = {Proceedings of the 11th {I}nternational {C}onference on {R}esearch and {D}evelopment in {I}nformation {R}etrieval}, month = {June}, conference = {Annual {ACM} Conference on Research and Development in Information Retrieval}, pages = {147--160}, address = {Grenoble, France}, abstract = {Spreading activation methods have been recommended in information retrieval to expand the search vocabulary and to complement the retrieved document sets. The spreading activation strategy is reminiscent of earlier associative indexing and retrieval systems. Some spreading activation procedures are briefly described, and evaluation output is given, reflecting the effectiveness of one of the proposed procedures.}, } @INPROCEEDINGS{contex:lee1999, title = {Context-sensitive vocabulary mapping with a spreading activation network}, author = {Jonghoon Lee and David Dubin}, year = 1999, booktitle = {Proceedings on the 22nd annual international ACM SIGIR conference on Research and development in information retrieval}, conference = {Annual ACM Conference on Research and Development in Information Retrieval}, address = {Berkeley, Ca}, month = {August}, pages={198--205}, } @ARTICLE{search:crestani2000, author = {Fabio Crestani and Puay Leng Lee}, title = {Searching the web by constrained spreading activation}, journal = {Information Processing and Management}, volume = 36, number = 4, year = 2000, pages = {585--605}, } @ARTICLE{applic:crestani1997, author = {Fabio Crestani}, year = 1997, title = {Application of Spreading Activation Techniques in Information Retrieval}, journal = {Artificial Intelligence Review}, volume = 11, number = 6, pages = {453--582} } @INPROCEEDINGS{silkfr:pirolli1996, author = {Peter Pirolli and James Pitkow and Ramana Rao}, month = {April}, year = 1996, title = {Silk from a sow's ear: Extracting usable structure from the web}, booktitle = {Proceedings of {CHI}'96 {(ACM)}, {H}uman {F}actors in {C}omputing {S}ystems}, address = {Vancouver, Canada}, organization = {ACM} } @PHDTHESIS{eviden:rocha1997, author = {Luis M. Rocha}, title = {Evidence Sets and Contextual Genetic Algorithms: Exploring Uncertainty, Context and Embodiment in Cognitive and Biological Systems}, year = 1997, school = {State University of New York}, address = {Binghamton}, } @INPROCEEDINGS{talkmi:rocha1999, author = {Luis Mateus Rocha}, month = {August}, year = 1999, title = {TalkMine and the Adaptive Recommendation Project}, booktitle = {Proceedings of ACM Digital Libraries 99}, address = {Berkeley, California} } @ARTICLE{catego:rocha1998, author = {Luis Mateus Rocha}, title = {Categorizing Databases, Evidence Sets, and Evolutionary Constructivism}, journal = {International Journal of Human-Machine Studies}, year = 1998, publisher = {in Press}, } @ARTICLE{provid:harvey1998, author = {Clare F. Harvey and Peter Smith and Peter Lund}, title = {Providing a networked future for interpersonal information retrieval: InfoVine and user modeling}, journal = {Interacting with Computers}, year = 1998, volume = {10}, pages = {195--212}, publisher = {Elsevier}, abstract = {This paper presents system that for each user stores a retrieval log, and a interest and expertise log. Interests are derived from queries, expertise from retrievals. A database is constructed containing this data that all users of the system can search, thereby implementing a word-of-mouth functionality. Users can edit their own profiles.} } @ARTICLE{recomm:resnick1997, author = {Paul Resnick and Hal R. Varian}, title = {Recommender Systems}, journal = {Communications of the ACM}, year = 1997, month = {March}, volume = {40}, issue = {3}, pages = {56--58}, publisher = {ACM}, } @ARTICLE{adapti:rocha2000, author = {Luis Mateus Rocha}, title = {Adaptive Recommendation and Open-Ended Semiosis}, journal = {International Journal of Human-Computer Studies}, volume = {In Press}, year = {2000}, } @INCOLLECTION{adapti2:rocha2000, author = {Luis M. Rocha}, year = {2000}, title = {Adaptive recommendation driven by measures of uncertainty}, booktitle = {Soft Computing Agents: New Trends for Designing Autonomous Systems - Studies in Fuzziness and Soft Computing}, editor = {V. Loia}, publisher = {Physica-Verlag, Springer}, type = {In Press}, } @INPROCEEDINGS{recomm:schafer1999, author = {J. Ben Schafer and Joseph Konstan and John Riedl}, title = {Recommender systems in e-commerce}, year = 1999, booktitle = {Proceedings of the first {ACM} {C}onference on {E}lectronic {C}ommerce}, month = {November 3-5}, address = {Denver, CO}, pages = {158-166}, } @ARTICLE{groupl:konstan1997, author = {Joseph A. Konstan and Bradley N. Miller and David Maltz and Jonathan L. Herlocker and Lee R. Gordon and John Riedl}, title = {GroupLens: applying collaborative filtering to Usenet news}, year = {1997}, journal = {Communications of the ACM}, volume = {40}, number = {3}, pages = {77--87}, } @INPROCEEDINGS{implic:nichols1997, author = {David M. Nichols}, title = {Implicit Rating and Filtering}, year = 1997, booktitle = {Proceedings of the 5th {DELOS} on {F}iltering and {C}ollaborative {F}iltering}, address = {Budapest, Hungary}, month = {November}, pages = {31--36}, } @INPROCEEDINGS{algori:herlocker1999, author = {Jonathan L. Herlocker and Joseph A. Konstan and Al Borchers and John Riedl}, title = {An algorithmic framework for performing collaborative filtering}, year = {1999}, booktitle = {Proceedings on the 22nd {A}nnual {I}nternational {ACM} {SIGIR} {C}onference on {R}esearch and {D}evelopment in {I}nformation {R}etrieval}, month = {August 15--19}, address = {Berkeley, CA}, pages = {230--237}, } @INPROCEEDINGS{social:shardanand1995, author = {Upendra Shardanand and Pattie Maes}, title= {Social information filtering: algorithms for automating "word of mouth"}, booktitle = {{ACM} {C}onference {P}roceedings on {H}uman {F}actors in {C}omputing {S}ystems}, month = {May 7-11}, year = {1995}, address = {Denver, CO}, pages = {210-217}, } @INPROCEEDINGS{analys:sarwar2000, title = {Analysis of recommendation algorithms for e-commerce}, author = {Badrul M. Sarwar and George Karypis and Joseph A. Konstan and John Riedl}, booktitle = {ACM Conference on Electronic Commerce}, year = 2000, pages = {158--167}, address = {Minneapolis, MN}, publisher = {{ACM}}, month = {October} }