• Journal of the Korean Society for information Management
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• v.33 no.1
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• pp.161-180
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• 2016

Physicians have information needs related to academic research and clinical practice but encounter difficulties seeking appropriate medical resources and information. The goal of this study is to develop a search system to support Korean physicians' information needs. To access sources to meet the identified need, in-depth interviews were conducted, and MediSearching, a new search system, was developed accordingly. To verify its usefulness and to obtain users' suggestions, interviews were conducted and feedback was solicited via collected test searches. The initial set of interviews indicated that physicians' information needs and search behaviors differed by type of hospital and clinical department. Physicians in university hospitals with a greater need for research materials searched for academic articles, whereas physicians in specialty hospitals or primary care clinics with a stronger need for materials related to clinical practice asked their colleagues for information. Consequently, MediSearching was designed to satisfy both groups' needs, and the test search provided useful search results compared with existing services. Korean physicians have previously had to repeat their search process on separate sites that provide different services according to type of information and search method. MediSearching may reduce this inconvenience and add documents in various formats and languages.

• Journal of the Korean Society for information Management
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• v.13 no.1
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• pp.65-82
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• 1996

The aim of this study is to identify how searchers reflect the search goal requirements associated with search questions in process and outcome. One query which has two different search goal requirements was given to subjects, that is, one is to increase high precision and the other is to increase high recall. Using ERIC ONTAP file through DIALOG online search system, 54 subjects conducted online searches twice for the high precision search and for the high recall search. Subjects employed significantly different search strategies, invested significantly different efforts, and achieved significantly different results between the high precision and the high recall search.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.9_10
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• pp.1036-1047
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• 2003

This study was carried out in the purpose of proposing internet marketing strategy which can make conversion rate higher through analysis of internet shopping behavior types. This study was executed in two stages; qualitative study, quantitative study. In the qualitative study, internet shopping behavior types were investigated through the In-depth interview and direct observation, and then in the quantitative study, differences of internet shopping behavior types according to consumer characteristics, product properties and shopping-mall types were examined. For qualitative study, 30 samples by focus sampling were inquired and for quantitative study, 334 data were collected through web survey. The results of this study are as follows: First, 7 Internet shopping behavior types of apparel were found through the qualitative study: cautious purchase by price comparison, searching purchase, special low price purchase, impulse purchase, prepurchase deliberation, information accumulation, recreation-oriented. Second, in relation to consumer characteristics, consumers that have many internet purchase experiences showed goal-directed behavior more and female did more special low price purchase behavior and impulse purchase behavior than male. Third, according to product properties, high price product led more cautious purchase by price comparison & prepurchase deliberation behavior and fashionable product led more information-searching behavior. In the case of low price and fashionable products, impulse purchase behaviors were showed more. Forth, according to Internet shopping mall types, category killer shopping mall visitors showed information search behavior, recreation-oriented behavior more.

• Journal of Digital Convergence
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• v.16 no.4
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• pp.29-37
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• 2018

The purpose of this study is to analyze the effects of self-development competency on employment readiness for job achievement of women's university students and to enhance the recruiting rate of female students ultimately. This paper classified the factors of self-development competency and employment readiness and defined a new research model. This study is meaningful what self-development competency is actually helpful for female undergraduates to get a job. Both self-recognition skill and self-control skill have positive primary effects on their career development skills in self-development competency. Career development skills has a positive secondary effect on not only their goal setting for job seeking but also their searching for job information. This paper suggests that career development skills is of paramount importance so as to improve employment readiness. It is expected that executable education policies and cases can be more developed on the basis of this study.

• Journal of the Korean Society for information Management
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• v.24 no.4
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• pp.191-221
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• 2007

The goal of this study was to examine the relationships between usability and the searching experience, and to uncover where an integrated cataloging and metadata system lay the usability problems of its primary users, catalogers. This study showed that the most important aspect of usability in Connexion lay in the experience of information retrieval system. Also, it showed there are seventeen usability problems to be improved in Connexion. Needless to say, it is most important to note that usability is not an exclusive goal of such an integrated cataloging and metadata system. Other goals such as quality of catalogs, and the reliability of its cataloging and metadata system are equally its concern. This study also suggested more testing on diverse cataloging systems and specific user groups, especially catalogers.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1433-1443
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• 2016

In the cases of the major cities, high poverty rate of the elderly, immature pension policies, and insufficient market conditions, policies and services for the employment of the elderly decrease the desire for the job participation. It is time to prevent the problems of the elderly, and induce the reachable seniors to participate in social activities. This research provides the location-based, customized job-search service for the elderly in order to actively support the participation in the economic activities of the elderly. The goal of SSJS(Smart Senior Job Search) is to provide the individual elderly with the customized position. It prints the appropriate positions near user location based on the residential area, job classification, and the physical condition, and provides the mash-up of the selectable job range in the unit distance based on the map. This customized service, which enables the seniors to select the type of the jobs based on their physical, mental and life conditions of the seniors, supports the participation in economic activities of the elderly people, and contribute to the expansion of the social job positions for the elderly and the equalization of the local development.

