-
Lusti, M.: Data Warehousing and Data Mining : Eine Einführung in entscheidungsunterstützende Systeme (1999)
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- Abstract
- Im Mittelpunkt dieses anwendungsbezogenen Lehrbuchs stehen Architekturen, Methoden und Werkzeuge entscheidungsunterstützender Systeme. Beispiele und Aufgaben ermöglichen die Entwicklung von Anwendungen mit der Demonstrationssoftware der CD-ROM. Eine interaktive Foliensammlung veranschaulicht den Buchtext und verweist auf zusätzliches Lernmaterial
- Date
- 17. 7.2002 19:22:06
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Analytische Informationssysteme : Data Warehouse, On-Line Analytical Processing, Data Mining (1998)
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- Abstract
- Neben den operativen Informationssystemen treten heute verstärkt Informationssysteme für die analytischen Aufgaben der Fach- und Führungskräfte in den Vordergrund. In fast allen Unternehmen werden derzeit Begriffe und Konzepte wie Data Warehouse, On-Line Analytical Processing und Data Mining diskutiert und die zugehörigen Produkte evaluiert. Vor diesem Hintergrund zielt der vorliegende Sammelband darauf, einen aktuellen Überblick über Technologien, Produkte und Trends zu bieten. Als Entscheidungsgrundlage für den Praktiker beim Aufbau und Einsatz derartiger analytischer Informationssysteme können die unterschiedlichen Beiträge aus Wirtschaft und Wissenschaft wertvolle Hilfestellung leisten
-
Analytische Informationssysteme : Data Warehouse, On-Line Analytical Processing, Data Mining (1999)
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- Abstract
- Neben den operativen Informationssystemen, welche die Abwicklung des betrieblichen Tagesgeschäftes unterstützen, treten heute verstärkt Informationssysteme für analytische Aufgaben der Fach- und Führungskräfte in den Vordergrund. In fast allen Unternehmen werden derzeit Begriffe und Konzepte wie Data Warehouse, On-Line Analytical Processing und Data Mining diskutiert und die zugehörigen Produkte evaluiert. Vor diesem Hintergrund zielt der vorliegende Sammelband darauf ab, einen aktuellen Überblick über Technologien, Produkte und Trends zu bieten. Als Entscheidungsgrundlage für den Praktiker beim Aufbau und Einsatz derartiger analytischer Informationssysteme können die unterschiedlichen Beiträge aus Wirtschaft und Wissenschaft wertvolle Hilfestellung leisten.
- Content
- Grundlagen.- Data Warehouse.- On-line Analytical Processing.- Data Mining.- Betriebswirtschaftliche und strategische Aspekte.
-
Data mining : Theoretische Aspekte und Anwendungen (1998)
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- Abstract
- Behandelt werden u.a. die Themen: Ziele und Methoden des Data Mining, Prozeß der Wissensentdeckung, State of the Art in der Forschung und Anwendung des Data Mining, wichtige Data Mining Tools, die Rolle der Informationsverarbeitung im KDD Prozeß, Data Warehousing, OLAP, Ansätze zur Benutzerunterstüzung des Data Mining Prozesses, Modellselektion und Evaluierungsmethoden für Data Mining Algorithmen
-
Hofstede, A.H.M. ter; Proper, H.A.; Van der Weide, T.P.: Exploiting fact verbalisation in conceptual information modelling (1997)
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- Abstract
- Focuses on the information modelling side of conceptual modelling. Deals with the exploitation of fact verbalisations after finishing the actual information system. Verbalisations are used as input for the design of the so-called information model. Exploits these verbalisation in 4 directions: considers their use for a conceptual query language, the verbalisation of instances, the description of the contents of a database and for the verbalisation of queries in a computer supported query environment. Provides an example session with an envisioned tool for end user query formulations that exploits the verbalisation
- Source
- Information systems. 22(1997) nos.5/6, S.349-385
-
Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997)
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- Abstract
- Defines digital libraries and discusses the effects of new technology on librarians. Examines the different viewpoints of librarians and information technologists on digital libraries. Describes the development of a digital library at the National Drug Intelligence Center, USA, which was carried out in collaboration with information technology experts. The system is based on Web enabled search technology to find information, data visualization and data mining to visualize it and use of SGML as an information standard to store it
- Date
- 22.11.1998 18:57:22
-
Amir, A.; Feldman, R.; Kashi, R.: ¬A new and versatile method for association generation (1997)
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- Abstract
- Current algorithms for finding associations among the attributes describing data in a database have a number of shortcomings. Presents a novel method for association generation, that answers all desiderata. The method is different from all existing algorithms and especially suitable to textual databases with binary attributes. Uses subword trees for quick indexing into the required database statistics. Tests the algorithm on the Reuters-22173 database with satisfactory results
- Source
- Information systems. 22(1997) nos.5/6, S.333-347
-
Chowdhury, G.G.: Template mining for information extraction from digital documents (1999)
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- Date
- 2. 4.2000 18:01:22
-
KDD : techniques and applications (1998)
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- Footnote
- A special issue of selected papers from the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'97), held Singapore, 22-23 Feb 1997
-
Fayyad, U.; Piatetsky-Shapiro, G.; Smyth, P.: From data mining to knowledge discovery in databases (1996)
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- Abstract
