The Principle of Justifiable Granularity and an Optimization of Information Granularity Allocation as Fundamentals of Granular Computing

Pedrycz, Witold Korea Information Processing Society 2011 Journal of information processing systems Vol.7 No.3

Granular Computing has emerged as a unified and coherent framework of designing, processing, and interpretation of information granules. Information granules are formalized within various frameworks such as sets (interval mathematics), fuzzy sets, rough sets, shadowed sets, probabilities (probability density functions), to name several the most visible approaches. In spite of the apparent diversity of the existing formalisms, there are some underlying commonalities articulated in terms of the fundamentals, algorithmic developments and ensuing application domains. In this study, we introduce two pivotal concepts: a principle of justifiable granularity and a method of an optimal information allocation where information granularity is regarded as an important design asset. We show that these two concepts are relevant to various formal setups of information granularity and offer constructs supporting the design of information granules and their processing. A suite of applied studies is focused on knowledge management in which case we identify several key categories of schemes present there.

Development of Personal Information Protection Model using a Mobile Agent

Bae, Seong-Hee,Kim, Jae-Joon Korea Information Processing Society 2010 Journal of information processing systems Vol.6 No.2

This paper proposes a personal information protection model that allows a user to regulate his or her own personal information and privacy protection policies to receive services provided by a service provider without having to reveal personal information in a way that the user is opposed to. When the user needs to receive a service that requires personal information, the user will only reveal personal information that they find acceptable and for uses that they agree with. Users receive desired services from the service provider only when there is agreement between the user's and the service provider's security policies. Moreover, the proposed model utilizes a mobile agent that is transmitted from the user's personal space, providing the user with complete control over their privacy protection. In addition, the mobile agent is itself a self-destructing program that eliminates the possibility of personal information being leaked. The mobile agent described in this paper allows users to truly control access to their personal information.

Fuzzy Linguistic Recommender Systems for the Selective Diffusion of Information in Digital Libraries

Porcel, Carlos,Ching-Lopez, Alberto,Bernabe-Moreno, Juan,Tejeda-Lorente, Alvaro,Herrera-Viedma, Enrique Korea Information Processing Society 2017 Journal of information processing systems Vol.13 No.4

The significant advances in information and communication technologies are changing the process of how information is accessed. The internet is a very important source of information and it influences the development of other media. Furthermore, the growth of digital content is a big problem for academic digital libraries, so that similar tools can be applied in this scope to provide users with access to the information. Given the importance of this, we have reviewed and analyzed several proposals that improve the processes of disseminating information in these university digital libraries and that promote access to information of interest. These proposals manage to adapt a user's access to information according to his or her needs and preferences. As seen in the literature one of the techniques with the best results, is the application of recommender systems. These are tools whose objective is to evaluate and filter the vast amount of digital information that is accessible online in order to help users in their processes of accessing information. In particular, we are focused on the analysis of the fuzzy linguistic recommender systems (i.e., recommender systems that use fuzzy linguistic modeling tools to manage the user's preferences and the uncertainty of the system in a qualitative way). Thus, in this work, we analyzed some proposals based on fuzzy linguistic recommender systems to help researchers, students, and teachers access resources of interest and thus, improve and complement the services provided by academic digital libraries.

The Design of the IIR Differintegrator and its Application in Edge Detection

Jain, Madhu,Gupta, Maneesha,Jain, N.K. Korea Information Processing Society 2014 Journal of information processing systems Vol.10 No.2

New IIR digital differintegrators (differentiator and integrator) with very minor absolute relative errors are presented in this paper. The digital integrator is designed by interpolating some of the existing integrators. The optimum value of the interpolation ratio is obtained through linear programming optimization. Subsequently, by modifying the transfer function of the proposed integrator appropriately, new digital differentiator is obtained. Simulation results demonstrate that the proposed differintegrator are a more accurate approximation of ideal ones, than the existing differintegrators. Furthermore, the proposed differentiator has been tested in an image processing application. Edges characterize boundaries and are, therefore, a problem of fundamental importance in image processing. For comparison purpose Prewitt, Sobel, Roberts, Canny, Laplacian of Gaussian (LOG), Zerocross operators were used and their results are displayed. The results of edge detection by some of the existing differentiators are also provided. The simulation results have shown the superiority of the proposed approach over existing ones.

