• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.111-123
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• 2013

Semantic similarity/relatedness measure between two concepts plays an important role in research on system integration and database integration. Moreover, current research on keyword recommendation or tag clustering strongly depends on this kind of semantic measure. For this reason, many researchers in various fields including computer science and computational linguistics have tried to improve methods to calculating semantic similarity/relatedness measure. This study of similarity between concepts is meant to discover how a computational process can model the action of a human to determine the relationship between two concepts. Most research on calculating semantic similarity usually uses ready-made reference knowledge such as semantic network and dictionary to measure concept similarity. The topological method is used to calculated relatedness or similarity between concepts based on various forms of a semantic network including a hierarchical taxonomy. This approach assumes that the semantic network reflects the human knowledge well. The nodes in a network represent concepts, and way to measure the conceptual similarity between two nodes are also regarded as ways to determine the conceptual similarity of two words(i.e,. two nodes in a network). Topological method can be categorized as node-based or edge-based, which are also called the information content approach and the conceptual distance approach, respectively. The node-based approach is used to calculate similarity between concepts based on how much information the two concepts share in terms of a semantic network or taxonomy while edge-based approach estimates the distance between the nodes that correspond to the concepts being compared. Both of two approaches have assumed that the semantic network is static. That means topological approach has not considered the change of semantic relation between concepts in semantic network. However, as information communication technologies make advantage in sharing knowledge among people, semantic relation between concepts in semantic network may change. To explain the change in semantic relation, we adopt the cognitive semantics. The basic assumption of cognitive semantics is that humans judge the semantic relation based on their cognition and understanding of concepts. This cognition and understanding is called 'World Knowledge.' World knowledge can be categorized as personal knowledge and cultural knowledge. Personal knowledge means the knowledge from personal experience. Everyone can have different Personal Knowledge of same concept. Cultural Knowledge is the knowledge shared by people who are living in the same culture or using the same language. People in the same culture have common understanding of specific concepts. Cultural knowledge can be the starting point of discussion about the change of semantic relation. If the culture shared by people changes for some reasons, the human's cultural knowledge may also change. Today's society and culture are changing at a past face, and the change of cultural knowledge is not negligible issues in the research on semantic relationship between concepts. In this paper, we propose the future directions of research on semantic similarity. In other words, we discuss that how the research on semantic similarity can reflect the change of semantic relation caused by the change of cultural knowledge. We suggest three direction of future research on semantic similarity. First, the research should include the versioning and update methodology for semantic network. Second, semantic network which is dynamically generated can be used for the calculation of semantic similarity between concepts. If the researcher can develop the methodology to extract the semantic network from given knowledge base in real time, this approach can solve many problems related to the change of semantic relation. Third, the statistical approach based on corpus analysis can be an alternative for the method using semantic network. We believe that these proposed research direction can be the milestone of the research on semantic relation.

• Asia pacific journal of information systems
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• v.32 no.1
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• pp.168-190
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• 2022

This review aims to synthesize social network theories by drawing on the importance of social network perspectives in understanding knowledge management with technology in organizations. I provide an overview of prior social network research with the following core ideas: the primacy of relations between organizational actors, the utility of actors' embeddedness in social fields, the social utility of network connections, and the structural patterning of social life. On top of that, I summarize critical social perspectives (the social capital theory, the structural hole theory, the embeddedness perspective, the social exchange theory, the organizational learning theory, and the innovation diffusion theory) to suggest potential research questions for future studies in social network research in the knowledge management discipline.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.5
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• pp.338-344
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• 2014

As the role of information collection becomes increasingly important in the enormous data environment, there is growing demand for more intelligent information technologies for managing complex data. On the other hand, it is difficult to find a solution because of the data complexity and big scaled amount. Accordingly, there is a need for a special intelligent knowledge base frame that can be operated by itself flexibly. In this paper, by adopting switching function for signal transmission in the synapse of the human brain, I/E selective activation based knowledge reconfiguring mechanism is proposed for building more intelligent information management system. In particular, knowledge network design, a special knowledge node structure, Type definition, I/E gauge definition and I/E matching scheme are provided. Using these concepts, the proposed system makes the functions of activation by I/E Gauge, selection and reconfiguration. In a more efficient manner, the routing and reasoning process was performed based on the knowledge reconfiguration network. In the experiments, the process of selection by I/E matching, knowledge reconfiguration and routing & reasoning results are described.

• The Journal of Society for e-Business Studies
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• v.24 no.4
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• pp.49-78
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• 2019

In the context of knowledge sharing, network position has been a controversial subject. A central position in the network provides access to non-redundant knowledge, leading to more opportunities of knowledge sharing. On the other hand, as "bridging" relationships, its characteristics as a "weak tie" suggest innate lack of trust and reciprocity which is considered an impediment to share knowledge. This paper attempts to enlighten the underlying dynamic by examining the interaction between network centrality, motivation and ability in knowledge sharing. Furthermore, this paper examines the concept of knowledge sharing ability in depth by operationalizing the construct into three aspects: extensive and diverse knowledge, social media utilization ability and self-efficacy. The results show a partially supported three-way interaction, where the highest level of knowledge provision is reported when the employee has low network centrality, high autonomous motivation and high knowledge sharing ability, i.e. extensive and diverse prior knowledge. Though all models indicate strong associations between network centrality and knowledge sharing, this suggests an even greater power of motivation and ability that gives the strength to overcome unfavorable environments of peripheral position. Therefore, this paper offers an alternative explanation to the existing debate whether network centrality positively or negatively influences knowledge sharing.

