Abstract A non-negative transferable utility (TU) game is average monotonic if there exists a vector according to which the relative worth not decreasing when enlarging coalition. We generalize this definition nontransferable (NTU) case. It shown that an NTU shares several properties with TU game. In particular it has special core element and population allocation scheme. show bankruptcy respec...

How to process missing attribute values is an important data preprocessing problem in data mining and knowledge discovery tasks. A commonly-used and naive solution to process data with missing attribute values is to ignore the instances which contain missing attribute values. This method may neglect important information within the data and a significant amount of data could be easily discarded...

Data mining is the process of extracting new, possibly useful information from vast data bases that not straightforward. Market basket analysis, a kind used in retail research, to analyse client transactions. The association between things occur transactions more frequently was focus earlier techniques. They don't take an item's significance or utility into account while often itemset. Utility ...

Association rules discovered from transaction databases can be large in number. Reduction of association rules is an issue in recent times. Conventionally by varying support and confidence number of rules can be increased and decreased. By combining additional constraint with support number of frequent itemsets can be reduced and it leads to generation of less number of rules. Average inter ite...

Tzung-Pei Hong , Cho-Han Lee and Shyue-Liang Wang Department of Computer Science and Information Engineering Department of Electrical Engineering Department of Information Management National University of Kaohsiung, Kaohsiung, 811, Taiwan Department of Computer Science and Engineering National Sun Yat-sen University, Kaohsiung, 804, Taiwan [email protected], [email protected], slwang@nu...

We introduce the measures share, coincidence and dominance as alternatives to the standard itemset methodology measure of support. We also redefine the confidence measure in this context. An itemset is a group of items bought together in a transaction. The support of an itemset is the ratio of transactions in which an itemset appears to the total number of transactions. The share of an itemset ...

Frequent generalized itemset mining is a data mining technique utilized to discover a high-level view of interesting knowledge hidden in the analyzed data. By exploiting a taxonomy, patterns are usually extracted at any level of abstraction. However, some misleading high-level patterns could be included in the mined set. This paper proposes a novel generalized itemset type, namely theMisleading...

For a transaction database, a frequent itemset is an itemset included in at least a specified number of transactions. A frequent itemset P is maximal if P is included in no other frequent itemset, and closed if P is included in no other itemset included in the exactly same transactions as P . The problems of finding these frequent itemsets are fundamental in data mining, and from the applicatio...

The paradigm shift from 'data-centered pattern mining' to 'domain driven actionable knowledge discovery' has increased the need for considering the business yield (utility) and demand or rate of recurrence of the items (frequency) while mining a retail business transaction database. Such a data mining process will help in mining different types of itemsets of varying business utility and demand...