Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Measuring retrieval effectiveness based on user preference of documents
Journal of the American Society for Information Science
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Communications of the ACM
Fab: content-based, collaborative recommendation
Communications of the ACM
Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
Recommendation as classification: using social and content-based information in recommendation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Fast and effective text mining using linear-time document clustering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Content-based book recommending using learning for text categorization
DL '00 Proceedings of the fifth ACM conference on Digital libraries
A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Clustering Algorithms
Machine Learning
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
Text-Learning and Related Intelligent Agents: A Survey
IEEE Intelligent Systems
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Collaborative Filtering Using Weighted Majority Prediction Algorithms
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Refining Initial Points for K-Means Clustering
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Collaborative Learning and Recommender Systems
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Content-boosted collaborative filtering for improved recommendations
Eighteenth national conference on Artificial intelligence
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Improving collaborative recommender systems by means of user profiles
Designing personalized user experiences in eCommerce
Incorporating contextual information in recommender systems using a multidimensional approach
ACM Transactions on Information Systems (TOIS)
IEEE Transactions on Knowledge and Data Engineering
Combining learning and word sense disambiguation for intelligent user profiling
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Using measures of semantic relatedness for word sense disambiguation
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Word sense disambiguation for exploiting hierarchical thesauri in text classification
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
WordNet-Based word sense disambiguation for learning user profiles
EWMF'05/KDO'05 Proceedings of the 2005 joint international conference on Semantics, Web and Mining
Improving Social Filtering Techniques Through WordNet-Based User Profiles
UM '07 Proceedings of the 11th international conference on User Modeling
The JIGSAW Algorithm for Word Sense Disambiguation and Semantic Indexing of Documents
AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
Discovering User Profiles from Semantically Indexed Scientific Papers
From Web to Social Web: Discovering and Deploying User and Content Profiles
Adaptive Search Results Personalized by a Fuzzy Recommendation Approach
PIT '08 Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems
Integrating tags in a semantic content-based recommender
Proceedings of the 2008 ACM conference on Recommender systems
A Collaborative Approach to User Modeling for Personalized Content Recommendations
ICADL 08 Proceedings of the 11th International Conference on Asian Digital Libraries: Universal and Ubiquitous Access to Information
Web-Based Recommender Systems and User Needs --the Comprehensive View
Proceedings of the 2008 conference on New Trends in Multimedia and Network Information Systems
Combining learning and word sense disambiguation for intelligent user profiling
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Content-based recommendation services for personalized digital libraries
DELOS'07 Proceedings of the 1st international conference on Digital libraries: research and development
MARS: a MultilAnguage Recommender System
Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems
Layered evaluation of interactive adaptive systems: framework and formative methods
User Modeling and User-Adapted Interaction
ACM Transactions on Interactive Intelligent Systems (TiiS)
CCR: a content-collaborative reciprocal recommender for online dating
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Collaborative user modeling for enhanced content filtering in recommender systems
Decision Support Systems
A folksonomy-based recommender system for personalized access to digital artworks
Journal on Computing and Cultural Heritage (JOCCH)
Information Sciences: an International Journal
Recommendations using linked data
Proceedings of the 5th Ph.D. workshop on Information and knowledge
Personal ontologies: Generation of user profiles based on the YAGO ontology
Information Processing and Management: an International Journal
Personalized news recommendation using ontologies harvested from the web
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
Facing the cold start problem in recommender systems
Expert Systems with Applications: An International Journal
Folksonomy-based fuzzy user profiling for improved recommendations
Expert Systems with Applications: An International Journal
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Collaborative and content-based filtering are the recommendation techniques most widely adopted to date. Traditional collaborative approaches compute a similarity value between the current user and each other user by taking into account their rating style, that is the set of ratings given on the same items. Based on the ratings of the most similar users, commonly referred to as neighbors, collaborative algorithms compute recommendations for the current user. The problem with this approach is that the similarity value is only computable if users have common rated items. The main contribution of this work is a possible solution to overcome this limitation. We propose a new content-collaborative hybrid recommender which computes similarities between users relying on their content-based profiles, in which user preferences are stored, instead of comparing their rating styles. In more detail, user profiles are clustered to discover current user neighbors. Content-based user profiles play a key role in the proposed hybrid recommender. Traditional keyword-based approaches to user profiling are unable to capture the semantics of user interests. A distinctive feature of our work is the integration of linguistic knowledge in the process of learning semantic user profiles representing user interests in a more effective way, compared to classical keyword-based profiles, due to a sense-based indexing. Semantic profiles are obtained by integrating machine learning algorithms for text categorization, namely a naïve Bayes approach and a relevance feedback method, with a word sense disambiguation strategy based exclusively on the lexical knowledge stored in the WordNet lexical database. Experiments carried out on a content-based extension of the EachMovie dataset show an improvement of the accuracy of sense-based profiles with respect to keyword-based ones, when coping with the task of classifying movies as interesting (or not) for the current user. An experimental session has been also performed in order to evaluate the proposed hybrid recommender system. The results highlight the improvement in the predictive accuracy of collaborative recommendations obtained by selecting like-minded users according to user profiles.