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User Approach to Knowledge Discovery in Networked Environment

Copyright © 2010. 17 pages.
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DOI: 10.4018/978-1-60566-906-9.ch018
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MLA

Kuusisto, Rauno. "User Approach to Knowledge Discovery in Networked Environment." Data Mining in Public and Private Sectors: Organizational and Government Applications. IGI Global, 2010. 358-374. Web. 1 Sep. 2014. doi:10.4018/978-1-60566-906-9.ch018

APA

Kuusisto, R. (2010). User Approach to Knowledge Discovery in Networked Environment. In A. Syvajarvi, & J. Stenvall (Eds.) Data Mining in Public and Private Sectors: Organizational and Government Applications (pp. 358-374). Hershey, PA: Information Science Reference. doi:10.4018/978-1-60566-906-9.ch018

Chicago

Kuusisto, Rauno. "User Approach to Knowledge Discovery in Networked Environment." In Data Mining in Public and Private Sectors: Organizational and Government Applications, ed. Antti Syvajarvi and Jari Stenvall, 358-374 (2010), accessed September 01, 2014. doi:10.4018/978-1-60566-906-9.ch018

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Abstract

Collaboration and networking demands are increasing and lots of organizational communicative activities have moved into technical networks. Need to understand not only how to refine right information contents out of the available data mass but also what type of information is important in various information using situations has increased. This chapter delves into the problem area of finding ways to support users to find relevant, specific types of information that is related to various phases of operating in network. Establishing a network, planning operations and managing operations differ from each others what comes into information requirements. It will be shown via four generalized cases that information requirements vary depending on what phase of networking activity the organization is. Via those cases that are based on sufficiently broad empirical material it will be cleared that knowledge requirements differ from situation to another. This leads to a conclusion that flexible data mining and knowledge discovery systems shall be constructed.
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Introduction

The increasing amount of various available data and information has been a powerful engine for the research of data mining and knowledge discovery. Methodology and procedure discovery and development to sort out relevant and reliable information out of vast masses of ever evolving and increasing data space have been successfully developed. In addition, a great amount of solutions that help to discover relevant key words or key expressions exist. However those solutions are mainly targeted to marketing development purposes, not for networking purposes. For networking purposes lots of social media tools and other more sophisticated collaboration solutions exist, but they do not answer the challenge of finding comprehensively right type of information. They rather support people to find other people who are interested in same kinds of areas and items leaving information discovery on the responsibility of the users. So, the question “How to do it?” is frequently expressed and answered in case of knowledge discovery. A less studied area is what kind or type of information shall be discovered for certain information using situations. This kind of situations exist e.g. in networked business environment and inter-authority collaboration situations. The question “What to do?” that is relevant in this kind of situations is expressed more seldom under the topic of knowledge discovery.

The purpose of this chapter is to introduce a less frequently expressed perspective to knowledge discovery. This chapter describes an example of high-level ontology to solve challenges faced when developing algorithms for networking in emergent and evolving communication environment. Algorithms are not introduced. The focal point is to introduce the difference of information requirements between various phases in collaboration situations. Via those differences it will be demonstrated that knowledge discovery requirements vary also from situation to another. Information is dealt not with content but with framework level. This allows finding general phenomena of inter-working situations thus making possible to solve general knowledge discovery algorithms in complex collaboration environment. Empirical material is collected in the context of authority cooperation.

The working environment of organizations has changed due the extensive use of information technology. Organizations are more or less interrelated to each others and lots of activities are executed using technical tools and networks. Relationships are changing more or less frequently making working environment challenging. New relationships are constructed while others are in execution phase containing planning and decision-making. Those phases differ from each others thus requiring different type of information exchanged. Organizations are interdependent with each others with certain cross-organizational and non-organization specific processes. They have common interests concerning certain objectives in certain situations. Information technology glues organizations together in two ways. It enables collaboration and the use of non-organizational specific services, and it enables somewhat free information publishing and gathering. The organization independent information domain makes inter-organizational relationships complex and emergent by nature. This emergence cannot be controlled, but the content of mutually available information can be structurized to some degree by using processual and technological tools. Knowledge discovery is about combining information to find hidden knowledge. This chapter describes what type of knowledge shall be discovered when acting in evolving cooperation environment. Knowledge discovery can be seen as a tool to enable more sophisticated way for organizations to optimize their efforts to gain their goals on adequate networking level.

Cross-organizational collaboration situations in inter-authority context are analyzed to increase understanding about the activity environment, where knowledge discovery needs may occur. It will be shown that information needs will vary depending on the phase of activity of an actor. The main research question is: “What type of information shall be discovered to serve actors´ needs during different phases of its activity?” This question is dealt with examples based on empirical findings of several collaboration situations of inter-working authorities. The analysis of these cases is based on multi-theoretical model of human information handling.

