SeCoP 2016 - 3rd International Workshop on Semantic Computing and Personalization (SeCoP 2016)

As the development of World Wide Web, social networks, wikis and social tagging communities are becoming more and more popular. The above user-generated data gives a new ground to extend the focus of the Semantic Web by engaging it in other communities, where semantics can play an important role. Along with the interaction between users and computers, more and more personalized information are potentially mined from the Web by using semantic computing technology, such as ontology engineering for social network and personalization, mining user reviews, learners and courses modeling, user profiling in social network, sentiment analysis for user opinion mining and so on. Connecting semantic computing and personalized can enhance classic information management and retrieval approaches. It combines data mining with semantic computing as a promising direction and offers opportunities for developing novel algorithms and tools ranging from text and multimedia. In many scenarios of social networking, massive online open courses (MOOCs), social tags and wikis, semantic computing, personalization and recommendation are core functionalities.
The 3rd International Workshop on Semantic Computing and Personalization (SeCoP) in conjunction with DASFAA 2016 will bring together the academia, researchers and industrial practitioners from computer science, information systems, psychology, behavior science and organization science discipline, and provide a forum for recent advances in the field of semantic computing and personalization, from the perspectives of information management and mining.
AREAS OF INTEREST:
Topics of interest include, but are not limited to the exploitation of the Web of Data, the identification of semantics underlying social annotations of multimedia contents, and the application of semantic-based techniques and technologies in research fields related to (but not limited):
Content-based recommendation and collaborative filtering
Personalized content browsing and searching
Community extraction and exploitation
Social networks analysis for collaborative recommendation
User profile construction based on social tagging information
Context-aware personalized information access and delivery
Mobile and ubiquitous multimedia content access and delivery
Sentiment analysis and opinion mining
Micro-blog and Review content mining and analysis
Personalized and context-aware ontology
E-learning systems and learner profiling
Massive online open courseware and content modeling