An Active Co-Training Algorithm for Biomedical Named-Entity Recognition

Munkhdalai, Tsendsuren,Li, Meijing,Yun, Unil,Namsrai, Oyun-Erdene,Ryu, Keun Ho Korea Information Processing Society 2012 Journal of information processing systems Vol.8 No.4

Exploiting unlabeled text data with a relatively small labeled corpus has been an active and challenging research topic in text mining, due to the recent growth of the amount of biomedical literature. Biomedical named-entity recognition is an essential prerequisite task before effective text mining of biomedical literature can begin. This paper proposes an Active Co-Training (ACT) algorithm for biomedical named-entity recognition. ACT is a semi-supervised learning method in which two classifiers based on two different feature sets iteratively learn from informative examples that have been queried from the unlabeled data. We design a new classification problem to measure the informativeness of an example in unlabeled data. In this classification problem, the examples are classified based on a joint view of a feature set to be informative/non-informative to both classifiers. To form the training data for the classification problem, we adopt a query-by-committee method. Therefore, in the ACT, both classifiers are considered to be one committee, which is used on the labeled data to give the informativeness label to each example. The ACT method outperforms the traditional co-training algorithm in terms of f-measure as well as the number of training iterations performed to build a good classification model. The proposed method tends to efficiently exploit a large amount of unlabeled data by selecting a small number of examples having not only useful information but also a comprehensive pattern.

The Effects Of Structured Methods On Object Orientation : A Knowledge Interference Prospective

김인재,정덕훈,Kim, In-Jai,Jeong, Duke-Hoon Korea Information Processing Society 2002 정보처리학회논문지D Vol.9 No.5

새로운 정보기술의 생명주기는 점점 작아지고 그 기술이 점차 복잡해짐에 따라 그 기술을 이해하기가 어려워진다. 본 연구의 목적은 객체 지향 기술의 채택에 관한 이해를 돕기 위하여 객체지향 기술이 전통적인 소프트웨어 프로세스 기술과는 다른 패러다임의 기술이기 때문에 프로세스 중심의 구조지향 기술로부터 영향을 받을 것으로 판단된다. 본 연구는 구조지향 방법이 객체지향 방법론에 미치는 지식간섭 현상을 일종의 2$\times$2 팩토리얼 유사 실험계획법을 사용하여 실증적으로 분석하였다. 구조지향 방법론과 객체지향 방법론을 사용한 기간을 2개의 독려변수로 선택하였고 객체지향 방법론에 대한 사용 편의성을 1개의 독립변수로 설정하였다 자료는 현재 활동중인 구조지향 및 객체지향 방법론에 모두 경험이 있는 자료처리와 관리협회(DPMA : Data Processing and Management Association) 회원으로부터 수집하였다 최종 결과는 구조지향 방법론의 경험이 객체지향 방법론의 사용편의성에 부의 영향을 주는 것으로 나타났다. 향후 연구과제로 문화가 다른 국가에서 유사한 연구 수행한 후에 그 결과를 비교하는 것도 의미가 있을 것이다. The life cycle of new information technologies is getting shorter, and the technologies are becoming more complex and difficult to understand. The need to better understand adoption of object orientation motivates this paper. Adoption of object orientation should certainly be influenced by prior software process technologies, such as the process-oriented structured methods, because object orientation is considered to be a paradigm shift from conventional software process technologies. This study aims to empirically analyze knowledge interference of the structured methods with object orientation. A two factorial quasi-experimental design is set forth. The period of experience using the structured methods and the period of experience using object orientation are selected as two independent variables, and the perceived ease of use is chosen as one dependent variable. Data are gathered from active members of Data Processing Management Association (DPMA), who have experiences in using both the structured methods and object orientation. The final results empirically show that previous experience using the structured methods negatively influences the perception of using object orientation that is one of critical factors to technology adoption. It is suggested here that a future study dealing with the same research topic in other countries will provide new insights about comparative studies.