• Journal of information and communication convergence engineering
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• v.12 no.1
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• pp.8-13
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• 2014

We consider the sensor selection problem in large sensor networks where the goal is to find the best set of sensors that maximizes application objectives. Since sensor selection typically involves a large number of sensors, a low complexity should be maintained for practical applications. We propose a geometry-based sensor selection algorithm that utilizes only the information of sensor locations. In particular, by observing that sensors clustered together tend to have redundant information, we theorize that the redundancy is inversely proportional to the distance between sensors and seek to minimize this redundancy by searching for a set of sensors with the maximum average distance. To further reduce the computational complexity, we perform an iterative sequential search without losing optimality. We apply the proposed algorithm to an acoustic sensor network for source localization, and demonstrate using simulations that the proposed algorithm yields significant improvements in the localization performance with respect to the randomly generated sets of sensors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1034-1041
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• 2014

This paper propose a fuzzy inference model for obstacle avoidance for a mobile robot with an active camera, which is intelligently searching the goal location in unknown environments using command fusion, based on situational command using an vision sensor. Instead of using "physical sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data. In this paper, "command fusion" method is used to govern the robot motions. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. We describe experimental results obtained with the proposed method that demonstrate successful navigation using real vision data.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.33-40
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• 2005

Recently So far Many low-cost mobile machinery have been produced. Those are being used for study and business. But those are some weak Points which are small-capacity storage and quite low-speed system. If we use general database programs or key-searching algorithm, It could decrease in performance of system. To solve those Problems, we applied CBDS(Compact Binary Digital Search) trie to mobile environment. As a result we could accomplish our goal which are quick searching and low-capacity indexing. We compared with some Java classes such as TreeSet to evaluation. As a result, the velocity of searching was a little slow than B-tree based TreeSet. But the storage space have been decreased by 29 percent. So I think that it would be practical use.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.171-193
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• 2018

LOD(Linked Open Data) cloud is a practical implementation of semantic web. We suggested a new method that provides identity links conveniently in LOD cloud. It also allows changes in LOD to be reflected to searching results without any omissions. LOD provides detail descriptions of entities to public in RDF triple form. RDF triple is composed of subject, predicates, and objects and presents detail description for an entity. Links in LOD cloud, named identity links, are realized by asserting entities of different RDF triples to be identical. Currently, the identity link is provided with creating a link triple explicitly in which associates its subject and object with source and target entities. Link triples are appended to LOD. With identity links, a knowledge achieves from an LOD can be expanded with different knowledge from different LODs. The goal of LOD cloud is providing opportunity of knowledge expansion to users. Appending link triples to LOD, however, has serious difficulties in discovering identity links between entities one by one notwithstanding the enormous scale of LOD. Newly added entities cannot be reflected to searching results until identity links heading for them are serialized and published to LOD cloud. Instead of creating enormous identity links, we propose LOD to prepare its own link policy. The link policy specifies a set of target LODs to link and constraints necessary to discover identity links to entities on target LODs. On searching, it becomes possible to access newly added entities and reflect them to searching results without any omissions by referencing the link policies. Link policy specifies a set of predicate pairs for discovering identity between associated entities in source and target LODs. For the link policy specification, we have suggested a set of vocabularies that conform to RDFS and OWL. Identity between entities is evaluated in accordance with a similarity of the source and the target entities' objects which have been associated with the predicates' pair in the link policy. We implemented a system "Change Acceptable In-Depth Searching System(CAIDS)". With CAIDS, user's searching request starts from depth_0 LOD, i.e. surface searching. Referencing the link policies of LODs, CAIDS proceeds in-depth searching, next LODs of next depths. To supplement identity links derived from the link policies, CAIDS uses explicit link triples as well. Following the identity links, CAIDS's in-depth searching progresses. Content of an entity obtained from depth_0 LOD expands with the contents of entities of other LODs which have been discovered to be identical to depth_0 LOD entity. Expanding content of depth_0 LOD entity without user's cognition of such other LODs is the implementation of knowledge expansion. It is the goal of LOD cloud. The more identity links in LOD cloud, the wider content expansions in LOD cloud. We have suggested a new way to create identity links abundantly and supply them to LOD cloud. Experiments on CAIDS performed against DBpedia LODs of Korea, France, Italy, Spain, and Portugal. They present that CAIDS provides appropriate expansion ratio and inclusion ratio as long as degree of similarity between source and target objects is 0.8 ~ 0.9. Expansion ratio, for each depth, depicts the ratio of the entities discovered at the depth to the entities of depth_0 LOD. For each depth, inclusion ratio illustrates the ratio of the entities discovered only with explicit links to the entities discovered only with link policies. In cases of similarity degrees with under 0.8, expansion becomes excessive and thus contents become distorted. Similarity degree of 0.8 ~ 0.9 provides appropriate amount of RDF triples searched as well. Experiments have evaluated confidence degree of contents which have been expanded in accordance with in-depth searching. Confidence degree of content is directly coupled with identity ratio of an entity, which means the degree of identity to the entity of depth_0 LOD. Identity ratio of an entity is obtained by multiplying source LOD's confidence and source entity's identity ratio. By tracing the identity links in advance, LOD's confidence is evaluated in accordance with the amount of identity links incoming to the entities in the LOD. While evaluating the identity ratio, concept of identity agreement, which means that multiple identity links head to a common entity, has been considered. With the identity agreement concept, experimental results present that identity ratio decreases as depth deepens, but rebounds as the depth deepens more. For each entity, as the number of identity links increases, identity ratio rebounds early and reaches at 1 finally. We found out that more than 8 identity links for each entity would lead users to give their confidence to the contents expanded. Link policy based in-depth searching method, we proposed, is expected to contribute to abundant identity links provisions to LOD cloud.