Efficient algorithms for mining frequent itemsets are crucial for mining association rules. Methods for mining frequent itemsets and for iceberg data cube computation have been implemented using a prefix-tree structure, known as an FP-tree, for storing compressed information about frequent itemsets. Numerous experimental results have demonstrated that these algorithms perform extremely well. In...

We present algorithms that run in linear time on pointer machines for a collection of problems, each of which either directly or indirectly requires the evaluation of a function defined on paths in a tree. These problems previously had linear-time algorithms but only for random-access machines (RAMs); the best pointer-machine algorithms were super-linear by an inverse-Ackermann-function factor....

In this paper, a theory of game tree algorithms is presented, entirely based upon the concept of solution tree. Two types of solution trees are distinguished: max and min solution trees respectively. We show that a game tree algorithm actually constructs a superposition of a max and a min solution tree. For algorithms searching a game tree, a cutoo criterion is suitable. A cut-oo criterion in t...

Internet growth has increased rapidly due to which number of network attacks have been increased. This emphasis importance of network intrusion detection systems (IDS) for securing the network. It is the process of monitoring and analyzing network traffic for detecting security violations many researcher suggested data mining technique such as classification, clustering ,pattern matching and ru...

Progressive advancements in the data stream mining have paved way for many algorithms to solve the problem of concept drift, a serious problem due to the wavering nature of the real time concepts. Concepts tend to change with time therefore concept drift is unavoidable in data stream mining but efficient algorithms can be designed to detect the concept drift and solve the problem. This paper pr...

High utility pattern (HUP) mining over data streams has become a challenging research issue in data mining. The existing sliding window-based HUP mining algorithms over stream data suffer from the level-wise candidate generationand-test problem. Therefore, they need a large amount of execution time and memory. Moreover, their data structures are not suitable for interactive mining. To solve the...

Minimum Steiner tree problem in a weighted graph is to find a least cost sub tree in the graph such that it contains special vertices called terminal points. Since this problem belongs to NP-Complete problems, many approximate algorithms including genetic algorithms and ant colony strategies have been designed for solving it. In this paper, we propose an algorithm based on distributed learning ...