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  1. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.31 
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    Content
    Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
    Date
    8. 1.2013 10:22:32
    Source
    Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 1-4 November 2004, Brighton, UK
  2. Chowdhury, G.G.: Template mining for information extraction from digital documents (1999) 0.25 
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    Date
    2. 4.2000 18:01:22
    Theme
    Data Mining
  3. KDD : techniques and applications (1998) 0.22 
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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
    Theme
    Data Mining
  4. Mommoh, O.M.: Subject analysis of post-graduate theses in library, archival and information science at Ahmadu Bello University, Zaria (1995/96) 0.20 
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    Abstract
    Reports results of a bibliometric study of 111 theses accepted by the Department of Library and Information Science, Ahmadu Bello University, Zaria, Nigeria, between 1977 and 1992. The analysis was based on year, type and degree awarded, subject, type of library and geographical area. Concludes that the highest number of submissions was 1991, when 108 MLS theses (97,29%) and 3 PhD theses (2,71%) were accepted. Libraries and readers was the most concetrated subject while the academic library was the most discussed type of library
    Source
    Library focus. 13/14(1995/96), S.22-25
  5. Lusti, M.: Data Warehousing and Data Mining : Eine Einführung in entscheidungsunterstützende Systeme (1999) 0.19 
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    Date
    17. 7.2002 19:22:06
    RSWK
    Data mining / Lehrbuch
    Subject
    Data mining / Lehrbuch
    Theme
    Data Mining
  6. McMillan, G.: Electronic theses and dissertations : merging perspectives (1996) 0.18 
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    Abstract
    Theses and dissertations as electronic files transferred from the student author to the Graduate School to the Library may well be the first major source of electronic texts that many libraries encounter. To prepare for this potential influx of electronic texts, an ad hoc task force considered work flow and cataloging guidelines. The author suggests expanding current theses cataloging and taking advantage of online information prepared by authors so that the bibliographic records provide OPACS with much more valuable information than does traditional theses cataloging. This should not require a lot of extra work.
    Source
    Cataloging and classification quarterly. 22(1996) nos.3/4, S.105-125
  7. Lackes, R.; Tillmanns, C.: Data Mining für die Unternehmenspraxis : Entscheidungshilfen und Fallstudien mit führenden Softwarelösungen (2006) 0.16 
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    Abstract
    Das Buch richtet sich an Praktiker in Unternehmen, die sich mit der Analyse von großen Datenbeständen beschäftigen. Nach einem kurzen Theorieteil werden vier Fallstudien aus dem Customer Relationship Management eines Versandhändlers bearbeitet. Dabei wurden acht führende Softwarelösungen verwendet: der Intelligent Miner von IBM, der Enterprise Miner von SAS, Clementine von SPSS, Knowledge Studio von Angoss, der Delta Miner von Bissantz, der Business Miner von Business Object und die Data Engine von MIT. Im Rahmen der Fallstudien werden die Stärken und Schwächen der einzelnen Lösungen deutlich, und die methodisch-korrekte Vorgehensweise beim Data Mining wird aufgezeigt. Beides liefert wertvolle Entscheidungshilfen für die Auswahl von Standardsoftware zum Data Mining und für die praktische Datenanalyse.
    Content
    Modelle, Methoden und Werkzeuge: Ziele und Aufbau der Untersuchung.- Grundlagen.- Planung und Entscheidung mit Data-Mining-Unterstützung.- Methoden.- Funktionalität und Handling der Softwarelösungen. Fallstudien: Ausgangssituation und Datenbestand im Versandhandel.- Kundensegmentierung.- Erklärung regionaler Marketingerfolge zur Neukundengewinnung.Prognose des Customer Lifetime Values.- Selektion von Kunden für eine Direktmarketingaktion.- Welche Softwarelösung für welche Entscheidung?- Fazit und Marktentwicklungen.
    Date
    22. 3.2008 14:46:06
    Theme
    Data Mining
  8. Li, T.-C.: Reference sources in periodicals : research note (1995) 0.15 
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    Abstract
    Presents a list of 53 periodicals in 22 subject fields which regularly provide bibliographies of theses, research in progress and patents in their particular subject field. The fields of business, economics, history and literature have most periodical listings of dissertations and theses. Also lists 63 periodicals in 25 sub-disciplines which provide rankings or ratings. Rankings and ratings information predominates in the fields of business, sports and games, finance and banking, and library and information science
  9. McMillan, G.: Electronic theses and dissertations : merging perspectives (1996) 0.15 
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    Abstract
