Digital Evidence Discovery and Knowledge Management Issues Concerning Multimedia Computing Devices Utilizing GPS Navigation Services and Social Network Activities

2011 ◽  
pp. 123-130
Author(s):  
Hai-Cheng Chu ◽  
K. H. Chang ◽  
Yi-Da Wang ◽  
Jong Hyuk Park
Keyword(s):  
Knowledge Management ◽  
Social Network ◽  
Digital Evidence ◽  
Multimedia Computing ◽  
Gps Navigation ◽  
Management Issues

scholarly journals Metamodelo de gestión de conocimiento a partir de análisis so¿cial de lecciones aprendidas [Metamodel knowledge management from social analysis of lessons learned]

2015 ◽  
Author(s):  
José Fernando López Quintero ◽  
Juan Manuel Cueva Lovelle ◽  
Begoña Cristina Pelayo García-Bustelo ◽  
Carlos Enrique Montenegro Marín
Keyword(s):  
Knowledge Management ◽  
Social Network ◽  
Web Services ◽  
Web 2.0 ◽  
Semantic Analysis ◽  
Lessons Learned ◽  
Personal Knowledge ◽  
Redes Sociales ◽  
Functional Architecture ◽  
Amazon Web Services

Este artículo describe el desarrollo de una arquitectura funcional orientada a la Gestión de Conocimiento Personal (GCP), definido desde el concepto de las lecciones aprendidas que se registran en una red social de uso masivo. Esta arquitectura funcional aplica de forma práctica la implementación de un sistema de registro de las lecciones aprendidas personales, en la nube a través de una red social Facebook. El proceso inicia con la adquisición de datos a partir de la conexión a una base de datos no relacional (NoSql) en SimpleDB de Amazon Web Services y a la cual se le ha configurado un algoritmo de análisis complementario para realizar el análisis semántico de la información registrada de las lecciones aprendidas y de esta forma estudiar la generación de Gestión de Conocimiento Organizacional (GCO) desde GCP. El resultado final es el diseño de una arquitectura funcional que permite integrar la aplicación web 2.0 y un algoritmo de análisis semántico a partir de información no estructurada aplicando técnicas de aprendizaje de máquina.Palabras Claves: Gestión de conocimiento, gestión de conocimiento personal, lecciones aprendidas, análisis semántico, computación en la nube, redes sociales, aprendizaje de máquina.This paper shows the development of a functional architecture oriented Personal Knowledge Management (PKM), defined from the concept of lessons learned that are registered in a social network for mass use. This functional architecture applied in a practical implementation of a registration system for personal lessons learned in the cloud through a social network Facebook. The process begins with the acquisition of data from the connection to a non-relational database (NoSQL) in SimpleDB of Amazon Web Services and which you have set up a complementary analysis algorithm for semantic analysis of information recorded lessons learned and thus study the generation of Organizational Knowledge Management (OKM) from PKM. The final result is the design of a functional architecture that enables web 2.0 application integration and semantic analysis of an algorithm from unstructured information using machine learning techniques.Keywords: Management of knowledge, management of personal knowledge, lessons learned, semantic analysis, computing in the cloud, social networks.

Social Network Structures for Explicit, Tacit and Potential Knowledge

2011 ◽  
pp. 81-90
Author(s):  
Anssi Smedlund
Keyword(s):  
Knowledge Management ◽  
Social Network ◽  
Tacit Knowledge ◽  
Network Structure ◽  
Explicit Knowledge ◽  
Network Structures ◽  
Underlying Assumption ◽  
Knowledge Assets ◽  
Social Network Structure

The purpose of this conceptual article is to develop argumentation of the knowledge assets of a firm as consisting of three constructs, to extend the conventional explicit, tacit dichotomy by including potential knowledge. The article highlights the role of knowledge, which has so far not been utilized in value creation. The underlying assumption in the article is that knowledge assets can be thought of as embedded in the relationships between individuals in the firm, rather than possessed by single actors. The concept of potential knowledge is explained with selected social network and knowledge management literature. The findings suggest that the ideal social network structure for explicit knowledge is centralized, for tacit knowledge it is distributed, and for potential knowledge decentralized. Practically, the article provides a framework for understanding the connection between knowledge assets and social network structures, thus helping managers of firms in designing suitable social network structures for different types of knowledge.

