GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Recommending and evaluating choices in a virtual community of use
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
ACM Computing Surveys (CSUR)
Content-based book recommending using learning for text categorization
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Mineral identification using artificial neural networks and the rotating polarizer stage
Computers & Geosciences - Geological Applications of Digital Imaging
MovieLens unplugged: experiences with an occasionally connected recommender system
Proceedings of the 8th international conference on Intelligent user interfaces
Intelligent Systems for Tourism
IEEE Intelligent Systems
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
PocketLens: Toward a personal recommender system
ACM Transactions on Information Systems (TOIS)
An Online Recommender System for Large Web Sites
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
JQuery: finding your way through tangled code
OOPSLA '04 Companion to the 19th annual ACM SIGPLAN conference on Object-oriented programming systems, languages, and applications
Evaluating similarity measures: a large-scale study in the orkut social network
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Requirements engineering paper classification and evaluation criteria: a proposal and a discussion
Requirements Engineering
CinemaScreen Recommender Agent: Combining Collaborative and Content-Based Filtering
IEEE Intelligent Systems
Journal of the American Society for Information Science and Technology
A time-based approach to effective recommender systems using implicit feedback
Expert Systems with Applications: An International Journal
A novel collaborative filtering approach for recommending ranked items
Expert Systems with Applications: An International Journal
A web-page recommender system via a data mining framework and the Semantic Web concept
International Journal of Computer Applications in Technology
Evaluation of recommender systems: A new approach
Expert Systems with Applications: An International Journal
Rapid Prototyping of CBR Applications with the Open Source Tool myCBR
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
An iterative semi-explicit rating method for building collaborative recommender systems
Expert Systems with Applications: An International Journal
Collaborative filtering adapted to recommender systems of e-learning
Knowledge-Based Systems
The relation between Pearson's correlation coefficient r and Salton's cosine measure
Journal of the American Society for Information Science and Technology
Recommender system based on workflow
Decision Support Systems
A Survey of Accuracy Evaluation Metrics of Recommendation Tasks
The Journal of Machine Learning Research
A classification-based review recommender
Knowledge-Based Systems
Case Based Design: Applications in Process Engineering
Case Based Design: Applications in Process Engineering
WebPUM: A Web-based recommendation system to predict user future movements
Expert Systems with Applications: An International Journal
Good properties of similarity measures and their complementarity
Journal of the American Society for Information Science and Technology
Contextual recommendation of social updates, a tag-based framework
AMT'10 Proceedings of the 6th international conference on Active media technology
A recommender system based on tag and time information for social tagging systems
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Recommender Systems Handbook
Recommender Systems: An Introduction
Recommender Systems: An Introduction
Categorising social tags to improve folksonomy-based recommendations
Web Semantics: Science, Services and Agents on the World Wide Web
k-ATTRACTORS: A PARTITIONAL CLUSTERING ALGORITHM FOR NUMERIC DATA ANALYSIS
Applied Artificial Intelligence
Information Sciences: an International Journal
Collaborative user modeling with user-generated tags for social recommender systems
Expert Systems with Applications: An International Journal
Proposing a charting recommender system for second-language nurses
Expert Systems with Applications: An International Journal
One Dependence Value Difference Metric
Knowledge-Based Systems
On nonmetric similarity search problems in complex domains
ACM Computing Surveys (CSUR)
Rapid development of knowledge-based conversational recommender applications with advisor suite
Journal of Web Engineering
Engineering Applications of Artificial Intelligence
Collaborative filtering based on significances
Information Sciences: an International Journal
A recommender mechanism based on case-based reasoning
Expert Systems with Applications: An International Journal
Using AHP to determine intangible priority factors for technology transfer adoption
Expert Systems with Applications: An International Journal
Updating broken web links: An automatic recommendation system
Information Processing and Management: an International Journal
A collaborative filtering similarity measure based on singularities
Information Processing and Management: an International Journal
OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part II
Impact of data characteristics on recommender systems performance
ACM Transactions on Management Information Systems (TMIS)
Evaluation of a web recommender system in electronic and mobile tourism
International Journal of Web Engineering and Technology
Semantic inference of user's reputation and expertise to improve collaborative recommendations
Expert Systems with Applications: An International Journal
CBTV: visualising case bases for similarity measure design and selection
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
Reorganizing clouds: A study on tag clustering and evaluation
Expert Systems with Applications: An International Journal
Evaluating tag filtering techniques for web resource classification in folksonomies
Expert Systems with Applications: An International Journal
Mendel: Source code recommendation based on a genetic metaphor
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
A framework for collaborative filtering recommender systems
Expert Systems with Applications: An International Journal
Collective intelligence as mechanism of medical diagnosis: The iPixel approach
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Recommender systems provide personalized recommendations on products or services to user. The amount information handled by this type of systems is steadily growing. Furthermore, the development of recommendation systems is a difficult task due to the implementation of complex algorithms and metrics. For this reason, the success of recommendation systems depends on preliminary design decisions such as the most adequate similarity metric, the right process to infer proactive recommendations, for mentioning a few. This decision determines the process for generating recommendations and also impacts quality and user's satisfaction. In this paper, we propose RESYGEN, a Recommendation System Generator. RESYGEN allows the user to generate such kind of systems in an easy and friendly way. Furthermore, RESYGEN allows the generation of multi-domain systems such as music, video, books, travel, hardware, software, and food to mention a few. RESYGEN is based in the selection of the best distance metrics for nominal, ordinal, numeric and binary attributes, with the aim to reduce complexity for non-expert users and also to facilitate the selection of the metric which best fits to the data type. A system generated through RESYGEN has several interesting elements such as ratings, recommendations, cloud tag, among others. We performed a qualitative evaluation with the aim of comparing other recommender systems against systems generated by RESYGEN. The results shows that generated systems by RESYGEN, comprise the basic elements of a recommendation system.