Answer Garden: a tool for growing organizational memory
COCS '90 Proceedings of the ACM SIGOIS and IEEE CS TC-OA conference on Office information systems
Answer Garden 2: merging organizational memory with collaborative help
CSCW '96 Proceedings of the 1996 ACM conference on Computer supported cooperative work
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Graph-based ranking algorithms for e-mail expertise analysis
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Expertise identification using email communications
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Finding experts in community-based question-answering services
Proceedings of the 14th ACM international conference on Information and knowledge management
Formal models for expert finding in enterprise corpora
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Expertise networks in online communities: structure and algorithms
Proceedings of the 16th international conference on World Wide Web
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
QuME: a mechanism to support expertise finding in online help-seeking communities
Proceedings of the 20th annual ACM symposium on User interface software and technology
Knowledge sharing and yahoo answers: everyone knows something
Proceedings of the 17th international conference on World Wide Web
Automatic generation of concept hierarchies using WordNet
Expert Systems with Applications: An International Journal
Non-local evidence for expert finding
Proceedings of the 17th ACM conference on Information and knowledge management
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
OSS: a semantic similarity function based on hierarchical ontologies
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
A recommender system for dynamically evolving online forums
Proceedings of the third ACM conference on Recommender systems
A method to automatically construct a user knowledge model in a forum environment
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Recommendations in Online Discussion Forums for E-Learning Systems
IEEE Transactions on Learning Technologies
The ContactFinder agent: answering bulletin board questions with referrals
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
TRUSTCOM '11 Proceedings of the 2011IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications
Information seeking in social context: structural influences andreceipt of information benefits
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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Currently, online forums have become one of the most popular collaborative tools on the Internet where people are free to express their opinions. Forums supply facilities for knowledge management in which, their members can share their knowledge with each other. In this regard, The main problem regarding to the knowledge sharing on forums is the extensive amount of data on them without any mechanism to determine their validity. So, for knowledge seekers, knowing the expertise level of each member in a specific context is important in order to find valid answers. In this research, a novel algorithm is proposed to determine people's expertise level based on the context. AskMe forum is chosen for the evaluation process of the proposed method and its data has been processed in several stages. First of all, a special crawling program is developed to gather data from AskMe forum. Then, raw data is extracted, transformed, and loaded into a designed database using SQL server integration services. Afterwards, people's expertise level for specified context is calculated by applying the proposed method on the processed data. Finally, evaluation tests are applied in order to calculate the accuracy of the proposed method and compare it with other methods.