An Efficient Web Ontology Storage Considering Hierarchical Knowledge for Jena-based Applications

Jeong, Dong-Won,Shin, Hee-Young,Baik, Doo-Kwon,Jeong, Young-Sik Korea Information Processing Society 2009 Journal of information processing systems Vol.5 No.1

As well as providing various APIs for the development of inference engines and storage models, Jena is widely used in the development of systems or tools related with Web ontology management. However, Jena still has several problems with regard to the development of real applications, one of the most important being that its query processing performance is unacceptable. This paper proposes a storage model to improve the query processing performance of the original Jena storage. The proposed storage model semantically classifies OWL elements, and stores an ontology in separately classified tables according to the classification. In particular, the hierarchical knowledge is managed, which can make the processing performance of inferable queries enhanced and stores information. It enhances the query processing performance by using hierarchical knowledge. For this paper an experimental evaluation was conducted, the results of which showed that the proposed storage model provides a improved performance compared with Jena.

Batch Resizing Policies and Techniques for Fine-Grain Grid Tasks: The Nuts and Bolts

Muthuvelu, Nithiapidary,Chai, Ian,Chikkannan, Eswaran,Buyya, Rajkumar Korea Information Processing Society 2011 Journal of information processing systems Vol.7 No.2

The overhead of processing fine-grain tasks on a grid induces the need for batch processing or task group deployment in order to minimise overall application turnaround time. When deciding the granularity of a batch, the processing requirements of each task should be considered as well as the utilisation constraints of the interconnecting network and the designated resources. However, the dynamic nature of a grid requires the batch size to be adaptable to the latest grid status. In this paper, we describe the policies and the specific techniques involved in the batch resizing process. We explain the nuts and bolts of these techniques in order to maximise the resulting benefits of batch processing. We conduct experiments to determine the nature of the policies and techniques in response to a real grid environment. The techniques are further investigated to highlight the important parameters for obtaining the appropriate task granularity for a grid resource.

Two-Dimensional Qualitative Asset Analysis Method based on Business Process-Oriented Asset Evaluation

Eom, Jung-Ho,Park, Seon-Ho,Kim, Tae-Kyung,Chung, Tai-Myoung Korea Information Processing Society 2005 Journal of information processing systems Vol.1 No.1

In this paper, we dealt with substantial asset analysis methodology applied to two-dimensional asset classification and qualitative evaluation method according to the business process. Most of the existent risk analysis methodology and tools presented classification by asset type and physical evaluation by a quantitative method. We focused our research on qualitative evaluation with 2-dimensional asset classification. It converts from quantitative asset value with purchase cost, recovery and exchange cost, etc. to qualitative evaluation considering specific factors related to the business process. In the first phase, we classified the IT assets into tangible and intangible assets, including human and information data asset, and evaluated their value. Then, we converted the quantitative asset value to the qualitative asset value using a conversion standard table. In the second phase, we reclassified the assets using 2-dimensional classification factors reflecting the business process, and applied weight to the first evaluation results. This method is to consider the organization characteristics, IT asset structure scheme and business process. Therefore, we can evaluate the concrete and substantial asset value corresponding to the organization business process, even if they are the same asset type.

Systematic Review of Bug Report Processing Techniques to Improve Software Management Performance

Lee, Dong-Gun,Seo, Yeong-Seok Korea Information Processing Society 2019 Journal of information processing systems Vol.15 No.4

Bug report processing is a key element of bug fixing in modern software maintenance. Bug reports are not processed immediately after submission and involve several processes such as bug report deduplication and bug report triage before bug fixing is initiated; however, this method of bug fixing is very inefficient because all these processes are performed manually. Software engineers have persistently highlighted the need to automate these processes, and as a result, many automation techniques have been proposed for bug report processing; however, the accuracy of the existing methods is not satisfactory. Therefore, this study focuses on surveying to improve the accuracy of existing techniques for bug report processing. Reviews of each method proposed in this study consist of a description, used techniques, experiments, and comparison results. The results of this study indicate that research in the field of bug deduplication still lacks and therefore requires numerous studies that integrate clustering and natural language processing. This study further indicates that although all studies in the field of triage are based on machine learning, results of studies on deep learning are still insufficient.