A hybrid recommender system for the selective dissemination of research resources in a Technology Transfer Office

Recommender systems could be used to help users in their access processes to relevant information. Hybrid recommender systems represent a promising solution for multiple applications. In this paper we propose a hybrid fuzzy linguistic recommender system to help the Technology Transfer Office staff in the dissemination of research resources interesting for the users. The system recommends users both specialized and complementary research resources and additionally, it discovers potential collaboration possibilities in order to form multidisciplinary working groups. Thus, this system becomes an application that can be used to help the Technology Transfer Office staff to selectively disseminate the research knowledge and to increase its information discovering properties and personalization capacities in an academic environment.

[1]  Enrique Herrera-Viedma,et al.  Evaluating the information quality of Web sites: A methodology based on fuzzy computing with words: Special Topic Section on Soft Approaches to Information Retrieval and Information Access on the Web , 2006 .

[2]  Enrique Herrera-Viedma Modeling the retrieval process for an information retrieval system using an ordinal fuzzy linguistic approach , 2001 .

[3]  Enrique Herrera-Viedma,et al.  A Review on Information Accessing Systems Based on Fuzzy Linguistic Modelling , 2010 .

[4]  Sophie Ahrens,et al.  Recommender Systems , 2012 .

[5]  Enrique Herrera-Viedma,et al.  A model of an information retrieval system with unbalanced fuzzy linguistic information , 2007, Int. J. Intell. Syst..

[6]  David B. Balkin,et al.  Entrepreneurship and university-based technology transfer , 2005 .

[7]  Hyung Jun Ahn,et al.  A new similarity measure for collaborative filtering to alleviate the new user cold-starting problem , 2008, Inf. Sci..

[8]  John Riedl,et al.  An algorithmic framework for performing collaborative filtering , 1999, SIGIR '99.

[9]  Zhifeng Chen,et al.  On the fusion of multi-granularity linguistic label sets in group decision making , 2006, Comput. Ind. Eng..

[10]  Juan C. Burguillo,et al.  A hybrid content-based and item-based collaborative filtering approach to recommend TV programs enhanced with singular value decomposition , 2010, Inf. Sci..

[11]  Enrique Herrera-Viedma,et al.  Managing the consensus in group decision making in an unbalanced fuzzy linguistic context with incomplete information , 2010, Knowl. Based Syst..

[12]  Alina A. von Davier,et al.  Cross-Validation , 2014 .

[13]  Luis Martínez-López,et al.  A Consensus Support System Model for Group Decision-Making Problems With Multigranular Linguistic Preference Relations , 2005, IEEE Transactions on Fuzzy Systems.

[14]  G. Pasi,et al.  A Fuzzy Linguistic Approach Generalizing Boolean Information Retrieval: a Model and its Evaluation , 1993 .

[15]  Enrique Herrera-Viedma,et al.  Dealing with incomplete information in a fuzzy linguistic recommender system to disseminate information in university digital libraries , 2010, Knowl. Based Syst..

[16]  Anthony F. Norcio,et al.  Representation, similarity measures and aggregation methods using fuzzy sets for content-based recommender systems , 2009, Fuzzy Sets Syst..

[17]  Enrique Herrera-Viedma,et al.  Evaluating the informative quality of documents in SGML format from judgements by means of fuzzy linguistic techniques based on computing with words , 2003, Inf. Process. Manag..

[18]  Luis Martínez-López,et al.  An Adaptive Consensus Support Model for Group Decision-Making Problems in a Multigranular Fuzzy Linguistic Context , 2009, IEEE Transactions on Fuzzy Systems.

[19]  Mark Claypool,et al.  Combining Content-Based and Collaborative Filters in an Online Newspaper , 1999, SIGIR 1999.

[20]  Francisco Herrera,et al.  hg-index: a new index to characterize the scientific output of researchers based on the h- and g-indices , 2010, Scientometrics.

[21]  Badredine Arfi Fuzzy Decision Making in Politics: A Linguistic Fuzzy-Set Approach (LFSA) , 2005, Political Analysis.

[22]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning - II , 1975, Inf. Sci..

[23]  A. Link,et al.  Toward a model of the effective transfer of scientific knowledge from academicians to practitioners: qualitative evidence from the commercialization of university technologies. , 2004 .

[24]  Enrique Herrera-Viedma,et al.  Tuning the matching function for a threshold weighting semantics in a linguistic information retrieval system: Research Articles , 2005 .

