• Asia pacific journal of information systems
• /
• v.30 no.2
• /
• pp.353-373
• /
• 2020

This paper tries to closely look at compliance knowledge relatedness and IT relatedness based on Tanriverdi's 'relatedness' concept. Also, this paper's main focus lies on how knowledge relatedness and IT relatedness influence compliance performance through compliance knowledge exploitation. The present study conducted a full-scale survey and finalized questionnaire was sent to compliance managers of 187 Korean multi-business firms. This study found (1) the impact of compliance knowledge relatedness on compliance performance, (2) the mediating role of knowledge exploitation on the relationship between compliance knowledge relatedness and compliance performance, and (3) the interaction effect of IT relatedness and compliance knowledge relatedness on knowledge exploitation. This paper contributes to both academic and business world by widening applicability of theories and providing guidelines conducive to improved compliance performance of corporations.

• Knowledge Management Research
• /
• v.11 no.4
• /
• pp.41-66
• /
• 2010

This research examines the effect of the relatedness and the gap between Resources and mechanisms on effectiveness of inter-organizational knowledge transfer. According to the literature, there has been a competing theory between two claims; one is that inter-organizational knowledge transfer will be more effective due to the reduction of the transaction cost as the relatedness increases. And the other is that the mutual complementarity of different organizational characteristics will increase synergy. In total, the relatedness and the gap of the Resource and mechanism makes the inverted U-shaped relationship with the inter-organizational knowledge transfer. As the result of empirical analysis about 109 Korean-based Joint Ventures entered country, it shows that the relatedness of parent company's production Resources, learning mechanisms, and coordination mechanisms made the inverted U-shaped relations with the inter-organizational knowledge transfer and the gap of production Resources and adjustment mechanism formed the same relationship. However, the U-shaped relationship has been established in the relatedness of market Resources, but the gap of market Resources and the learning mechanism was not statistically significant. Through this study, I can draw a best conclusion that the inter-organizational knowledge transfer will be more effective when the relatedness and the gap of management resources and mechanisms is in optimal level. However, when it comes to market Resources, it can be inferred that the result could be the opposite because the partner country's market environment would be different.

• ETRI Journal
• /
• v.39 no.2
• /
• pp.191-201
• /
• 2017

This paper proposes an approach using taxonomic relatedness for answer-type recognition and type coercion in a question-answering system. We introduce a question analysis method for a lexical answer type (LAT) and semantic answer type (SAT) and describe the construction of a taxonomy linking them. We also analyze the effectiveness of type coercion based on the taxonomic relatedness of both ATs. Compared with the rule-based approach of IBM's Watson, our LAT detector, which combines rule-based and machine-learning approaches, achieves an 11.04% recall improvement without a sharp decline in precision. Our SAT classifier with a relatedness-based validation method achieves a precision of 73.55%. For type coercion using the taxonomic relatedness between both ATs and answer candidates, we construct an answer-type taxonomy that has a semantic relationship between the two ATs. In this paper, we introduce how to link heterogeneous lexical knowledge bases. We propose three strategies for type coercion based on the relatedness between the two ATs and answer candidates in this taxonomy. Finally, we demonstrate that this combination of individual type coercion creates a synergistic effect.

• Information Systems Review
• /
• v.17 no.1
• /
• pp.19-47
• /
• 2015

The purpose of this research is to represent how ICT relatedness and organization environment influence on interactions between healthcare specialist and patients, and how knowledge sharing influence on healthcare innovation, and how service innovation influence on service performance through structured research model. This research also has applied to resource based view, adaptive structuration theory, service innovation, ICT relatedness to find out performance effect on healthcare service innovation and service performance. In other words, organization structure environment and ICT relatedness are important factors to promote interaction between healthcare service providers and customers like patients each other, moreover, to share the tacit knowledge by creating in the interaction. Moreover in order to verify model fitness, this research has surveyed among healthcare specialists, technicians and other staffs. Model verification result, all hypotheses have been found to give a positive effect on the creation and significantly. Structured organizational environment and ICT association is to promote the organization's functions by influencing the behavior of the service organization and patient interaction and knowledge sharing, and suggests that the major factors influencing the innovation performance of hospitals and health care services.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.2
• /
• pp.111-118
• /
• 2015

Entity linking is to link entity's name mentions occurring in text to corresponding entities within knowledge bases. Since the same entity mention may refer to different entities according to their context, entity linking needs to deal with entity disambiguation. Most recent works on entity disambiguation focus on semantic relatedness between entities and attempt to integrate semantic relatedness with entity prior probabilities and term co-occurrence. To the best of my knowledge, however, it is hard to find studies that analyze and present the pure effects of semantic relatedness on entity disambiguation. From the experimentation on Korean Wikipedia data set, this article empirically evaluates entity disambiguation approaches using semantic relatedness in terms of the following aspects: (1) the difference among semantic relatedness measures such as NGD, PMI, Jaccard, Dice, Simpson, (2) the influence of ambiguities in co-occurring entity mentions' set, and (3) the difference between individual and collective disambiguation approaches.

