• Asia pacific journal of information systems
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• v.21 no.2
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• pp.89-116
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• 2011

In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.77-83
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• 2015

Frequent pattern mining, which is one of the major areas actively studied in data mining, is a method for extracting useful pattern information hidden from large data sets or databases. Moreover, frequent pattern mining approaches have been actively employed in a variety of application fields because the results obtained from them can allow us to analyze various, important characteristics within databases more easily and automatically. However, traditional frequent pattern mining methods, which simply extract all of the possible frequent patterns such that each of their support values is not smaller than a user-given minimum support threshold, have the following problems. First, traditional approaches have to generate a numerous number of patterns according to the features of a given database and the degree of threshold settings, and the number can also increase in geometrical progression. In addition, such works also cause waste of runtime and memory resources. Furthermore, the pattern results excessively generated from the methods also lead to troubles of pattern analysis for the mining results. In order to solve such issues of previous traditional frequent pattern mining approaches, the concept of representative pattern mining and its various related works have been proposed. In contrast to the traditional ones that find all the possible frequent patterns from databases, representative pattern mining approaches selectively extract a smaller number of patterns that represent general frequent patterns. In this paper, we describe details and characteristics of pattern condensing techniques that consider the maximality or closure property of generated frequent patterns, and conduct comparison and analysis for the techniques. Given a frequent pattern, satisfying the maximality for the pattern signifies that all of the possible super sets of the pattern must have smaller support values than a user-specific minimum support threshold; meanwhile, satisfying the closure property for the pattern means that there is no superset of which the support is equal to that of the pattern with respect to all the possible super sets. By mining maximal frequent patterns or closed frequent ones, we can achieve effective pattern compression and also perform mining operations with much smaller time and space resources. In addition, compressed patterns can be converted into the original frequent pattern forms again if necessary; especially, the closed frequent pattern notation has the ability to convert representative patterns into the original ones again without any information loss. That is, we can obtain a complete set of original frequent patterns from closed frequent ones. Although the maximal frequent pattern notation does not guarantee a complete recovery rate in the process of pattern conversion, it has an advantage that can extract a smaller number of representative patterns more quickly compared to the closed frequent pattern notation. In this paper, we show the performance results and characteristics of the aforementioned techniques in terms of pattern generation, runtime, and memory usage by conducting performance evaluation with respect to various real data sets collected from the real world. For more exact comparison, we also employ the algorithms implementing these techniques on the same platform and Implementation level.

• Journal of Korea Water Resources Association
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• v.44 no.4
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• pp.295-304
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• 2011

For effective water quality management, it is necessary to secure reliable water quality information. There are many variables that need to be included in a comprehensive practical monitoring network : representative sampling locations, suitable sampling frequencies, water quality variable selection, and budgetary and logistical constraints are examples, especially sampling location is considered to be the most important issues. Until now, monitoring network design for water quality management was set according to the qualitative judgments, which is a problem of representativeness. In this paper, we propose network design system for optimal water quality monitoring using the scientific statistical techniques. Network design system is made based on the SAS program of version 9.2 and configured with simple input system and user friendly outputs considering the convenience of users. It applies to Excel data format for ease to use and all data of sampling location is distinguished to sheet base. In this system, time plots, dendrogram, and scatter plots are shown as follows: Time plots of water quality variables are graphed for identifying variables to classify sampling locations significantly. Similarities of sampling locations are calculated using euclidean distances of principal component variables and dimension coordinate of multidimensional scaling method are calculated and dendrogram by clustering analysis is represented and used for users to choose an appropriate number of clusters. Scatter plots of principle component variables are shown for clustering information with sampling locations and representative location.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.3
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• pp.76-84
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• 2003

Software agents reduce human involvement to a certain extent by automating routine tasks. However, most of agents have assisted with only a few steps in the multi-steps process of electronic transactions. In order to help users with the important steps in the electronic transactions, software agents need to persuade other parties to act in particular ways. While negotiations have many shapes and forms, this paper focuses on a particular class of negotiation, that is competitive business environment based negotiation. For negotiation with other parties in this contort, it is necessary for autonomous agents to consider environmental variables-the number of competitors, the number of negotiation parties, the maximum time by which they must finish their jobs, and user's preferences. Previous negotiation decision functions for the automated negotiation have used only time or the static numbs of negotiating parties as negotiation criteria, although competitive business environment should include potential competitors who can snatch negotiation parties away. This paper attempts to evaluate the performance of a negotiation decision function that considers the potential competitors in competitive market environment as well as that of a negotiation decision function that does not. For this evaluation, this study adopts the electronic marketplace as an application domain because many buyers and sellers compete for limited resources in the marketplace.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.5
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• pp.141-150
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• 2014

In recent years, because of the development of ubiquitous technology in healthcare research is actively progress. Especially, healthcare service area is change to home for the elderly or patients from hospital. The technology to identify residents in a home is crucial for smart home application services. However, existing researches for resident identification have several problems. In this case, residents are needed to attach of various sensors on their body. Also relating private life, it is difficult to apply to resident's environment. In this paper, we used constraint-free sensor and unconscious sensor to solve these problems and we limited using of sensor and indoor environment in the way of working economical price systems. The way of multi-resident identification using only these limited sensors, we selected elements of personal identifications and suggested the methods in giving the weight to apply these elements to systems. And we designed the SABA mechanism to tract their location and identify the residents. It mechanism can distinguish residents through the sensors located each space and can finally identify them by using the records of their behaviors occurred before. And we applied the mechanism designed for applications to approve this location tracking system. We verified to the location tracking system performance according to the scenario.

