Mining frequent partial orders from a collection of sequences was introduced as an alternative to mining frequent sequential patterns in order to provide a more compact/understandable representation. The motivation was that a single partial order can represent the same ordering information between items in the collection as a set of sequential patterns (set of totally ordered sets of items). Ho...

In this version of Colored Bin-Packing, we have n items of unit weight, where each item is one of x colors, where x ≥ 3. Again, we have an unlimited supply of bins, each with weight limit L, in which to pack the items and our goal is to minimize the total number of bins. 2 Algorithm The unit-weight case introduces weight constraints. Furthermore, we know that color constraints, specifically the...

Traditional classification techniques such as decision trees and RIPPER use heuristic search methods to find a small subset of patterns. In recent years, a promising new approach that mainly uses association rule mining in classification called associative classification has been proposed. Most associative classification algorithms adopt the exhaustive search method presented in the famous Apri...

There are several mining algorithms which have been developed over the years. Apriori Algorithm is one of the most important algorithm which is used to extract frequent itemsets from large database and get the association rule for discovering the knowledge. It basically requires two important things: minimum support and minimum confidence. Firstly, we check whether the items are greater than or...

Mining frequent items and itemsets is a daunting task in large databases and has attracted research attention in recent years. Generating specific itemset, K –itemset having K items, is an interesting research problem in data mining and knowledge discovery. In this paper, we propose an algorithm for finding K itemset frequent pattern generation in large databases which is named as AMKIS. AMKIS ...

The retention of communication data has recently attracted much public interest, mostly because of the possibility of its misuse. In this paper, we present protocols that address the privacy concerns of the communication partners. Our data retention protocols store streams of encrypted data items, some of which may be flagged as critical (representing misbehavior). The frequent occurrence of cr...

As a technology based on database, statistics and AI, data mining provides biological research a useful information analyzing tool. The key factors which influence the performance of biological data mining approaches are the large-scale of biological data and the high similarities among patterns mined. In this paper, we present an efficient algorithm named IRTM for mining frequent subtrees embe...

We introduce an approach to learn discriminative visual representations while exploiting external semantic knowledge about object category relationships. Given a hierarchical taxonomy that captures semantic similarity between the objects, we learn a corresponding tree of metrics (ToM). In this tree, we have one metric for each non-leaf node of the object hierarchy, and each metric is responsibl...