A Social Network Perspective on Knowledge Management

2011 ◽  
pp. 2070-2078 ◽  
Author(s):  
Reed E. Nelson ◽  
HY Sonya Hsu
Keyword(s):  
Social Networks ◽  
Knowledge Management ◽  
Social Network ◽  
Organizational Learning

Social networks—the sets of relations that link individuals and collectives—have implications for the speed and effectiveness with which knowledge is created and disseminated in organizations Both social networks and knowledge management (KM) are complex, multifaceted phenomena that are as yet imperfectly understood. Not unsurprisingly, our understanding of the interface between the two is similarly imperfect and evolving. There are, however, a number of foundational concepts upon which existing thought converges as well as a body of emerging research that offers practical and conceptual guidance for developing the kind of network best suited for managing different kinds of knowledge. In this article, we introduce rudimentary network concepts, briefly recapitulate KM and organizational learning concepts related to networks, and then explore some of the interfaces between social networks and KM.

Knowledge Management Within Collaboration Processes

2011 ◽  
pp. 1176-1190
Author(s):  
Jian Cai
Keyword(s):  
Information System ◽  
Knowledge Management ◽  
Social Network ◽  
Collaborative Process ◽  
Distributed Knowledge ◽  
Web Based ◽  
Analysis Methodology ◽  
The Social ◽  
Generic Modeling ◽  
Perspective Model

Collaborative projects are relatively complex and, hence, are difficult to handle. Managing distributed knowledge among stakeholders in a systematic way is crucial to improving the collaboration productivity. This article provides a generic modeling approach that explicitly represents the perspectives of stakeholders and their evolution traversing a collaborative process. This approach provides a mechanism to analytically identify the interdependencies among stakeholders and to detect conflicts and reveal their intricate causes and effects. Collaboration is thus improved through efficient knowledge management. This article also introduces a Web-based information system that uses the perspective model and the social network analysis methodology to support knowledge management within collaboration.

Social Network Analysis

2011 ◽  
pp. 1460-1469
Author(s):  
David J. Dekker ◽  
Paul H.J. Hendriks
Keyword(s):  
Knowledge Management ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Development Project ◽  
Knowledge Networks ◽  
Knowledge Processes ◽  
Social Network Structure ◽  
Product Development Project ◽  
Practice Knowledge

In knowledge management (KM), one perspective is that knowledge resides in individuals who interact in groups. Concepts as communities-of-practice, knowledge networks, and “encultured knowledge” as the outcome of shared sense-making (Blackler, 1995) are built upon this perspective. Social network analysis focuses on the patterns of people’s interactions. This adds to KM theory a dimension that considers the effects of social structure on for example, knowledge creation, retention and dissemination. This article provides a short overview of consequences of social network structure on knowledge processes and explores how the insights generated by social network analysis are valuable to KM as diagnostic elements for drafting KM interventions. Relevance is apparent for management areas such as R&D alliances, product development, project management, and so forth.

A Social Network Perspective on Knowledge Management

2011 ◽  
pp. 826-832
Author(s):  
Reed E. Nelson ◽  
H.Y. Sonya Hsu
Keyword(s):  
Social Networks ◽  
Knowledge Management ◽  
Social Network ◽  
Organizational Learning

Social networks—the sets of relations that link individuals and collectives—have implications for the speed and effectiveness with which knowledge is created and disseminated in organizations Both social networks and knowledge management (KM) are complex, multifaceted phenomena that are as yet imperfectly understood. Not unsurprisingly, our understanding of the interface between the two is similarly imperfect and evolving. There are, however, a number of foundational concepts upon which existing thought converges as well as a body of emerging research that offers practical and conceptual guidance for developing the kind of network best suited for managing different kinds of knowledge. In this article, we introduce rudimentary network concepts, briefly recapitulate KM and organizational learning concepts related to networks, and then explore some of the interfaces between social networks and KM.

Applied Technology in Analysis of Status Quo of University Library Social Network Service and the Treatment Countermeasures

2014 ◽  
Vol 915-916 ◽  
pp. 1327-1331
Author(s):  
Kong Guo Zhu
Keyword(s):  
Knowledge Management ◽  
Social Network ◽  
University Students ◽  
Learning Community ◽  
Evolutionary Game ◽  
Evolutionary Process ◽  
Network Service ◽  
Social Network Service ◽  
University Library ◽  
The Status

More and more university students is getting used to get information through SNS (Social Network Service) as the development of network technology, this make university library SNS play a positive and significant role in university students. Because of the speed and advantages of popularity of SNS, using SNS to make the students establish virtual learning community become the study object of many university libraries. The paper established the evolutionary game model of knowledge management of university library SNS, and analysed its dynamic evolutionary process. Moreover, key factors such as the income, cost, the status of the knowledge management and knowledge absorption which affects the effectiveness of knowledge management were discussed. Finally, the measures on the improvement of domestic university library SNS were put forward.

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