[25]  E. Herrera‐Viedma,et al.  Evaluating the Informative Quality of Documents in SGML Format Using Fuzzy Linguistic Techniques Based on Computing with Words , 2001 .

[26]  Robert R. Korfhage,et al.  Information Storage and Retrieval , 1963 .

[27]  Francisco Herrera,et al.  A fusion approach for managing multi-granularity linguistic term sets in decision making , 2000, Fuzzy Sets Syst..

[28]  Gerhard Weikum,et al.  Social Wisdom for Search and Recommendation , 2008, IEEE Data Eng. Bull..

[29]  Mei-Hua Hsu,et al.  A personalized English learning recommender system for ESL students , 2008, Expert Syst. Appl..

[30]  David M. Pennock,et al.  Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments , 2001, UAI.

[31]  George Karypis,et al.  Item-based top-N recommendation algorithms , 2004, TOIS.

[32]  R. Veugelers,et al.  Licensing of University Inventions: The Role of a Technology Transfer Office , 2007 .

[33]  Guy Shani,et al.  Evaluating Recommendation Systems , 2011, Recommender Systems Handbook.

[34]  Enrique Herrera-Viedma,et al.  A model of an information retrieval system with unbalanced fuzzy linguistic information: Research Articles , 2007 .

[35]  Robin D. Burke,et al.  Hybrid Web Recommender Systems , 2007, The Adaptive Web.

[36]  L. A. ZADEH,et al.  The concept of a linguistic variable and its application to approximate reasoning - I , 1975, Inf. Sci..

[37]  Enrique Herrera-Viedma,et al.  Evaluating the information quality of Web sites: A methodology based on fuzzy computing with words , 2006, J. Assoc. Inf. Sci. Technol..

[38]  Francisco Herrera,et al.  Linguistic decision analysis: steps for solving decision problems under linguistic information , 2000, Fuzzy Sets Syst..

[39]  Francisco Herrera,et al.  Applying multi-objective evolutionary algorithms to the automatic learning of extended Boolean queries in fuzzy ordinal linguistic information retrieval systems , 2009, Fuzzy Sets Syst..

[40]  Enrique Herrera-Viedma,et al.  An improved recommender system to avoid the persistent information overload in a university digital library ∗ by , 2011 .

[41]  William W. Cohen,et al.  Recommendation as Classification: Using Social and Content-Based Information in Recommendation , 1998, AAAI/IAAI.

[42]  Peretz Shoval,et al.  Information Filtering: Overview of Issues, Research and Systems , 2001, User Modeling and User-Adapted Interaction.

[43]  Yoon Ho Cho,et al.  Collaborative filtering with ordinal scale-based implicit ratings for mobile music recommendations , 2010, Inf. Sci..

[44]  Duen-Ren Liu,et al.  A hybrid of sequential rules and collaborative filtering for product recommendation , 2009, Inf. Sci..

[45]  Francisco Herrera,et al.  A web based consensus support system for group decision making problems and incomplete preferences , 2010, Inf. Sci..

[46]  Enrique Herrera-Viedma,et al.  Modeling the retrieval process for an information retrieval system using an ordinal fuzzy linguistic approach , 2001, J. Assoc. Inf. Sci. Technol..

[47]  Enrique Herrera-Viedma,et al.  An Information Retrieval Model with Ordinal Linguistic Weighted Queries Based on Two Weighting Elements , 2001, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[48]  Javed Mostafa,et al.  An experiment in building profiles in information filtering: the role of context of user relevance feedback , 2002, Inf. Process. Manag..

[49]  Enrique Herrera-Viedma,et al.  A Model Based on Fuzzy Linguistic Information to Evaluate the Quality of Digital Libraries , 2010, Int. J. Inf. Technol. Decis. Mak..

[50]  Jian Ma,et al.  A method for group decision making with multi-granularity linguistic assessment information , 2008, Inf. Sci..

[51]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[52]  Herman Akdag,et al.  A tool for aggregation with words , 2009, Inf. Sci..

[53]  Enrique Herrera-Viedma,et al.  A recommender system for research resources based on fuzzy linguistic modeling , 2009, Expert Syst. Appl..

[54]  Oscar Cordón,et al.  A model of fuzzy linguistic IRS based on multi-granular linguistic information , 2003, Int. J. Approx. Reason..

