Hierarchical Text Classification and Evaluation
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Document Indexing With a Concept Hierarchy
NDDL '01 Proceedings of the 1st International Workshop on New Developments in Digital Libraries: n conjunction with ICEIS 2001
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
The Google Similarity Distance
IEEE Transactions on Knowledge and Data Engineering
Graph-based Knowledge Representation: Computational Foundations of Conceptual Graphs
Graph-based Knowledge Representation: Computational Foundations of Conceptual Graphs
Exploiting Linked Data to Build Web Applications
IEEE Internet Computing
Towards Exploratory Video Search Using Linked Data
ISM '09 Proceedings of the 2009 11th IEEE International Symposium on Multimedia
Referral based expertise search system in a time evolving social network
Proceedings of the Third Annual ACM Bangalore Conference
Automatic Construction of Domain Concept Hierarchy
CYBERC '10 Proceedings of the 2010 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery
Beyond the social search: personalizing the semantic search in social networks
OCSC'11 Proceedings of the 4th international conference on Online communities and social computing
Towards automatic concept hierarchy generation for specific knowledge network
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
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Social networks are in constant growth, here users share all kind of information such as news, pictures and their personal opinions about different topics. In order to a user can retrieve such content for a topic of interest, it must provide the terms believed to occur in the posts; but in a matter of semantics, this tends to leave out relevant results. This paper proposes an approach to perform semantic classification of posts in social networks using concept hierarchies (CH). This classification is considered as a first step towards semantic searching. In addition, a method to obtain a CH for a particular subject is also proposed. With the implementation of this approach, the obtained results reflect what it seems to be a so promising approach, obtaining more than 64% of accuracy on the F-measure.