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From Data Mining to Knowledge Discovery in Databases.

by Usama Fayyad , Gregory Piatetsky-Shapiro , Padhraic Smyth - AI Magazine, , 1996
"... ■ Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. What is all the excitement about? This article provides an overview of this emerging field, clarifying how data mining and knowledge discovery in database ..."
Abstract - Cited by 538 (0 self) - Add to MetaCart
predictive model for estimating the value of future cases). At the core of the process is the application of specific data-mining methods for pattern discovery and extraction. 1 This article begins by discussing the historical context of KDD and data mining and their intersection with other related fields. A

Extracting Relations from Large Plain-Text Collections

by Eugene Agichtein, Luis Gravano , 2000
"... Text documents often contain valuable structured data that is hidden in regular English sentences. This data is best exploited if available as a relational table that we could use for answering precise queries or for running data mining tasks. We explore a technique for extracting such tables fr ..."
Abstract - Cited by 494 (25 self) - Add to MetaCart
Text documents often contain valuable structured data that is hidden in regular English sentences. This data is best exploited if available as a relational table that we could use for answering precise queries or for running data mining tasks. We explore a technique for extracting such tables

Workflow Mining: Discovering process models from event logs

by W.M.P. van der Aalst, A.J.M.M. Weijter, L. Maruster - IEEE Transactions on Knowledge and Data Engineering , 2003
"... Contemporary workflow management systems are driven by explicit process models, i.e., a completely specified workflow design is required in order to enact a given workflow process. Creating a workflow design is a complicated time-consuming process and typically there are discrepancies between the ac ..."
Abstract - Cited by 400 (57 self) - Add to MetaCart
executed. We present a new algorithm to extract a process modelf3q such a log and represent it in terms of a Petri net. However, we will also demonstrate that it is not possible to discover arbitrary workflow processes. In this paper we explore a classof workflow processes that can be discovered. We show

Matching words and pictures

by Kobus Barnard, Pinar Duygulu, David Forsyth, Nando De Freitas, David M. Blei, Michael I. Jordan - JOURNAL OF MACHINE LEARNING RESEARCH , 2003
"... We present a new approach for modeling multi-modal data sets, focusing on the specific case of segmented images with associated text. Learning the joint distribution of image regions and words has many applications. We consider in detail predicting words associated with whole images (auto-annotation ..."
Abstract - Cited by 665 (40 self) - Add to MetaCart
We present a new approach for modeling multi-modal data sets, focusing on the specific case of segmented images with associated text. Learning the joint distribution of image regions and words has many applications. We consider in detail predicting words associated with whole images (auto

Mining: Information and Pattern Discovery on the World Wide Web

by R. Cooley, B. Mobasher, J. Srivastava - In: Proceedings of the 9th IEEE International Conference on Tools with Artificial Intelligence (ICTAI , 1997
"... Application of data mining techniques to the World Wide Web, referred to as Web mining, has been the focus of several recent research projects and papers. However, there is no established vocabulary, leading to confusion when comparing research efforts. The term Web mining has been used in two disti ..."
Abstract - Cited by 372 (21 self) - Add to MetaCart
Application of data mining techniques to the World Wide Web, referred to as Web mining, has been the focus of several recent research projects and papers. However, there is no established vocabulary, leading to confusion when comparing research efforts. The term Web mining has been used in two

Web mining for web personalization

by Magdalini Eirinaki, Michalis Vazirgiannis - ACM Transactions on Internet Technology , 2003
"... Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user’s navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content an ..."
Abstract - Cited by 217 (6 self) - Add to MetaCart
Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user’s navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content

Business process mining: An industrial application

by Wil M. P. van der Aalst , H. A. Reijers, A. J. M. M. Weijters, B. F. van Dongen, A. K. Alves de Medeiros, M. Song, H. M. W. Verbeek - INFORMATION SYSTEMS , 2007
"... ... SCM, and B2B systems) record business events in so-called event logs. Business process mining takes these logs to discover process, control, data, organizational, and social structures. Although many researchers are developing new and more powerful process mining techniques and software vendors ..."
Abstract - Cited by 83 (7 self) - Add to MetaCart
... SCM, and B2B systems) record business events in so-called event logs. Business process mining takes these logs to discover process, control, data, organizational, and social structures. Although many researchers are developing new and more powerful process mining techniques and software vendors

Interestingness measures for data mining: a survey

by Liqiang Geng, Howard, J. Hamilton - ACM Computing Surveys
"... Interestingness measures play an important role in data mining, regardless of the kind of patterns being mined. These measures are intended for selecting and ranking patterns according to their potential interest to the user. Good measures also allow the time and space costs of the mining process to ..."
Abstract - Cited by 158 (2 self) - Add to MetaCart
to be reduced. This survey reviews the interestingness measures for rules and summaries, classifies them from several perspectives, compares their properties, identifies their roles in the data mining process, gives strategies for selecting appropriate measures for applications, and identifies opportunities

Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values

by Zhexue Huang , 1998
"... The k-means algorithm is well known for its efficiency in clustering large data sets. However, working only on numeric values prohibits it from being used to cluster real world data containing categorical values. In this paper we present two algorithms which extend the k-means algorithm to categoric ..."
Abstract - Cited by 264 (3 self) - Add to MetaCart
algorithms are efficient when clustering large data sets, which is critical to data mining applications.

Active Storage For Large-Scale Data Mining and Multimedia

by Erik Riedel, et al. , 1998
"... The increasing performance and decreasing cost of processors and memory are causing system intelligence to move into peripherals from the CPU. Storage system designers are using this trend toward "excess" compute power to perform more complex processing and optimizations inside stora ..."
Abstract - Cited by 147 (19 self) - Add to MetaCart
to move data more efficiently. We propose a system called Active Disks that takes advantage of processing power on individual disk drives to run application-level code. Moving portions of an application's processing to execute directly at disk drives can dramatically reduce data traffic
Results 1 - 10 of 3,383