Refine your search
Collections
Co-Authors
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Menaka, P.
- Identification of Semantic Relation for Disease-Treatment Using Machine Learning Approach
Abstract Views :183 |
PDF Views:1
Authors
P. Menaka
1,
D. Thilagavathy
1
Affiliations
1 Department of Computer Science and Engineering, Adhiyamman College of Engineering, Hosur, Tamil Nadu, IN
1 Department of Computer Science and Engineering, Adhiyamman College of Engineering, Hosur, Tamil Nadu, IN
Source
Data Mining and Knowledge Engineering, Vol 4, No 4 (2012), Pagination: 155-158Abstract
The Machine Learning (ML) is almost used in any domain of research and now it has become a reliable tool in the medical domain.ML is a tool by which medical field is integrated with the computer based systems to provide more efficient medical care. The main objective of this work is to show what Natural Language Processing (NLP) and Machine Learning (ML) techniques used for representation of information and what classification algorithms are suitable for identifying and classifying relevant medical information in short texts. It is difficult task to identify the informative sentences in fields such as summarization and information extraction. The work and contribution value with this task is helpful in results and in settings for this task in healthcare field. It provides classification of disease, its cure and prevention. It acknowledges the fact that tools capable of identifying reliable information in the medical domain stand as building blocks for a healthcare system that is up-to-date with the latest discoveries. In this research, it focuses on diseases and treatment information, and the relation that exists between these two entities.Keywords
Machine Learning, Classification, NLP.- Review on Web Usage Mining and Data Preprocessing Techniques
Abstract Views :188 |
PDF Views:4
Authors
Affiliations
1 Department of Information Technology, Dr. N.G.P. Arts and Science College, IN
1 Department of Information Technology, Dr. N.G.P. Arts and Science College, IN
Source
Data Mining and Knowledge Engineering, Vol 10, No 1 (2018), Pagination: 12-14Abstract
The popularity of World Wide Web is increasing day by day by allowing peoples to share/ transfer their information to multiple sites. WWW becomes the most popular source for containing most information from the various peoples from different locations. Search engines are most useful tool which enables users to retrieve their required contents from the websites. However retrieval of more related contents for the users would be more difficult task which is resolved by using the web mining concepts. Web mining is nothing but integration of data mining techniques with the WWW to retrieve the most useful information required by the users. There are various methodologies are proposed by different authors to perform web mining in the effective way. In this analysis work, different methodologies proposed by various authors are discussed in terms of their working procedure along with their merits and demerits.Keywords
Web Mining, Useful Information, Data Mining, World Wide Web, Search Engine.References
- Sunena; Kamaljit Kaur, “Web usage mining-current trends and future challenges”, 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), Pages: 1409 - 1414, 2016
- Dhandi, M., & Chakrawarti, R. K. (2016, March). A comprehensive study of web usage mining. In Colossal Data Analysis and Networking (CDAN), Symposium on (pp. 1-5). IEEE
- Zdravko Markov, Daniel T. Larose "Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage", Wiley, 2007
- Yan LI, Boqin FENG and Qinjiao MAO, “Research on Path Completion Technique in Web Usage Mining”, IEEE International Symposium on Computer Science and Computational Technology, pp. 554-559, 2008.
- Tasawar Hussain, Dr. Sohail Asghar and Nayyer Masood, “Hierarchical Sessionization at Preprocessing Level of WUM Based on Swarm Intelligence”, 6th International Conference on Emerging Technologies (ICET) IEEE, pp. 21-26, 2010
- Doru Tanasa and Brigitte Trousse, ”Advanced Data Preprocessing for Inter sites Web Usage Mining“, Published by the IEEE Computer Society, pp. 59-65, March/April 2004
- Ling Zheng, Hui Gui and Feng Li, “Optimized Data Preprocessing Technology For Web Log Mining”, IEEE International Conference On Computer Design and Applications( ICCDA ), pp. VI-19-VI-21,2010
- JING Chang-bin and Chen Li, “Web Log Data Preprocessing Based on Collaborative Filtering”, IEEE 2nd International Workshop on Education Technology and Computer Science, pp.118-121, 2010.