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Complete Chapter List

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Table of Contents
Foreword
Gerald Quirchmayr
Preface
Antti Syvajarvi, Jari Stenvall
Chapter 1
Dries Verlet, Carl Devos
Although policy evaluation has always been important, today there is a rising attention for policy evaluation in the public sector. In order to... Sample PDF
Before the Mining Begins: An Enquiry into the Data for Performance Measurement in the Public Sector
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Chapter 2
José Luis Zafra-Gómez, Antonio Manuel Cortés-Romero
In local government, the financial analysis is focused on evaluating the financial condition of municipalities, and this is normally accomplished... Sample PDF
Measuring the Financial Crisis in Local Governments through Data Mining
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Chapter 3
Malcolm J. Beynon, Martin Kitchener
The chapter exposits the strategies employed by the public long-term care systems operated by each U.S. state government. The central technique... Sample PDF
Data Mining Using Fuzzy Decision Trees: An Exposition from a Study of Public Services Strategy in the USA
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Chapter 4
Zdravko Pecar, Ivan Bratko
The aim of this research was to study the performance of 58 Slovenian administrative districts (state government offices at local level), to... Sample PDF
The Use of Data Mining for Assessing Performance of Administrative Services
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Chapter 5
Aki Jääskeläinen, Paula Kujansivu, Jaani Väisänen
Productivity is a key success factor in any organization. In order to improve productivity, it is necessary to understand how various factors affect... Sample PDF
Productivity Analysis of Public Services: An Application of Data Mining
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Chapter 6
John C. Molluzzo, James P. Lawler, Pascale Vandepeutte
Mobile computing is a maturing technology with benefits for consumers. The purpose of this chapter is to furnish research on the perceptions of... Sample PDF
Perceptions of Students on Location-Based Privacy and Security with Mobile Computing Technology
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Chapter 7
Aris Gkoulalas-Divanis, Vassilios S. Verykios
Since its inception in 2000, privacy preserving data mining has gained increasing popularity in the data mining research community. This line of... Sample PDF
Privacy Preserving Data Mining: How Far Can We Go?
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Chapter 8
Konrad Stark, Michael Ilger, Wilfried N. Gansterer
Retaining electronic communication and internet traffic data imposes novel technical and organisational challenges for internet service providers as... Sample PDF
Data Mining Challenges in the Context of Data Retention
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Chapter 9
Oliver Krone
Understanding data mining (DM) as part of Information Systems (IS) this contribution investigates the question how this subordination is reasoned in... Sample PDF
On Data Mining and Knowledge: Questions of Validity
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Chapter 10
Jue Wang, Wei Xu, Xun Zhang, Yejing Bao, Ye Pang, Shouyang Wang
In this study, two data mining based models are proposed for crude oil price analysis and forecasting, one of which is a hybrid wavelet... Sample PDF
Data Mining Methods for Crude Oil Market Analysis and Forecast
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Chapter 11
Vincent Lemaire, Carine Hue, Olivier Bernier
This chapter presents a new method to analyze the link between the probabilities produced by a classification model and the variation of its input... Sample PDF
Correlation Analysis in Classifiers
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Chapter 12
Mirco Nanni, Laura Spinsanti
In large-scale retail trade, a very significant problem consists in analyzing the response of clients to product promotions. The aim of the project... Sample PDF
Forecast Analysis for Sales in Large-Scale Retail Trade
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Chapter 13
Goran Klepac
A business case presents a retail company facing new competitors and consequently preparing a customer retention strategy. The business environment... Sample PDF
Preparing for New Competition in the Retail Industry
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Chapter 14
Malcolm J. Beynon, Rhys Andrews
The non-trivial extraction of implicit, previously unknown, interesting, and potentially useful information is at the heart of efforts to solve... Sample PDF
An Exposition of CaRBS Based Data Mining: Investigating Intra Organization Strategic Consensus
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Chapter 15
Jukka Aaltonen, Annamari Turunen, Ilkka Kamaja
In the field of information technology (IT) enabled business networks and research the traditional data mining approach is theoretically and... Sample PDF
Data Mining In the Context of Business Network Research
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Chapter 16
Irwin Epstein, Lynette Joubert
Clinical Data Mining (CDM) is a paradigm of practice-based research that engages practitioners in analyzing and evaluating routinely recorded... Sample PDF
Clinical Data Mining in the Age of Evidence-Based Practice: Recent Exemplars and Future Challenges
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Chapter 17
Emanuel Camilleri
The chapter illustrates how data mining and knowledge management concepts may be applied in a project oriented environment for both the private and... Sample PDF
Data Mining and the Project Management Environment
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Chapter 18
Rauno Kuusisto
Collaboration and networking demands are increasing and lots of organizational communicative activities have moved into technical networks. Need to... Sample PDF
User Approach to Knowledge Discovery in Networked Environment
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