The automatic identification of stop words
Journal of Information Science
C4.5: programs for machine learning
C4.5: programs for machine learning
The nature of statistical learning theory
The nature of statistical learning theory
Solving the multiple instance problem with axis-parallel rectangles
Artificial Intelligence
Selection of relevant features and examples in machine learning
Artificial Intelligence - Special issue on relevance
Machine Learning - Special issue on learning with probabilistic representations
Data preparation for data mining
Data preparation for data mining
A framework for multiple-instance learning
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Expert Systems and Probabiistic Network Models
Expert Systems and Probabiistic Network Models
Modern Information Retrieval
Instance Selection and Construction for Data Mining
Instance Selection and Construction for Data Mining
Machine Learning
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Machine Learning
Feature extraction by non parametric mutual information maximization
The Journal of Machine Learning Research
Consistency-based search in feature selection
Artificial Intelligence
Introduction to the special issue on word sense disambiguation: the state of the art
Computational Linguistics - Special issue on word sense disambiguation
Proceedings of the 16th international conference on World Wide Web
Combating Good Word Attacks on Statistical Spam Filters with Multiple Instance Learning
ICTAI '07 Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence - Volume 02
User Participation in Social Media: Digg Study
WI-IATW '07 Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Estimating the selectivity of tf-idf based cosine similarity predicates
ACM SIGMOD Record
Word sense disambiguation: A survey
ACM Computing Surveys (CSUR)
Supervised Machine Learning: A Review of Classification Techniques
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
A First Study on the Use of Coevolutionary Algorithms for Instance and Feature Selection
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
SMOTE: synthetic minority over-sampling technique
Journal of Artificial Intelligence Research
The foundations of cost-sensitive learning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
A Bayesian method for constructing Bayesian belief networks from databases
UAI'91 Proceedings of the Seventh conference on Uncertainty in Artificial Intelligence
IEEE Transactions on Information Technology in Biomedicine
OFFSS: optimal fuzzy-valued feature subset selection
IEEE Transactions on Fuzzy Systems
| Hi-index | 12.05 |
The use of the social web has brought a series of changes in the way how content is created. In particular, social news sites link stories and the different users can comment them. In this paper, we propose a new method based on different features extracted from the text able to categorise the comments. To this end, we use a combination of statistical, syntactic and opinion features and machine-learning classifiers to classify a comment within three different categorisation types: the focus of the comment, the type of information contained in the comment and the controversy level of the comment. We validate our approach with data from 'Meneame', a popular Spanish social news site.