• Journal of Digital Convergence
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• v.10 no.8
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• pp.287-297
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• 2012

In order to prepare for the introduction of the E-Discovery system from the United States and to cope with some causable changes of legal systems, we propose a general E-Discovery process and essential tasks of the each phase. The proposed process model is designed by the analysis of well-known projects such as EDRM, The Sedona Conference, which are advanced research for the standardization of E-Discovery task procedures and for the supply of guidelines to hands-on workers. In addition, Machine Learning Algorithms, Open-source libraries for the Information Retrieval and Distributed Processing technologies based on the Hadoop for big data are introduced and its application methods on the E-Discovery work scenario are proposed. All this information will be useful to vendors or people willing to develop the E-Discovery service solution. Also, it is very helpful to company owners willing to rebuild their business process and it enables people who are about to face a major lawsuit to handle a situation effectively.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.5
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• pp.1171-1183
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• 2016

Today, many domestic companies often face the lawsuits from the U.S. companies as they expand their business in the U.S. market and it is necessary for the domestic companies to prepare for the e-Discovery process in the systematic manner. Yet, the e-discovery system has not been properly established in Korea, however, domestic companies are growing more and more interests in e-Discovery processes and procedures so that they are seeking for the appropriate actions that they should take when facing lawsuits. When adopting the e-Discovery system in Korea, there are three main considerations including the differences in laws and regulations, enterprise system and language and company culture. This study aims to draw the problems for the Korean domestic companies in responding the U.S. lawsuits and to suggest the specialized e-discovery processes and procedures to effectively overcome them.

• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.151-175
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• 2007

Until now, most semantic web service discovery research has been carried out using either Web Service Modeling Ontology (WSMO) or a profile of OWL-based Web Service ontology (OWL-S). However, such efforts have focused primarily on service name and input/output ontology. Thus, the internal information of a service has not been utilized, and queries regarding internal information such as 'Find book-selling services allowing payment after delivery' are not addressed. This study outlines the development of TM-S (Topic Maps for Service) ontology and TMS-QL (TM-S Query Language), two novel technologies that address the aforementioned issues in semantic web service discovery research. TM-S ontology describes the behavior of services using process information and consists of three sub-ontologies: process signature ontology, process structure ontology and process concept ontology. TMS-QL allows users to describe service discovery requests.

• Journal of the Korean Society for information Management
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• v.38 no.2
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• pp.201-226
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• 2021

Discovery's collection was originally paper documents, but with the advent of the digital age, its collection expanded. Resolving the issue of ESI has now become important in litigation. Therefore, this study analyzes the requirements of each domain for electronic records to be recognized as evidence. It also explained the factors that should be considered in record management. In addition, eDiscovery in the United States was selected as an advanced case to utilize records as evidence. This study investigated the Commentary on Legal Holdings: The Trigger & The Process and analyzed which functions must be considered in order for electronic records to be preserved as evidence. To this end, we analyze the functional requirements of the eDiscovery solution. Through this, necessary functional requirements are derived to help implement the system in preparation for eDiscovery.

• The Journal of Society for e-Business Studies
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• v.9 no.4
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• pp.85-102
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• 2004

Currently, developed technologies for semantic web services discovery are based on ontologies. These ontologies are DAML-S(DARPA Agent Markup Language for Services) and Process Handbook Project of MIT. These technologies have some problems for intelligent web services discovery. So, in this paper we analyzed those ontologies and proposed TM-S, Topic Maps for Services. TM-S is the presentation model for semantic web services. And TM-S includes benefits and complements weaknesses of those ontologies. And we proposed TMS-QL, TM-S Query Language. TMS-QL is query language for intelligent web services discovery. At last, we designed and implemented intelligent web service discovery system that deals TM-S ontology and TMS-QL

• The Journal of Society for e-Business Studies
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• v.10 no.3
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• pp.85-110
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• 2005

