A Theoretical Framework of Procedures Contain Random Walk Methodology in Various Field of Data Mining and Distributed Computing
Garima Singh Makhija, Anjali Mahajan · 2015
The concept of Random Walk begins from Social Science and enters into many fields of today like Computer Science, Financial Analysis, and Economics etc. Theory of Random walk is very flexible to understand but at the same time the ambiguity arises to use the same. This paper reflects the use of Random Walk concept in numerous field of Computer Science; it shows that how differently their concepts use in Sensor Network and in the field of Data mining. This paper mainly focused in Random Walk model in Graph based algorithm and shows how it has been used for improving result of previous algorithms and methods given for that particular technique. Mainly, concepts of Data mining which summarized in this paper are Outlier (Isolation Detection) and Clustering (Similarity Detection) which are more prominent research topic in this field. Also, the concept of Target set selection and mobile data gathering in large scale wireless sensor network. Numerous techniques have been developed to these both concepts but the purpose of this paper is to discuss and evaluate algorithms based on Random Walk for specified above methods and their comparison with previous techniques.