• Cartoon and Animation Studies
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• s.47
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• pp.273-294
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• 2017

Korea has suffered numerous casualties due to a lot of accidents caused by safety insufficiency in recent years. Therefore, safety education is more important than ever before, and 'how to educate with what contents' is an important subject. Especially, experience education is effective rather than theoretical education because of the nature of safety education. However, it is not easy to design and develop these safety education programs. There is not much opportunity to access first-aid training, which is a part of safety education, unless it is compulsory to learn through public institutions. As a result, program utilization on safety education in Korea is still insufficient to what it should be. With that taken into account, this study proposed an effective serious game with fun and immersion for medical first-aid education. To do this, we analyzed five medical games through 20 cases of first-aid applications and elicited five factors that enhance the usability of serious games. With an analysis of five medical games, we selected one game to borrow the game rules, and applied the elicited five elements in the forms of level-up structure, iterative learning, compensation outcomes, competition system, and information transfer. The proposed medical education functional games should have 1) a character that plays a role of a patient, 2) a narrative flow that shows the situation, 3) the user should judge the situation and induce first aid. 4) compensation, levels, and simple repetition should be designed, and 5) information should be shared with the others in the given community. The results of this study is believed to contribute to enhance the medical emergency education in Korea.

• Journal of Navigation and Port Research
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• v.36 no.6
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• pp.475-480
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• 2012

In order to establish eLoran (enhanced Long Range Navigation) system, it needs the advancement of receiver, transmitter, data channel addition for Loran information, differential Loran sites for compensating Loran-c signal and ASFs (Additional Secondary Factors) database, etc. In addition, the precise synchronization of transmitting station to the UTC (Coordinated Universal Time) is essential if Loran delivers the high absolute accuracy of navigation demanded for maritime harbor entrance. For better timing synchronization to the UTC among transmitting stations, it is necessary to measure and monitor the transmission delay of the station, and the correction information of the transmitting station should be provided to the user's receivers. In this paper we presented the measurement method of absolute delay of Pohang Loran transmitting station and developed a time delay measurement system and a phase monitoring system for Loran station. We achieved -2.23 us as a result of the absolute phase delay of Pohang station and the drift of Loran pulse of the station was measured about 0.3 us for a month period. Therefore it is necessary to measure the delay offset of transmitting station and to compensate the drift of the Loran signal for the high accuracy application of PNT (Positioning, Navigation and Timing).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.374-380
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• 2017

The Internet of Things (IoT) refers to intelligent technologies and services that connect all things to the internet so they can interactively communicate with people, other things, and other systems. The development of the IoT environment accompanies advances in network protocols applicable to more lightweight and intelligent sensors, and lightweight and diverse environments. The development of those elemental technologies is promoting the rapid progress in smart car environments that provide safety features and user convenience. These developments in smart car services will bring a positive effect, but can also lead to a catastrophe for a person's life if security issues with the services are not resolved. Although smart cars have various features with different types of communications functions to control the vehicles under the existing platforms, insecure features and functions may bring various security threats, such as bypassing authentication, malfunctions through illegitimate control of the vehicle via data forgery, and leaking of private information. In this paper, we look at types of smart car services in the IoT, deriving the security threats from smart car services based on various scenarios, suggesting countermeasures against them, and we finally propose a safe smart car application plan.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.7
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• pp.307-314
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• 2017

Stick-PC is small and portable, So it can be used like a desktop if you connect it to a display device such as a monitor or TV anytime and anywhere. Accordingly, Stick-PC can related to various crimes, and various evidence may remain. Stick-PC uses the same Windows version of the operating system as the regular Desktop, the artifacts to be analyzed are the same. However, unlike the Desktop, it can be used as a meaningful information for forensic investigation if it is possible to identify the actual user and trace the usage by finding the traces of peripheral devices before analyzing the system due to the mobility. In this paper, We presents a method of collecting images using Bootable OS, which is one of the image collection methods of Stick-PC. In addition, we show how to analyze the trace of peripheral connection and network connection trace such as Display, Bluetooth through the registry and event log, and suggest the application method from the forensic point of view through experimental scenario.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.239-244
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• 2008

We lead a life in our community, beginning a new relationship with a stranger or maintaining or stopping existing relationships. Relationships with others are sustained through social activities based on communication. Generally speaking, by exchanging feelings and information through communication, relationships are formed and continued, and strengthened through active communication As a result of the development of technologies and information technology over the recent 10 years, a mobile phone has stood as a communication channel, and now it has become such a universal, and highly intimate and important means of communication that almost all the Koreans use more often than wired phones. Today, people have their communication channel available for others, by using a mobile phone at any time and anywhere. Like this, mobile phones have been playing a key role in helping people maintain, repair and strengthen their personal relationship, but from the perspective of personal relationship management, they still remain as an aid to help communication, failing to provide a positive help for actual relationship management. This study was designed to provide services supporting user's personal relationship management, focusing on the use of mobile phones as a major tool of communication, aiming to enable users to understand current state of their relationship and make relationship management efforts, or communication behaviors, by informing who needs communication, on the basis of data on mobile phone calls. To this end, the study established a method to extract intimacy between users and callers and develop a prototype of services supporting personal relationship management, using relationship characteristics in terms of mobile communication.