OWL-S has a major leadership in the field of Web Service discovery and is being actively studied in LARKS and METEOR-S projects. These researches do not consider all components of OWL-S standards, and it is needed to enhance their discovery algorithms. In this paper, we propose matching algorithms based on process information such as process structure matching, service classification matching and business pattern matching algorithms. We also improve the QoS matching algorithm of METEOR-S project. Finally, we integrate these two kinds of matching algorithms as accommodate users preferences.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1128-1135
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• 2003

e-Transformation of an enterprise requires the collaboration of business processes to be suited to the business participants' purpose. To realize this collaboration, business processes should be implemented as components and the system developers could be able to reuse the components for their specific purpose. The first step of this collaboration is the discovery of exact components for business processes. A dilemma, however, is the fact that there are thousands or even millions of business processes which vary from one enterprise to another. Moreover, business processes could be decomposed into multiple levels of semantics and classified into several process areas. In general, discovery of exact business processes requires understanding of widely adopted classification schemes such as CBPC, OAGIS, or SCOR. To cope with this obstacle, business process metadata should be defined and managed regardless of specific classification schemes to support effective discovery and reuse of business processes components. In this paper, a methodology to discover business process components published in different semantic levels is proposed. The proposed methodology represents the metadata of business process components as topic maps stored in a registry and utilizes the powerful features of topic maps for process discovery. TM4J, an open-source topic map engine, is modified to support concept matching and navigation. With the implemented tool, application system developers can discover and publish the business process components effectively.

• Journal of the Korean Society for information Management
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• v.33 no.4
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• pp.125-157
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• 2016

As the domestic companies which have made inroads into foreign markets have more lawsuits, these companies' demands for responding to E-Discovery are also increasing. E-Discovery, derived from Anglo-American law, is the system to find electronic evidences related to lawsuits among scattered electronic data within limited time, to review them as evidences, and to submit them. It is not difficult to find, select, review, and submit evidences within limited time given the reality that the domestic companies do not manage their records even though lots of electronic records are produced everyday. To reduce items to be reviewed and proceed the process efficiently is one of the most important tasks to win a lawsuit. The Predictive Coding is a computer assisted review instrument used in reviewing process of E-Discovery, which is to help companies review their own electronic data using mechanical learning. Predictive Coding is more efficient than the previous computer assister review tools and has a merit to select electronic data related to lawsuit. Through companies' selection of efficient computer assisted review instrument and continuous records management, it is expected that time and cost for reviewing will be saved. Therefore, in for companies to respond to E-Discovery, it is required to seek the most effective method through introduction of the professional Predictive Coding solution and Business records management with consideration of time and cost.

• Proceedings of the CALSEC Conference
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• 2003.09a
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• pp.191-196
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• 2003

The Semantic web service is able to intelligently discover, execute, composite and monitor the Web Service. It constructs the ontology on Web Service and describes the Semantic Markup in the machine-readable form. The currently developing technologies of the Semantic Web Service discovery are DAML-S matchmaker in Carnegie Mellon University, Process Handbook in MIT and etc. In this paper, we propose the ontology language based on Topic Maps that supports the benefits and solves the problems of the Semantic Web Service discovery technologies .

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.431-434
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• 2001

Knowledge discovery in databases(KDD) is the process for extracting valid, novel, potentially useful and understandable knowledge form real data. There are many academic and industrial activities with new technologies and application areas. Particularly, data mining is the core step in the KDD process, consisting of many algorithms to perform clustering, pattern recognition and rule induction functions. The main goal of these algorithms is prediction and description. Prediction means the assessment of unknown variables. Description is concerned with providing understandable results in a compatible format to human users. We introduce an efficient data mining algorithm considering predictive and descriptive capability. Reasonable pattern is derived from real world data by a revised neural network model and a proposed fuzzy rule extraction technique is applied to obtain understandable knowledge. The proposed neural network model is a hierarchical self-organizing system. The rule base is compatible to decision makers perception because the generated fuzzy rule set reflects the human information process. Results from real world application are analyzed to evaluate the system\`s performance.