Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
Topic Identification in Dynamical Text by Complexity Pursuit
Neural Processing Letters
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Text classification by labeling words
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
A comparison of textual data mining methods for sex identification in chat conversations
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
A target oriented agent to collect specific information in a chat medium
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
Automatic turkish text categorization in terms of author, genre and gender
NLDB'06 Proceedings of the 11th international conference on Applications of Natural Language to Information Systems
Improving user experience with case-based reasoning systems using text mining and Web 2.0
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Mostly, the conversations taking place in chat mediums bear important information concerning the speakers. This information can vary in many fields such as tendencies, habits, attitudes, guilt situations, and intentions of the speakers. Therefore, analysis and processing of these conversations are of much importance. Many social and semantic inferences can be made from these conversations. In determining characteristics of conversations and analysis of conversations, subject designation can be grounded on. In this study, chat mining is chosen as an application of text mining, and a study concerning determination of subject in the Turkish text based chat conversations is conducted. In sorting the conversations, supervised learning methods are used in this study. As for classifiers, Naive Bayes, k-Nearest Neighbor and Support Vector Machine are used. Ninety-one percent success is achieved in determination of subject.