process mining includes the automated discovery of petri nets from event logs. these event logs are the starting point for various discovery and analysis techniques of the process.  in this paper process model is developed using colored petri nets (cpns) and the supporting software package cpn tools. the restaurant process model is represented for the analysis using a combination of process min...

Document Clustering is one of the main themes in text mining. It refers to the process of grouping documents with similar contents or topics into clusters to improve both availability and reliability of text mining applications. Some of the recent algorithms address the problem of high dimensionality of the text by using frequent termsets for clustering. Although the drawbacks of the Apriori al...

begin{abstract} in this paper, we introduce an iterative method for amenable semigroup of non expansive mappings and infinite family of non expansive mappings in the frame work of hilbert spaces. we prove the strong convergence of the proposed iterative algorithm to the unique solution of a variational inequality, which is the optimality condition for a minimization problem. the results present...

D2.2.5.1 Abstract MineSet is a commercial data mining product from Silicon Graphics. It provides an interactive platform for data mining, integrating three powerful technologies: database and file access, analytical data mining engines, and data visualization. MineSet supports the knowledge discovery process from data access and preparation through iterative analysis and visualization to deploy...

D2.2.5.1 Abstract MineSetTM is a commercial data mining product from Silicon Graphics. It provides an interactive platform for data mining, integrating three powerful technologies: database and file access, analytical data mining engines, and data visualization. MineSet supports the knowledge discovery process from data access and preparation through iterative analysis and visualization to depl...

rapid growth of networks and social networks results in more access to people’s opinion. these opinions contain useful information. by analyzing these opinions, people’s preferences and their positive and negative opinions about different subjects can be identified. opinion mining is the process of analyzing people’s emotions, feelings and opinions to identify their preferences. in this article...

Creating executable semantic mappings is an important task for ontology-based information integration. Although it is argued that mapping tools may require interaction from humans (domain experts) for best accuracy, in general, automatic ontology mapping is an AI-Complete problem. Finding matchings (correspondences) between the concepts of two ontologies is the first step towards solving this p...

Introduction Geographic data mining can be defined as a set of exploratory computational and statistical approaches for analyzing very large spatial and spatiotemporal data sets. Data mining techniques are often grouped into categories that include clustering, categorization, summarization, rule-mining, and feature extraction. All of these types of techniques are generally oriented towards iden...

Successful data mining is an iterative process during which data will be refined and adjusted to achieve more accurate mining results. Most important tools in the text mining context are list of stop words and list of synonyms. The size and richness of the lists mentioned depend on the structure of the language used in the text to be mined. English, for example, is an “easy” language for search...

Data mining, also known as knowledge discovery in databases, is the process of discovery potentially useful, hidden knowledge or relations among data from large databases. An important topic in data mining research is concerned with the discovery of association rules. The majority of databases are distributed nowadays. In this paper is presented an algorithm for mining fuzzy association rules f...