Search (37 results, page 1 of 2)

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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.

Series

Morgan Kaufmann series in data management systems

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Abstract

Whereas traditional science maps emphasize citation statistics and static relationships, this paper presents a term-based method to identify and visualize the evolutionary pathways of scientific topics in a series of time slices. First, we create a data preprocessing model for accurate term cleaning, consolidating, and clustering. Then we construct a simulated data streaming function and introduce a learning process to train a relationship identification function to adapt to changing environments in real time, where relationships of topic evolution, fusion, death, and novelty are identified. The main result of the method is a map of scientific evolutionary pathways. The visual routines provide a way to indicate the interactions among scientific subjects and a version in a series of time slices helps further illustrate such evolutionary pathways in detail. The detailed outline offers sufficient statistical information to delve into scientific topics and routines and then helps address meaningful insights with the assistance of expert knowledge. This empirical study focuses on scientific proposals granted by the United States National Science Foundation, and demonstrates the feasibility and reliability. Our method could be widely applied to a range of science, technology, and innovation policy research, and offer insight into the evolutionary pathways of scientific activities.

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Series

United States Patent 20050171760

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Abstract

Semantische Netze unterstützen den Suchvorgang im Information Retrieval. Sie bestehen aus relationierten Begriffen und helfen dem Nutzer das richtige Vokabular zur Fragebildung zu finden. Eine leicht und intuitiv erfassbare Darstellung und eine interaktive Bedienungsmöglichkeit optimieren den Suchprozess mit der Begriffsstruktur. Als Interaktionsform bietet sich Hy-pertext mit dem etablierte Point- und Klickverfahren an. Eine Visualisierung zur Unterstützung kognitiver Fähigkeiten kann durch eine Darstellung der Informationen mit Hilfe von Punkten und Linien erfolgen. Vorgestellt wer-den die Anwendungsbeispiele Wissensnetz im Brockhaus multimedial, WordSurfer der Firma BiblioMondo, SpiderSearch der Firma BOND und Topic Maps Visualization in dandelon.com und im Portal Informationswis-senschaft der Firma AGI - Information Management Consultants.

Date

30. 1.2007 18:22:41

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Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 68(2016) no.3, S.265-285

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Source

Information processing and management. 37(2001) no.4, S.639-657

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Abstract

Purpose - This paper aims to explore the theory and practice of knowledge organization and its necessary connection to human perception, and shows a solution of the potential ones. Design/methodology/approach - The author attempts to survey the problem of concept-building and extension, as well as the determination of semantics in different aspects. The purpose is to find criteria for the choice of the solution that best incorporates users into the design cycles of knowledge organization systems. Findings - It is widely agreed that cognition provides the basis for concept-building; however, at the next stage of processing there is a debate. Fundamentally, what is the connection between perception and the superior cognitive processes? The perceptual method does not separate these two but rather considers them united, with perception permeating cognition. By contrast, the linguistic method considers perception as an information-receiving system. Separate from, and following, perception, the cognitive subsystems then perform information and data processing, leading to both knowledge organization and representation. We assume by that model that top-level concepts emerge from knowledge organization and representation. This paper points obvious connection of visual imagery and the internet; perceptual access of knowledge organization and information retrieval. There are some practical and characteristic solutions for the visualization of information without demand of completeness. Research limitations/implications - Librarians need to identify those semantic characteristics which stimulate a similar conceptual image both in the mind of the librarian and in the mind of the user. Originality/value - For a fresh perspective, an understanding of perception is required as well.

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Abstract

This article aims to stimulate research on business process oriented knowledge infrastructures by pointing to the power of visualizations. It claims that business process oriented knowledge infrastructure research is stuck and therefore needs to reinvent and revitalize itself with new impulses. One such stimulus is the use of visualization techniques in business process oriented knowledge infrastructures, with the aim to improve knowledge transfer, knowledge communication, and knowledge creation. First, this article presents an overview on related visualization research. Second, it proposes the Knowledge Visualization Framework as a theoretical backbone where business process oriented knowledge infrastructure research can anchor itself. The framework points to the key questions that need to be answered when visual methods are used in business process oriented knowledge infrastructures. Finally, the article compares the Tube Map Visualization with the Gantt Chart, and proves that the new format excels the traditional approach in regards to various tasks. The findings from the evaluation of 44 interviews indicates that the Project Tube Map is more effective for (1) drawing attention and keeping interest, (2) presenting overview and detail, (3) visualizing who is collaborating with whom, (4) motivating people to participate in the project, and (5) increasing recall. The results presented in this paper are important for researchers and practitioners in the fields of Knowledge Management, Knowledge Visualization, Project Management, and Visual Communication Sciences.