• Knowledge Management Research
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• v.1 no.1
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• pp.47-64
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• 2000

As the Knowledge Economy grows bigger, studies and practices of knowledge management flourish in almost every organizations. Yet, the studies of fundamental relationships between knowledge and organization have not been sufficiently developed. It is partly because current knowledge management mainly focus on the technical aspects of the theme. This paper tries to find the possible organizing principles and theoretical foundations of knowledge-intensive organizations through the perspective of knowledge market and knowledge community. Based on the differentiation of "knowledge" and "knowing", the author draws several propositions about knowledge creation and knowledge use. Then, the author relates these propositions to the design and implementation of two theoretical models of organizations, i. e. knowledge market and knowledge community. Major claims are: 1) Knowledge use and knowledge creation process are conceptually separable, so that different conceptual models (market & community) need to be applied. 2) Since knowledge use and creation should be integrated, organizations in the Knowledge Economy should be the efficient knowledge market and, at the same time, knowledge community with care and cooperations. 3) The network of independent small KIFs(knowledge-intensive firms) could be considered as the possible organizational model of the future.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.327-338
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• 2020

This study wants to test the nexus among resource orientation, market orientation, social network, and knowledge sharing toward organizational innovation, and the nexus between organizational innovation and MSMEs performance. Questionnaires and interviews are conducted with some MSMEs actors in Central Java Province, Indonesia, in Klaten Regency and Pekalongan City. These two areas have creative MSMEs, especially Batik MSMEs that have been very large and known worldwide. The sampling technique is done purposively with certain criteria for the respondents. The data analysis technique is done using Partial Least Square. This study provides recommendations about strategic practice and policy (resource and market), social network, and knowledge sharing in increasing organizational innovation, and the impact of organizational innovation toward MSMEs performance. It also offers a comprehensive model of the determinant factor of organizational innovation by considering the aspect of strategic orientation, social network, and knowledge sharing. Other unique aspects that are also important to consider are social network and the importance of knowledge sharing in improving MSMEs Performance. The respondents are still limited in two areas, namely, Pekalongan and Klaten, so it still cannot represent the whole population. These areas also have different orientation of production process approach, namely, synthetic and natural dyes.

• Knowledge Management Research
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• v.13 no.1
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• pp.1-12
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• 2012

A knowledge map is a network-typed diagram visualizing all kinds of knowledge that influences each other to solve a problem. A knowledge map determines the structure of knowledge categorizing and archiving by defining the relationship of referential navigation among knowledge. Since tremendous and increasing number of knowledge needs to be included in a knowledge map, a knowledge map must be organized automatically by considering the contents and relationships of knowledge. This paper suggests the concept and prototype of a semi-automated knowledge map which automatically maps new piece of knowledge onto a manually provided draft map. The prototype knowledge map is based on the recursive programming to make a knowledge map automatically determine the location of the newly-entered knowledge by considering the referential relationship between knowledge. The proposed knowledge enables the knowledge network to expand autonomously by automatically including and storing knowledge. Also, it can improve the accuracy and applicability of knowledge for problem-solving, because the relationship of referential navigation among knowledge can be efficiently and effectively expressed.

• Knowledge Management Research
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• v.13 no.1
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• pp.13-24
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• 2012

Unlike the traditional belief that knowledge flows along the formal reporting procedures, recent social network research has reported the importance of informal social networks which may play a critical role as the real knowledge conduits. In fact, as a complementary approach of utilizing knowledge management systems (KMSs), many firms have focused on managing informal knowledge flow through which to acquire and transfer valuable knowledge in a fast and effective way. In a case of global companies that have newly developed foreign branches or subsidiaries, due to cultural or institutional differences and lack of understanding of knowledge management and its benefits, they often have difficulties in activating knowledge sharing in local branches. In these situations, diagnosing organizational knowledge flow through SNA can be a first step to solve the problems. Therefore, in this paper, I report on the result of case study on a foreign branch of "A" global company by identifying organizational knowledge paths. Based on the results of the diagnosis, some implications and insights for building knowledge management (KM) strategy specified for a newly developed foreign branch will also be discussed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.410-412
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• 1998

Subsymbolic Knowledge processing is said to be changed states of networks constructed from small elements. subsymbolic systems also make it possible to use connectionist models for knowledge processing. Connectionist realization such modulus are modulus linked together for solving a given problem. We study using neural networks as distinct actions. The output vectors produced by the neural networks are consider as a new facts. These new facts are then processed to activate another networks or used in the current production rule, The production rule is applying knowledge stored in the knowledge base to make inference. After neural networks knowledge base is constructed and trained. We present a running sample of incorporating neural network knowledge base. We implement using rochester connectionist simulator. We suggest that incorporating neural network knowledge base. Therefore incorporated neural network knowledge base ensures a cleaner solution which results in better perfor s.

• Knowledge Management Research
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• v.14 no.3
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• pp.1-13
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• 2013

This study investigates how relational activities within MNC network affect knowledge transfer and performance of subsidiary. We separated the possible relationships between headquarter and overseas subsidiaries by support level, interaction level, and conflict level, and compared the impact on knowledge transfer, and performance. To understand the knowledge sharing, development and performance, we use structural equation modeling to analyze data from subsidiaries in China.