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

• Journal of the Korean Regional Science Association
• /
• v.37 no.3
• /
• pp.3-18
• /
• 2021

The fourth Industrial Revolution is transforming the industrial structure of the region, and it is necessary to develop new industries and technologies that reflect regional characteristics. The purpose of this study is to measure the knowledge relatedness and technological complexity in Busan, Ulsan, and Gyeongnam, and to identify technologies with potential for regional industrial differentiation strategies. Using patent data from 2015 to 2019, co-occurrence matrices were derived from 652 IPC codes, and the knowledge relatedness density and technology complexity index were calculated. Network analysis was performed using the knowledge relatedness density. As a result of analysis, it was found that mechanical engineering occupied a large proportion, followed by chemistry and electrical engineering. As a result of applying the risk-benefit framework to derive technologies with the potential to differentiate local industries, the technological capabilities of low-risk-high-benefit were different. Among mechanical engineering, technologies such as engine, machine operation, and transportation were included in Busan. In Ulsan, environmental technology in chemical and materials, and heat treatment technology in mechanical engineering were technologies with low-risk and high-benefit capabilities. Gyeongnam showed competence in mechanical engineering, chemistry, and electrical engineering in some areas such as Gimhae, Yangsan, and Changwon. The results of this study are meaningful in that they identified technologies with potential for selecting and deriving strategic industries for regional growth based on latent knowledge in the region.

• Knowledge Management Research
• /
• v.14 no.1
• /
• pp.95-119
• /
• 2013

Although merger and acquisition (M&A) has been considered as an important means to improve firm performance, most prior empirical research have failed to prove the relationship between M&A and firm performance. In order to fill this gap, this study attempts to identify the effect of M&A on firm performance based on knowledge resources relatedness and complementarity theory. For this purpose, this study examines complementarity patterns of knowledge resources and their impacts on acquirer's performance using M&A announcements of electronic commerce industry from 2001 to 2007. The results of this study indicate complementarity among knowledge resources are positively related with acquirer's market value. This study contributes to expand knowledge management research by identifying the relationship among knowledge resources and their impacts on firm performance.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.32 no.1
• /
• pp.247-265
• /
• 2021

Recently, public libraries have increased in quantity, while various problems have arisen regarding the operation of public libraries, such as lack of librarian manpower and facilities. Additionally, an increase in the number of public libraries does not correlate to an increase in the utilization of public libraries, and thus developing various services is needed to maintain the continued use of public libraries. This study examined which types of use motivations affect the intention of knowledge exchange in public libraries when using public libraries based on the self-determination theory. It also looked at how the use motivations and the intention of knowledge exchange vary depending on the frequency of public library use. According to an online survey of 230 users of public libraries, extrinsic motivation, intrinsic motivation, autonomy, competence, and relatedness as independent variables had a positive impact on the level of knowledge exchange. In addition, the higher the frequency of public library use, the higher the needs for autonomy and relatedness were. Based on the results, it was suggested that the knowledge exchange needs to be established as a new service of public libraries by offsetting extrinsic motivation that emerged from by negative influences and promoting intrinsic motivation, autonomy and competence.

• Journal of Information Science Theory and Practice
• /
• v.6 no.2
• /
• pp.46-61
• /
• 2018

The mobile social networking application Instagram is a well-known platform for sharing photos and videos. Since it is folksonomy-oriented, it provides the possibility for image indexing and knowledge representation through the assignment of hashtags to posted content. The purpose of this study is to analyze how Instagram users tag their pictures regarding different kinds of picture and hashtag categories. For such a content analysis, a distinction is made between Food, Pets, Selfies, Friends, Activity, Art, Fashion, Quotes (captioned photos), Landscape, and Architecture image categories as well as Content-relatedness (ofness, aboutness, and iconology), Emotiveness, Isness, Performativeness, Fakeness, "Insta"-Tags, and Sentences as hashtag categories. Altogether, 14,649 hashtags of 1,000 Instagram images were intellectually analyzed (100 pictures for each image category). Research questions are stated as follows: RQ1: Are there any differences in relative frequencies of hashtags in the picture categories? On average the number of hashtags per picture is 15. Lowest average values received the categories Selfie (average 10.9 tags per picture) and Friends (average 11.7 tags per picture); for highest, the categories Pet (average 18.6 tags), Fashion (average 17.6 tags), and Landscape (average 16.8 tags). RQ2: Given a picture category, what is the distribution of hashtag categories; and given a hashtag category, what is the distribution of picture categories? 60.20% of all hashtags were classified into the category Content-relatedness. Categories Emotiveness (about 4.38%) and Sentences (0.99%) were less often frequent. RQ3: Is there any association between image categories and hashtag categories? A statistically significant association between hashtag categories and image categories on Instagram exists, as a chi-square test of independence shows. This study enables a first broad overview on the tagging behavior of Instagram users and is not limited to a specific hashtag or picture motive, like previous studies.