- Gives an overview of data mining and knowledge discovery in databases. Clarifies how they are related both to each other and to related fields. Mentions real world applications data mining techniques, challenges involved in real world applications of knowledge discovery, and current and future research directions
-
Advances in knowledge discovery and data mining (1996)
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- Footnote
- Rez. in: JASIS 49(1998) no.4, S.386-387 (F. Exner)
-
Mattison, R.: Data warehousing and data mining for telecommunications (1997)
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- Footnote
- Rez. in: Database 21(1998) no.3, S.94 (J.D. Blackwell)
-
Bell, D.A.; Guan, J.W.: Computational methods for rough classification and discovery (1998)
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- Abstract
- Rough set theory is a mathematical tool to deal with vagueness and uncertainty. To apply the theory, it needs to be associated with efficient and effective computational methods. A relation can be used to represent a decison table for use in decision making. By using this kind of table, rough set theory can be applied successfully to rough classification and knowledge discovery. Presents computational methods for using rough sets to identify classes in datasets, finding dependencies in relations, and discovering rules which are hidden in databases. Illustrates the methods with a running example from a database of car test results
-
Schmid, J.: Data mining : wie finde ich in Datensammlungen entscheidungsrelevante Muster? (1999)
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-
Cardie, C.: Empirical methods in information extraction (1997)
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- Footnote
- Contribution to a special section reviewing recent research in empirical methods in speech recognition, syntactic parsing, semantic processing, information extraction and machine translation
-
Gaizauskas, R.; Wilks, Y.: Information extraction : beyond document retrieval (1998)
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- Abstract
- In this paper we give a synoptic view of the growth of the text processing technology of informatione xtraction (IE) whose function is to extract information about a pre-specified set of entities, relations or events from natural language texts and to record this information in structured representations called templates. Here we describe the nature of the IE task, review the history of the area from its origins in AI work in the 1960s and 70s till the present, discuss the techniques being used to carry out the task, describe application areas where IE systems are or are about to be at work, and conclude with a discussion of the challenges facing the area. What emerges is a picture of an exciting new text processing technology with a host of new applications, both on its own and in conjunction with other technologies, such as information retrieval, machine translation and data mining
-
Wong, S.K.M.; Butz, C.J.; Xiang, X.: Automated database schema design using mined data dependencies (1998)
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- Abstract
- Data dependencies are used in database schema design to enforce the correctness of a database as well as to reduce redundant data. These dependencies are usually determined from the semantics of the attributes and are then enforced upon the relations. Describes a bottom-up procedure for discovering multivalued dependencies in observed data without knowing a priori the relationships among the attributes. The proposed algorithm is an application of the technique designed for learning conditional independencies in probabilistic reasoning. A prototype system for automated database schema design has been implemented. Experiments were carried out to demonstrate both the effectiveness and efficiency of the method
-
Galal, G.M.; Cook, D.J.; Holder, L.B.: Exploiting parallelism in a structural scientific discovery system to improve scalability (1999)
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- Abstract
- The large amount of data collected today is quickly overwhelming researchers' abilities to interpret the data and discover interesting patterns. Knowledge discovery and data mining approaches hold the potential to automate the interpretation process, but these approaches frequently utilize computationally expensive algorithms. In particular, scientific discovery systems focus on the utilization of richer data representation, sometimes without regard for scalability. This research investigates approaches for scaling a particular knowledge discovery in databases (KDD) system, SUBDUE, using parallel and distributed resources. SUBDUE has been used to discover interesting and repetitive concepts in graph-based databases from a variety of domains, but requires a substantial amount of processing time. Experiments that demonstrate scalability of parallel versions of the SUBDUE system are performed using CAD circuit databases and artificially-generated databases, and potential achievements and obstacles are discussed
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Cios, K.J.; Pedrycz, W.; Swiniarksi, R.: Data mining methods for knowledge discovery (1998)
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- Footnote
- Rez. in: Journal of end user computing 12(2000) no.3, S.50 (D. Mitchell)
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Chen, Z.: Knowledge discovery and system-user partnership : on a production 'adversarial partnership' approach (1994)
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- Abstract
- Examines the relationship between systems and users from the knowledge discovery in databases or data mining perspecitives. A comprehensive study on knowledge discovery in human computer symbiosis is needed. Proposes a database-user adversarial partnership, which is general enough to cover knowledge discovery and security of issues related to databases and their users. It can be further generalized into system-user adversarial paertnership. Discusses opportunities provided by knowledge discovery techniques and potential social implications
