Pre Prospection data mining model for hydrocarbon development guides to the need of developing a model for prospection activity for which the data of surface indicators collected through remote sensing and microbial sources can be used. This chapter proposes a new approach to mine context based positive and negative spatial association rules. Researchers are using Apriori algorithm on spatial d...

Data mining methods that exploit graph/network have become quite popular and a timely challenge is to consider the discovery of dynamic properties in evolving graphs or networks. In this paper, we consider the dynamic oriented graphs that can be encoded as n-ary relations with n ≥ 3 such that we have a least 3 dimensions: the dimensions of departure (tail) and arrival (head) vertices plus the t...

Case-based reasoning usually exploits positive source cases, each of them consisting in a problem and correct solution to this problem. Now, the general issue exploiting also negative cases—i.e., problem-solution pairs where answers incorrectly problem—can be raised. Indeed, such cases are “naturally” generated by CBR system as long it sometimes proposes incorrect solutions. This paper aims at ...

Knowledge discovery in databases, or data mining, is an important issue in the development of dataand knowledge-base systems. An attribute-oriented induction method has been developed for knowledge discovery in databases. The method integrates a machine learning paradigm, especially learning-from-examples techniques, with set-oriented database operations and extracts generalized data from actua...

Previous research has resulted in a number of different algorithms for rule discovery. Two approaches discussed here, the ‘all-rules’ algorithm and multiobjective metaheuristics, both result in the production of a large number of partial classification rules, or ‘nuggets’, for describing different subsets of the records in the class of interest. This paper describes the application of a number ...

In this paper we apply computer-aided theorem discovery technique to discover theorems about strongly equivalent logic programs under the answer set semantics. Our discovered theorems capture new classes of strongly equivalent logic programs that can lead to new program simplification rules that preserve strong equivalence. Specifically, with the help of computers, we discovered exact condition...

Highly specific direct genome-scale expression discovery from two biological samples facilitates functional discovery of molecular systems. Here, expression data from cDNA arrays are ranked and curve-fitted. The algorithm uses filters based on the derivatives (slopes) of the curve fits. The rules are set to (i) filter the largest number of artifactual ratios from same-to-same datasets and (ii) ...

Data mining is the process of extracting implicit, previously unknown, and potentially useful information from data in databases. It is widely recognized as a useful tool for decision making and knowledge discovery. Rule mining, however, is computationally expensive. Moreover, certain mathematical properties of mined rules have been given little attention. This paper applies logical identities ...

in recent years social psychologists have concerned themselves with the ways people classify information about others, store them in their memories, and judge others on. such studies on the process of social cognition have three aspects: structure, process, and causes: i.e. (i) the structure of the social knowledge, (ii) the process of thinking about others, the performance of cognitive categor...