    Reports the work of the ad hoc task force, coordinated by the Scholarly Communications Project (SCP) at Virginia Polytechnic Institute and State University, to discuss the best means of cataloguing the theses palnned to be produced directly in electronic forms by postgraduate students. The main goals were to determine a process for handling electronic theses so that access would be at least as good as for hard copy and to find a way to derive cataloguing information from the electronic text and avoid rekeying as much as possible. An important part of the study was the application of existing MARC format tagged record structures to the new system. Concludes with brief notes on the concerns of UMI regarding Internet access of electronic theses
    Series
    Cataloging and classification quarterly; vol.22, nos.3/4
  10. Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997) 0.15 
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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
    Theme
    Data Mining
  11. Keim, D.A.: Data Mining mit bloßem Auge (2002) 0.14 
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    Abstract
    Visualisierungen, die möglichst instruktive grafische Darstellung von Daten, ist wesentlicher Bestandteil des Data Mining
    Footnote
    Teil eines Heftthemas 'Data Mining'
    Series
    Data Mining
    Theme
    Data Mining
  12. Saz, J.T.: Perspectivas en recuperacion y explotacion de informacion electronica : el 'data mining' (1997) 0.12 
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    Abstract
    Presents the concept and the techniques identified by the term data mining. Explains the principles and phases of developing a data mining process, and the main types of data mining tools
    Footnote
    Übers. des Titels: Perspectives on the retrieval and exploitation of electronic information: data mining
    Theme
    Data Mining
  13. Wrobel, S.: Lern- und Entdeckungsverfahren (2002) 0.12 
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    Abstract
    Betrügerische Kreditkartenkäufe, besonders fähige Basketballspieler und umweltbewusste Saftverkäufer ausfindig machen - Data-Mining-Verfahren lernen selbständig das Wesentliche
    Footnote
    Teil eines Heftthemas 'Data Mining'
    Series
    Data Mining
    Theme
    Data Mining
  14. Callahan, P.F.: ISBD(S) revised edition and AACR2 1988 revision : a comparison (1992) 0.12 
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    Abstract
    Article appearing as part of an issue devoted to the theme, Serials Cataloguing: Modern Perspectives and International Developments. Pt.2. In 1988, a revision of AACR2 and a revised edition of the ISBD for serials were published. Discusses and compares the origins of theses 2 standards and their relationship. Describes the inconsistencies between the 2 texts and evaluates their compatibility. Concludes that there is a high degree of compatability on major points but that relatively little progress has been made since the original editions in reducing the substantial number of minor differences
    Source
    Serials librarian. 22(1992) no.3/4, S.249-262
  15. Strader, C.R.: Citation analysis (2012) 0.12 
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    Abstract
    This study is a citation analysis of a set of theses and dissertations in the Ohio State University's online catalog, for which the author-assigned keywords and cataloger-assigned Library of Congress Subject Headings (LCSH) are known. Correlations are sought between the types and ages of resources cited and the number of unique keywords and unique LCSH that were found. The author presents results found in three general discipline areas: arts and humanities, the social sciences, and science, technology, engineering, and medicine.
    Date
    10. 9.2000 17:38:22
  16. Information visualization in data mining and knowledge discovery (2002) 0.12 
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    Date
    23. 3.2008 19:10:22
    Footnote
    Rez. in: JASIST 54(2003) no.9, S.905-906 (C.A. Badurek): "Visual approaches for knowledge discovery in very large databases are a prime research need for information scientists focused an extracting meaningful information from the ever growing stores of data from a variety of domains, including business, the geosciences, and satellite and medical imagery. This work presents a summary of research efforts in the fields of data mining, knowledge discovery, and data visualization with the goal of aiding the integration of research approaches and techniques from these major fields. The editors, leading computer scientists from academia and industry, present a collection of 32 papers from contributors who are incorporating visualization and data mining techniques through academic research as well application development in industry and government agencies. Information Visualization focuses upon techniques to enhance the natural abilities of humans to visually understand data, in particular, large-scale data sets. It is primarily concerned with developing interactive graphical representations to enable users to more intuitively make sense of multidimensional data as part of the data exploration process. It includes research from computer science, psychology, human-computer interaction, statistics, and information science. Knowledge Discovery in Databases (KDD) most often refers to the process of mining databases for previously unknown patterns and trends in data. Data mining refers to the particular computational methods or algorithms used in this process. The data mining research field is most related to computational advances in database theory, artificial intelligence and machine learning. This work compiles research summaries from these main research areas in order to provide "a reference work containing the collection of thoughts and ideas of noted