Abstract/Description
Early work for unification of information extraction and data mining is motivational and problem stated work. This paper proposes a solution framework for unification using intelligent agents. A Relation manager agent extracted feature with cross feedback approach and also provide a Unified Undirected graphical handle. An RPM agent an approach to minimize loop back proposes pooling and model utilization with common parameter for both text and entity level abstractions.
Keywords
Data mining, Uncertainty, Hidden Markov models, Graphical models, Bayesian methods, Intelligent agent, Feature extraction, Feedback, Inference algorithms, Cleaning
Location
Crystal Ball Room A, Hotel Pearl Continental, Karachi, Pakistan
Session Theme
Database and Warehousing [DB-DW]
Session Type
Other
Session Chair
Dr. Beatriz De La Iglesia
Start Date
27-8-2005 3:35 PM
End Date
27-8-2005 3:55 PM
Recommended Citation
Imtiaz, S., Hussain, A., & Hiyat, D. (2005). Using Agents for Unification of Information Extraction and Data Mining. International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2005/2005/19
Using Agents for Unification of Information Extraction and Data Mining
Crystal Ball Room A, Hotel Pearl Continental, Karachi, Pakistan
Early work for unification of information extraction and data mining is motivational and problem stated work. This paper proposes a solution framework for unification using intelligent agents. A Relation manager agent extracted feature with cross feedback approach and also provide a Unified Undirected graphical handle. An RPM agent an approach to minimize loop back proposes pooling and model utilization with common parameter for both text and entity level abstractions.
