The web content in present scenario is mainly comprised of Social media systems such as blogs, photo and link sharing sites and on-line forums. . Web Usage Mining is the application of data mining techniques in the field of social networks to discover exciting usage patterns from SNS data and to serve the needs of SNS applications in a better manner. The major use of web usage mining techniques...

Association rules is a very important part of data mining. It is used to find the interesting patterns from transaction databases. Apriori algorithm is one of the most classical algorithms of association rules, but it has the bottleneck in efficiency. In this article, we proposed a prefixed-itemset-based data structure for candidate itemset generation, with the help of the structure we managed ...

In this paper, we present PRICES, an efficient algorithm for mining association rules, which first identifies all large itemsets and then generates association rules. Our approach reduces large itemset generation time, known to be the most time-consuming step, by scanning the database only once and using logical operations in the process. Experimental results and comparisons with the state of t...

A great research work has been done in last decade in association rules mining (ARM) algorithms . Therefore, various algorithms were proposed to discover frequent item sets and then mine association rules. Apriori algorithm is the most frequently used algorithm for generating association rules. Apriori algorithm has some abuses, such as too many scans of the database, large load of system’s I/O...

Frequent item generation is a key approach in association rule mining. The Data mining is the process of generating frequent itemsets that satisfy minimum support. Efficient algorithms to mine frequent patterns are crucial in data mining. Since the Apriori algorithm was proposed to generate the frequent item sets, there have been several methods proposed to improve its performance. But they do ...

A framework is proposed for the detection of reduplication in digital videos of American Sign Language (ASL). In ASL, reduplication is used for a variety of linguistic purposes, including overt marking of plurality on nouns, aspectual inflection on verbs, and nominalization of verbal forms. Reduplication involves the repetition, often partial, of the articulation of a sign. In this paper, the a...

This paper presents a set of programme to extract the application-layer protocol features. Based on frequent itemsets mining, the program automatically extracts four most common features of a protocol: characteristic string, session tag, packet length, and packet order. It is experimentally demonstrated that this progran can significantly improve the efficiency of feature extraction, and can be...

Action recognition in video sequence has been a major challenging research area for number of years. Apriori algorithm and SIFT descriptor based approach for action recognition is proposed in this paper. Here, two phases can be carried out for accurate and updating of action recognition. In the first phase, the input should be the video sequence. For preprocessing the sequences frame can be for...

Association rule mining searches for interesting relationship among items in a large data set. Market basket analysis, a typical example of association rule mining, analyzes buying habit of customers by finding association between the different items that customers put in their shopping cart (basket). Apriori algorithm is an influential algorithm for mining frequent itemset for generating assoc...