researchers from the fields of data mining and data visualization" (p. 8). It addresses these areas in three main sections: the first an data visualization, the second an KDD and model visualization, and the last an using visualization in the knowledge discovery process. The seven chapters of Part One focus upon methodologies and successful techniques from the field of Data Visualization. Hoffman and Grinstein (Chapter 2) give a particularly good overview of the field of data visualization and its potential application to data mining. An introduction to the terminology of data visualization, relation to perceptual and cognitive science, and discussion of the major visualization display techniques are presented. Discussion and illustration explain the usefulness and proper context of such data visualization techniques as scatter plots, 2D and 3D isosurfaces, glyphs, parallel coordinates, and radial coordinate visualizations. Remaining chapters present the need for standardization of visualization methods, discussion of user requirements in the development of tools, and examples of using information visualization in addressing research problems.
    In 13 chapters, Part Two provides an introduction to KDD, an overview of data mining techniques, and examples of the usefulness of data model visualizations. The importance of visualization throughout the KDD process is stressed in many of the chapters. In particular, the need for measures of visualization effectiveness, benchmarking for identifying best practices, and the use of standardized sample data sets is convincingly presented. Many of the important data mining approaches are discussed in this complementary context. Cluster and outlier detection, classification techniques, and rule discovery algorithms are presented as the basic techniques common to the KDD process. The potential effectiveness of using visualization in the data modeling process are illustrated in chapters focused an using visualization for helping users understand the KDD process, ask questions and form hypotheses about their data, and evaluate the accuracy and veracity of their results. The 11 chapters of Part Three provide an overview of the KDD process and successful approaches to integrating KDD, data mining, and visualization in complementary domains. Rhodes (Chapter 21) begins this section with an excellent overview of the relation between the KDD process and data mining techniques. He states that the "primary goals of data mining are to describe the existing data and to predict the behavior or characteristics of future data of the same type" (p. 281). These goals are met by data mining tasks such as classification, regression, clustering, summarization, dependency modeling, and change or deviation detection. Subsequent chapters demonstrate how visualization can aid users in the interactive process of knowledge discovery by graphically representing the results from these iterative tasks. Finally, examples of the usefulness of integrating visualization and data mining tools in the domain of business, imagery and text mining, and massive data sets are provided. This text concludes with a thorough and useful 17-page index and lengthy yet integrating 17-page summary of the academic and industrial backgrounds of the contributing authors. A 16-page set of color inserts provide a better representation of the visualizations discussed, and a URL provided suggests that readers may view all the book's figures in color on-line, although as of this submission date it only provides access to a summary of the book and its contents. The overall contribution of this work is its focus an bridging two distinct areas of research, making it a valuable addition to the Morgan Kaufmann Series in Database Management Systems. The editors of this text have met their main goal of providing the first textbook integrating knowledge discovery, data mining, and visualization. Although it contributes greatly to our under- standing of the development and current state of the field, a major weakness of this text is that there is no concluding chapter to discuss the contributions of the sum of these contributed papers or give direction to possible future areas of research. "Integration of expertise between two different disciplines is a difficult process of communication and reeducation. Integrating data mining and visualization is particularly complex because each of these fields in itself must draw an a wide range of research experience" (p. 300). Although this work contributes to the crossdisciplinary communication needed to advance visualization in KDD, a more formal call for an interdisciplinary research agenda in a concluding chapter would have provided a more satisfying conclusion to a very good introductory text.
