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
Jaikumar, M.
- An Optimal Decision Making System on Road Accident Analysis and Road Safety Enhancements
Authors
1 Sri Ramakrishna Mission Vidyalaya College of Arts and Science, Coimbatore-641020, Tamilnadu, IN
2 Dept of Computer Applications (UG), Sri Ramakrishna Mission Vidyalaya College of Arts and Science, Coimbatore-641020, Tamilnadu, IN
Source
Data Mining and Knowledge Engineering, Vol 7, No 10 (2015), Pagination: 333-337Abstract
Determining road accident and provoke of the road occasion in every area is important for road safety enlargements. Earlier spatial immersion procedures did not concede the cause and asperity levels of road accidents. Applying Data-Driven Methods to ROAD Safety (DDMRS) can aid police departments designate resources more effectively. By lime-lighting on risky block, highly visible traffic law enforcement coincidently can diminish crashes. Most studies have focused on crunches after appealing new patrol paths, but few have archived how to progress or change police report time. To drastically reduce fatalities and serious cramps on roads, the ability need to review the appearance and cause of road accidents and classify the hidden information's behind the accidents using previous chronicles. For these analyses the raw data is not sufficient, so implementation of effective data excavating is obligatory.With the use of data mining method such as decision trees will help to discover a best remedy for every scrutiny. The contemplated system familiarizes a road accident classification model. In the scheme, the system first mine associations rules of the crash data, and the detected rules will be build the decision tree named as "SDT" spatial Decision Tree, which is based on the consolidation of association rule and ID3 algorithms. Using these approaches the road accident data can be induced. And finally, the cause for the accident will be recognized for the desired effort.
Keywords
Road Accident Scrutiny, Methodology, SDT.
- A Survey of Web Content Mining Based on Information Retrieval
Authors
1 Dept. of Computer Applications (UG), Sri Ramakrishna Mission Vidyalaya College of Arts and Science, Coimbatore-641020, Tamilnadu, IN
2 Sri Ramakrishna Mission Vidyalaya College of Arts and Science, Coimbatore-641020, Tamilnadu, IN
Source
Data Mining and Knowledge Engineering, Vol 7, No 5 (2015), Pagination: 197-200Abstract
The cynosure of this paper is to fetch the important significance of Web Content Mining. The paper gives a vision into its functions, methods and its efforts in the current business environment as well in research extracting contents for day to day purpose. It also explicates how to use web content mining and how it plays an entity role by getting precious set of volumes and uses those contents in the judgment making in the cluster situation, literacy and scrutinize.Keywords
Web Content Mining Techniques, Process of Mining.- A Survey on E-Learning Personalization Techniques Using Data Mining
Authors
1 Department of Computer Applications (UG), Sri Ramakrishna Mission Vidyalaya College of Arts and Science, Coimbatore, Tamil Nadu, IN
2 Department of Computer Science, Sri Ramakrishna Mission Vidyalaya College of Arts and Science, Coimbatore, Tamil Nadu, IN
Source
Data Mining and Knowledge Engineering, Vol 8, No 9 (2016), Pagination: 274-278Abstract
Web based education System (E-learning) has the tremendous growth in current learning scenario. Such systems utilize several data mining techniques and tools to evaluate the knowledge level of every user. This survey explores the impact of data mining techniques in adaptive e-learning environment. Implementation adaptive E-learning environment with personalized knowledge evaluation is a challenging task. In this paper, we explore different techniques and methods, which used in such environment and modern e-learning environment. Finally, we list the comparisons of these schemes by some criteria for Web based education system. By applying the most appropriate Data mining techniques on personalized e-learning environment will bring better solution, so based on the comparison, our system gives optimum way to achieve high accuracy in e-learning recommendation.