• Journal of Information Science Theory and Practice
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• v.7 no.2
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• pp.54-64
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• 2019

A theory of public knowledge is offered for the purposes of defining more clearly its role in information systems and classification schemas. Public knowledge is knowledge intended to be available for use in a public system. It is knowledge accessible to the public or knowledge in the public arena as opposed to the other seemingly multitudinous ways to describe knowledge. Furthermore, there are many different public arenas or small worlds. Public knowledge, irrespective of these different arenas, has four important overlying characteristics: It is consensual, it does not imply complete truth or certainty, it is autonomous, and it has a constant renewal of old knowledge with new knowledge. Each of these attributes has been culled from a study of the works of Patrick Wilson, Karl Popper, and John Ziman.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.177-182
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• 2020

In the age of technology and information, communicating with people from different cultures is significantly important. Regarding this perspective, communicative competence has been the focus in the EFL educational context. The purpose of this study is to investigate the effectiveness of using movies in a culture-integrated English reading course at the college level. In order to achieve this purpose, pre- and post-reading comprehension tests, pre- and post-surveys and in-depth interviews were conducted. The results of data analysis showed that using movies in the culture-integrated English reading class positively affected students' interest and confidence towards English reading as well as their reading achievement. In this respect, we suggest that cultural teaching through movies in English classes should be learner-centered so that learners can proactively analyze and understand different cultural backgrounds shown in the movies and build schemas which can be used in their learning process.

• Journal of KIISE:Databases
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• v.37 no.2
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• pp.92-103
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• 2010

The Web Ontology Language (OWL) has become the W3C recommendation for publishing and sharing ontologies on the Semantic Web. To derive hidden information from OWL data, a number of OWL reasoners have been proposed. Since OWL reasoners are memory-based, they cannot handle large-sized OWL data. To overcome the scalability problem, RDBMS-based systems have been proposed. These systems store OWL data into a database and perform reasoning by incorporating the use of a database. However, they do not consider complete reasoning on all types of properties defined in OWL and the database schemas they use are ineffective for reasoning. In addition, they do not manage updates to the OWL data which can occur frequently in real applications. In this paper, we compare various database schemas used by RDBMS-based systems and propose an improved schema for efficient reasoning. Also, to support reasoning for all the types of properties defined in OWL, we propose a complete and efficient reasoning algorithm. Furthermore, we suggest efficient approaches to managing the updates that may occur on OWL data. Experimental results show that our schema has improved performance in OWL data storage and reasoning, and that our approaches to managing updates to OWL data are more efficient than the existing approaches.

• Journal of Korean Academy of Nursing
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• v.36 no.4
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• pp.604-611
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• 2006

Purpose. Koreans are one of the fastest growing Asian populations in the U.S. since 1960s. In Korean immigrant women (KIW), breast cancer was reported as the most frequently diagnosed cancer. However, their screening rates for breast cancer are lower than national guidelines; it is assumed that underlying cultural schemas of breast, breast cancer, and its screening modalities exist and need to be studied. This study was aimed to investigate cultural meanings of breast, breast cancer, and breast cancer screenings in KIW. Methods. Using cultural models theory from cognitive anthropology, naturalistic qualitative methodology was utilized. Three focus group interviews with fifteen KIW were conducted. Thematic analysis with constant comparison technique was performed eliciting units of meaning, categories, and themes. Results. The cultural schema of the meaning of breast is 'mother who is breast-feeding her baby,' with two themes of 'balance in size,' and 'shyness.' Regarding breast cancer, three themes, i.e., 'indifference,' 'fear,' and 'uncertainty' are emerged. 'Lack of information about screening modalities' is the overarching schema with reference to breast cancer screenings. Conclusions. The findings of this study demonstrate unique cultural models of KIW related to breast cancer and its screenings, which are critical to understand and penetrate their barriers to breast cancer screening.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.454-457
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• 2005

Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especially when there exist prolific patterns and/or long patterns. And calendar based on temporal association rules proposes the discovery of association rules along with their temporal patterns in terms of calendar schemas, but this approach is also adopt an Apriori-like candidate set generation. In this paper, we propose an efficient temporal frequent pattern mining using TFP-tree (Temporal Frequent Pattern tree). This approach has three advantages: (1) this method separates many partitions by according to maximum size domain and only scans the transaction once for reducing the I/O cost. (2) This method maintains all of transactions using FP-trees. (3) We only have the FP-trees of I-star pattern and other star pattern nodes only link them step by step for efficient mining and the saving memory. Our performance study shows that the TFP-tree is efficient and scalable for mining, and is about an order of magnitude faster than the Apriori algorithm and also faster than calendar based on temporal frequent pattern mining methods.

• The Transactions of the Korea Information Processing Society
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• v.2 no.1
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• pp.12-22
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• 1995

When we integrate schema of distributed local databases, we mean entity integration as central concept of schema integration, and semantic of entity affects several factors. Thus the schema integration in distributed database environment starts from definition of domain relation among entity types of local schemas. Moreover, the domain relation defined by designer needs some works for confidence and validation of schema integration system. But this work was not presented in previous integration system. In this paper, we define object oriented integration for schema integration of local databases in distributed system environment, present models to verify validation on its integration, and implement the validation system.

• Korean Journal of Cognitive Science
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• v.1 no.2
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• pp.347-360
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• 1989

Retearches on epistemology for artificial intelligence have started quite recently.Recently,Konolige made a contribution to epistemology by proposing a deduction model based on an efficieit modal logic for a proof mechanism for belief.In this thesis,a unified and generalized proof mechanism for the epistemic logic using a formal system called a View is pesented.In addition,the algorithm to adapt the theorem prover according to the given rule schema,which charncterizes the deduction model of the epistemic logic,is constructed. With this algorlthm,multiple agents having different rule schemas can co-exist in the proposed system. The soundness and completeness of the proposed proof mechanism is proved and a simple theorem prover is implemented to demonstrate the usefulness and practilcality.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.23-28
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• 2002

A fundamental problem in building an intelligent agent is that an agent does not understand the meaning of its perception or its action. One reason that an agent cannot understand the world is partially caused by a syntactic approach that converts a semantic feature into a simple string. To solve this problem, Cohen introduces a semantic approach that an agent autonomously learns a meaningful representation of physical schemas, on which some advanced conceptual structures are built, from physically interacting with environment using its own sensors and effectors. However, Cohen does not deal with a meta level of conceptual primitive that makes recognizing a schema possible. We propose that negation is a meta schema that enables an agent to recognize a physical schema. We prove some semantic aspects of negation.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1041-1048
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• 2004

Database logs contain various information on database operations, but they are used to recover database systems from failures generally. This paper proposes a log analysis tool that provides useful information for database tuning. This tool provides users with information on work-load organization, database schemas, and resources usages of queries. This paper describes the tool in views of its architecture, functions, implementation, and verification. The tool is verified by running the TPC-W benchmark, and representative analysis results are also presented.

• Journal of Computing Science and Engineering
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• v.8 no.2
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• pp.94-106
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• 2014

Schema matching is widely used in many applications, such as data integration, ontology merging, data warehouse and dataspaces. In this paper, we propose a novel matching technique that is based on the order of attributes appearing in the schema structure of query results. The appearance order embodies the extent of the importance of an attribute for the user examining the query results. The core idea of our approach is to collect statistics about the appearance order of attributes from the query logs, to find correspondences between attributes in the schemas to be matched. As a first step, we employ a matrix to structure the statistics around the appearance order of attributes. Then, two scoring functions are considered to measure the similarity of the collected statistics. Finally, a traditional algorithm is employed to find the mapping with the highest score. Furthermore, our approach can be seen as a complementary member to the family of the existing matchers, and can also be combined with them to obtain more accurate results. We validate our approach with an experimental study, the results of which demonstrate that our approach is effective, and has good performance.