    With contributors almost exclusively from the computer science field, the intended audience of this work is heavily slanted towards a computer science perspective. However, it is highly readable and provides introductory material that would be useful to information scientists from a variety of domains. Yet, much interesting work in information visualization from other fields could have been included giving the work more of an interdisciplinary perspective to complement their goals of integrating work in this area. Unfortunately, many of the application chapters are these, shallow, and lack complementary illustrations of visualization techniques or user interfaces used. However, they do provide insight into the many applications being developed in this rapidly expanding field. The authors have successfully put together a highly useful reference text for the data mining and information visualization communities. Those interested in a good introduction and overview of complementary research areas in these fields will be satisfied with this collection of papers. The focus upon integrating data visualization with data mining complements texts in each of these fields, such as Advances in Knowledge Discovery and Data Mining (Fayyad et al., MIT Press) and Readings in Information Visualization: Using Vision to Think (Card et. al., Morgan Kauffman). This unique work is a good starting point for future interaction between researchers in the fields of data visualization and data mining and makes a good accompaniment for a course focused an integrating these areas or to the main reference texts in these fields."
    LCSH
    Data mining
    RSWK
    Visualisierung / Computergraphik / Data Mining
    Data Mining / Visualisierung / Aufsatzsammlung (BVB)
    Subject
    Visualisierung / Computergraphik / Data Mining
    Data Mining / Visualisierung / Aufsatzsammlung (BVB)
    Data mining
    Theme
    Data Mining
  17. Peters, G.; Gaese, V.: ¬Das DocCat-System in der Textdokumentation von G+J (2003) 0.11 
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    Abstract
    Wir werden einmal die Grundlagen des Text-Mining-Systems bei IBM darstellen, dann werden wir das Projekt etwas umfangreicher und deutlicher darstellen, da kennen wir uns aus. Von daher haben wir zwei Teile, einmal Heidelberg, einmal Hamburg. Noch einmal zur Technologie. Text-Mining ist eine von IBM entwickelte Technologie, die in einer besonderen Ausformung und Programmierung für uns zusammengestellt wurde. Das Projekt hieß bei uns lange Zeit DocText Miner und heißt seit einiger Zeit auf Vorschlag von IBM DocCat, das soll eine Abkürzung für Document-Categoriser sein, sie ist ja auch nett und anschaulich. Wir fangen an mit Text-Mining, das bei IBM in Heidelberg entwickelt wurde. Die verstehen darunter das automatische Indexieren als eine Instanz, also einen Teil von Text-Mining. Probleme werden dabei gezeigt, und das Text-Mining ist eben eine Methode zur Strukturierung von und der Suche in großen Dokumentenmengen, die Extraktion von Informationen und, das ist der hohe Anspruch, von impliziten Zusammenhängen. Das letztere sei dahingestellt. IBM macht das quantitativ, empirisch, approximativ und schnell. das muss man wirklich sagen. Das Ziel, und das ist ganz wichtig für unser Projekt gewesen, ist nicht, den Text zu verstehen, sondern das Ergebnis dieser Verfahren ist, was sie auf Neudeutsch a bundle of words, a bag of words nennen, also eine Menge von bedeutungstragenden Begriffen aus einem Text zu extrahieren, aufgrund von Algorithmen, also im Wesentlichen aufgrund von Rechenoperationen. Es gibt eine ganze Menge von linguistischen Vorstudien, ein wenig Linguistik ist auch dabei, aber nicht die Grundlage der ganzen Geschichte. Was sie für uns gemacht haben, ist also die Annotierung von Pressetexten für unsere Pressedatenbank. Für diejenigen, die es noch nicht kennen: Gruner + Jahr führt eine Textdokumentation, die eine Datenbank führt, seit Anfang der 70er Jahre, da sind z.Z. etwa 6,5 Millionen Dokumente darin, davon etwas über 1 Million Volltexte ab 1993. Das Prinzip war lange Zeit, dass wir die Dokumente, die in der Datenbank gespeichert waren und sind, verschlagworten und dieses Prinzip haben wir auch dann, als der Volltext eingeführt wurde, in abgespeckter Form weitergeführt. Zu diesen 6,5 Millionen Dokumenten gehören dann eben auch ungefähr 10 Millionen Faksimileseiten, weil wir die Faksimiles auch noch standardmäßig aufheben.
    Date
    22. 4.2003 11:45:36
    Theme
    Data Mining
  18. Strader, C.R.: Author-assigned keywords versus Library of Congress Subject Headings : implications for the cataloging of electronic theses and dissertations (2009) 0.11 
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    Abstract
    This study is an examination of the overlap between author-assigned keywords and cataloger-assigned Library of Congress Subject Headings (LCSH) for a set of electronic theses and dissertations in Ohio State University's online catalog. The project is intended to contribute to the literature on the issue of keywords versus controlled vocabularies in the use of online catalogs and databases. Findings support previous studies' conclusions that both keywords and controlled vocabularies complement one another. Further, even in the presence of bibliographic record enhancements, such as abstracts or summaries, keywords and subject headings provided a significant number of unique terms that could affect the success of keyword searches. Implications for the maintenance of controlled vocabularies such as LCSH also are discussed in light of the patterns of matches and nonmatches found between the keywords and their corresponding subject headings.
    Date
    10. 9.2000 17:38:22
  19. Tunbridge, N.: Semiology put to data mining (1999) 0.11 
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    Theme
    Data Mining
  20. Spertus, E.: ParaSite : mining structural information on the Web (1997) 0.11 
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    Date
    1. 8.1996 22:08:06

Authors

Years

Languages

Types

  • a 3411
  • m 409
  • el 189
  • s 189
  • b 40
  • x 39
  • i 23
  • r 18
  • ? 8
  • p 5
  • d 3
  • n 3
  • u 2
  • z 2
  • au 1
  • h 1
  • More… Less…

Themes

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