Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
Building a Recommender Agent for e-Learning Systems
ICCE '02 Proceedings of the International Conference on Computers in Education
Personalization technologies: a process-oriented perspective
Communications of the ACM - The digital society
WordNet-based User Profiles for Neighborhood Formation in Hybrid Recommender Systems
HIS '05 Proceedings of the Fifth International Conference on Hybrid Intelligent Systems
Using data mining as a strategy for assessing asynchronous discussion forums
Computers & Education
CinemaScreen Recommender Agent: Combining Collaborative and Content-Based Filtering
IEEE Intelligent Systems
User Modeling and User-Adapted Interaction
A recursive prediction algorithm for collaborative filtering recommender systems
Proceedings of the 2007 ACM conference on Recommender systems
HIS '07 Proceedings of the 7th International Conference on Hybrid Intelligent Systems
A Hybrid, Multi-dimensional Recommender for Journal Articles in a Scientific Digital Library
WI-IATW '07 Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
Semantic Organization of Online Discussion Transcripts for Active Collaborative Learning
ICALT '08 Proceedings of the 2008 Eighth IEEE International Conference on Advanced Learning Technologies
Expert Systems with Applications: An International Journal
A User Modeling Using Implicit Feedback for Effective Recommender System
ICHIT '08 Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology
Word sense disambiguation: A survey
ACM Computing Surveys (CSUR)
Developing argumentation processing agents for computer-supported collaborative learning
Expert Systems with Applications: An International Journal
Hybrid Content and Tag-based Profiles for Recommendation in Collaborative Tagging Systems
LA-WEB '08 Proceedings of the 2008 Latin American Web Conference
Personalized Web Service Ranking via User Group Combining Association Rule
ICWS '09 Proceedings of the 2009 IEEE International Conference on Web Services
Using Social Network to Predict the Behavior of Active Members of Online Communities
ASONAM '09 Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining
Collaborative Feature-Combination Recommender Exploiting Explicit and Implicit User Feedback
CEC '09 Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing
Combining learning and word sense disambiguation for intelligent user profiling
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Multi-model Ontology-Based Hybrid Recommender System in E-learning Domain
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Personalized Recommender Systems Integrating Social Tags and Item Taxonomy
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Tag Sense Disambiguation for Clarifying the Vocabulary of Social Tags
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
HIS '09 Proceedings of the 2009 Ninth International Conference on Hybrid Intelligent Systems - Volume 02
A recommender system for dynamically evolving online forums
Proceedings of the third ACM conference on Recommender systems
Exploring foundations for computer-supported collaborative learning
CSCL '02 Proceedings of the Conference on Computer Support for Collaborative Learning: Foundations for a CSCL Community
A personalized recommender system for digital libraries
Proceedings of the 14th Brazilian Symposium on Multimedia and the Web
Content-Based Filtering with Tags: The FIRSt System
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
A Framework for Tag-Based Research Paper Recommender System: An IR Approach
WAINA '10 Proceedings of the 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops
Improving the accuracy of tagging recommender system by using classification
ICACT'10 Proceedings of the 12th international conference on Advanced communication technology
Distributed recommender for peer-to-peer knowledge sharing
Information Sciences: an International Journal
Recommendations in Online Discussion Forums for E-Learning Systems
IEEE Transactions on Learning Technologies
User comments for news recommendation in forum-based social media
Information Sciences: an International Journal
Hybrid Product Recommender System for Apparel Retailing Customers
ICIE '10 Proceedings of the 2010 WASE International Conference on Information Engineering - Volume 01
Information Sciences: an International Journal
Information Sciences: an International Journal
IEEE Transactions on Consumer Electronics
A method for collaborative recommendation in document retrieval systems
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part II
Scaling up cosine interesting pattern discovery: A depth-first method
Information Sciences: an International Journal
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Recommender systems have been developed in variety of domains, including asynchronous discussion group which is one of the most interesting ones. Due to the information overload and its varieties in discussion groups, it is difficult to draw out the relevant information. Therefore, recommender systems play an important role in filtering and customizing the desired information. Nowadays, collaborative and content-based filtering are the most adopted techniques being utilized in recommender systems. The collaborative filtering technique recommends items based on liked-mind users' opinions and users' preferences. Alternatively, the aim of the content-based filtering technique is the identification of items which are similar to those a user has preferred in past. To overcome the drawbacks of the aforementioned techniques, a hybrid recommender system combines two or more recommendation techniques to obtain more accuracy. The most important achievement of this study is to present a novel approach in hybrid recommendation systems, which identifies the user similarity neighborhood from implicit information being collected in a discussion group. In the proposed system, initially the association rules mining technique is applied to discover the similar users, and then the related posts are recommended to them. To select the appropriate contents in the transacted posts, it is necessary to focus on the concepts rather than the key words. Therefore, to locate the semantic related concepts Word Sense Disambiguation strategy based on WordNet lexical database is exploited. The experiments carried out on the discussion group datasets proved a noticeable improvement on the accuracy of useful posts recommended to the users in comparison to content-based and the collaborative filtering techniques as well.