Source

Journal of universal knowledge management. 0(2005) no.2, S.170-188

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Abstract

In this demonstration we present a visual analysis approach that addresses both developers and users of hierarchical classification systems. The approach supports an intuitive understanding of the structure and current use in relation to a specific collection. We will also demonstrate its application for the development and management of library collections.

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Abstract

Icon system could represent an efficient solution for collective iconic categorization of knowledge by providing graphical interpretation. Their pictorial characters assist visualizing the structure of text to become more understandable beyond vocabulary obstacle. In this paper we are proposing a Knowledge Engineering (KM) based iconic representation approach. We assume that these systematic icons improve collective knowledge management. Meanwhile, text (constructed under our knowledge management model - Hypertopic) helps to reduce the diversity of graphical understanding belonging to different users. This "position paper" also prepares to demonstrate our hypothesis by an "iconic social tagging" experiment which is to be accomplished in 2011 with UTT students. We describe the "socio semantic web" information portal involved in this project, and a part of the icons already designed for this experiment in Sustainability field. We have reviewed existing theoretical works on icons from various origins, which can be used to lay the foundation of robust "icons systems".

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Abstract

Semantische Netze unterstützen den Suchvorgang im Information Retrieval. Sie bestehen aus relationierten Begriffen und helfen dem Nutzer, das richtige Vokabular zur Fragebildung zu finden. Eine leicht und intuitiv erfassbare Darstellung und eine interaktive Bedienungsmöglichkeit optimieren den Suchprozess mit der Begriffsstruktur. Als Interaktionsform bietet sich Hypertext mit seinem Point- und Klickverfahren an. Die Visualisierung erfolgt als Netzstruktur aus Punkten und Linien. Es werden die Anwendungsbeispiele Wissensnetz im Brockhaus multimedial, WordSurfer der Firma BiblioMondo, SpiderSearch der Firma BOND und Topic Maps Visualization in dandelon.com und im Portal Informationswissenschaft der Firma AGI - Information Management Consultants vorgestellt.

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Source

Information processing and management. 41(2005) no.4, S.1003-1018

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Content

Diese Publikation entstand im Rahmen einer Thesis zum Master of Science FHO in Business Administration, Major Information and Data Management.

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Date

30. 5.2010 16:22:35

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Date

1. 2.2016 18:25:22

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Source

Information processing and management. 39(2003) no.6, S.923-940

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Abstract

Purpose - The purpose of this paper is to report an investigation into the ways in which Canadian digital library collections have incorporated knowledge organization systems into their search interfaces. Design/methodology/approach - A combination of data-gathering techniques was used. These were as follows: a review of the literature related to the application of knowledge organization systems, deep scanning of Canadian governmental and academic institutions web sites on the web, identify and contact researchers in the area of knowledge organization, and identify and contact people in the governmental organizations who are involved in knowledge organization and information management. Findings - A total of 33 digital collections were identified that have made use of some type of knowledge organization system. Thesauri, subject heading lists and classification schemes were the widely used knowledge organization systems in the surveyed Canadian digital library collections. Research limitations/implications - The target population for this research was limited to governmental and academic digital library collections. Practical implications - An evaluation of the knowledge organization systems interfaces showed that searching, browsing and navigation facilities as well as bilingual features call for improvements. Originality/value - This research contributes to the following areas: digital libraries, knowledge organization systems and services and search interface design.

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Source

Information processing and management. 49(2013) no.5, S.1019-1048

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Source

Information processing and management. 49(2013) no.5, S.1139-1164