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

[56]  Efendi N. Nasibov,et al.  An iterative approach for estimation of student performances based on linguistic evaluations , 2009, Inf. Sci..

[57]  Yukun Cao,et al.  An intelligent fuzzy-based recommendation system for consumer electronic products , 2007, Expert Syst. Appl..

[58]  Enrique Herrera-Viedma,et al.  A Fuzzy Linguistic IRS Model Based on a 2-Tuple Fuzzy Linguistic Approach , 2007, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[59]  A. Rosenfeld,et al.  IEEE TRANSACTIONS ON SYSTEMS , MAN , AND CYBERNETICS , 2022 .

[60]  Enrique Herrera-Viedma,et al.  A filtering and recommender system for e-scholars , 2010 .

[61]  Enrique Herrera-Viedma,et al.  A google wave-based fuzzy recommender system to disseminate information in University Digital Libraries 2.0 , 2011, Inf. Sci..

[62]  Long-Sheng Chen,et al.  Developing recommender systems with the consideration of product profitability for sellers , 2008, Inf. Sci..

[63]  John Riedl,et al.  Combining Collaborative Filtering with Personal Agents for Better Recommendations , 1999, AAAI/IAAI.

[64]  John Riedl,et al.  Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.

[65]  Robin D. Burke,et al.  Hybrid Recommender Systems: Survey and Experiments , 2002, User Modeling and User-Adapted Interaction.

[66]  Enrique Herrera-Viedma,et al.  A quality evaluation methodology for health-related websites based on a 2-tuple fuzzy linguistic approach , 2010, Soft Comput..

[67]  Francisco Herrera,et al.  Aggregation operators for linguistic weighted information , 1997, IEEE Trans. Syst. Man Cybern. Part A.

[68]  John Riedl,et al.  Analysis of recommendation algorithms for e-commerce , 2000, EC '00.

[69]  Francisco Herrera,et al.  A model based on linguistic 2-tuples for dealing with multigranular hierarchical linguistic contexts in multi-expert decision-making , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[70]  Paul Resnick,et al.  Recommender systems , 1997, CACM.

[71]  Ronald R. Yager,et al.  Fuzzy logic methods in recommender systems , 2003, Fuzzy Sets Syst..

[72]  Enrique Herrera-Viedma,et al.  Tuning the matching function for a threshold weighting semantics in a linguistic information retrieval system , 2005, Int. J. Intell. Syst..

[73]  Francisco Herrera,et al.  A 2-tuple fuzzy linguistic representation model for computing with words , 2000, IEEE Trans. Fuzzy Syst..

[74]  Jonathan L. Herlocker,et al.  Evaluating collaborative filtering recommender systems , 2004, TOIS.

[75]  Enrique Herrera-Viedma,et al.  A computer-supported learning system to help teachers to teach Fuzzy Information Retrieval Systems , 2009, Information Retrieval.

[76]  Enrique Herrera-Viedma,et al.  Recommending biomedical resources: A fuzzy linguistic approach based on semantic web , 2010 .

[77]  Panagiotis Symeonidis,et al.  Collaborative recommender systems: Combining effectiveness and efficiency , 2008, Expert Syst. Appl..

[78]  Michael Keen,et al.  ASLIB CRANFIELD RESEARCH PROJECT FACTORS DETERMINING THE PERFORMANCE OF INDEXING SYSTEMS VOLUME 2 , 1966 .

[79]  Francisco Herrera,et al.  Direct approach processes in group decision making using linguistic OWA operators , 1996, Fuzzy Sets Syst..

[80]  B. C. Brookes,et al.  Information Sciences , 2020, Cognitive Skills You Need for the 21st Century.

[81]  Francisco Herrera,et al.  Journal of Informetrics , 2022 .

[82]  由希 辻 Representation , 2020, The SAGE International Encyclopedia of Mass Media and Society.

[83]  Jie Lu,et al.  A linguistic intelligent user guide for method selection in multi-objective decision support systems , 2009, Inf. Sci..

[84]  Enrique Herrera-Viedma,et al.  Recommending biomedical resources: A fuzzy linguistic approach based on semantic web , 2010, Int. J. Intell. Syst..

[85]  Shih-Yuan Wang,et al.  Applying a direct multi-granularity linguistic and strategy-oriented aggregation approach on the assessment of supply performance , 2007, Eur. J. Oper. Res..