• Proceedings of the Korean Information Science Society Conference
• /
• 2004.04b
• /
• pp.589.2-861
• /
• 2004

XML 문서를 변환하는 목적은 하나의 어플리케이션에서 사용되는 XML 문서를 다른 XML 어플리케이션에서 재 사용하여 사용자에게 동일한 정보를 제공하는데 있다 XML 문서는 어플리케이션 특성에 따라 한 문서에서 전달할 수 있는 정보의 량이 다르다. 따라서 문서를 변환하기 전에 어플리케이션의 특성에 따라 문서를 분할하거나 병합하여야 한다[1]. 또한, XML 문서의 정보는 속성에 따라 문법적인 특성을 가진다. 본 논문은 문벌적인 특성을 의미 속성이라 하고 의미 속성을 파악하기 위해 XML 문서의 의미 구조와 의미 구조 관계를 정의한다. 그리고 정의된 의미 구조와 의에 구조 관계를 이용하여 문서 정보의 속성을 분류하는 방법을 제안한다. 변환 규칙은 의ロP 구조 관계가 유사한 엘리먼트간의 대응으로 정의하고, 변환 규칙을 이용하여 문서 변환을 실행하여 변환 XML과 의미 관계 구조가 유사한 피 변환 XML 문서를 생성한다. 의미구조 분석을 이용한 변환은 기존의 사용 패턴을 분석한 변환에서 벗어나 DTD의 분석을 통한 자동화된 문서 변환 방법을 제공한다.

• Journal of Korea Multimedia Society
• /
• v.9 no.7
• /
• pp.773-781
• /
• 2006

XML is a standard language to express and exchange the data over the web. Recently, researches about techniques that storing XML documents into RDBMS and managing it have been progressed. These researches use a technique that are receiving the DTD document as an input and generate the relational schema from it. Existing researches, however, do not consider the semantic preservation because of the simplification of the DTD. Further, because existing studies only focus on the preservation technique to store information such as content and structure, there is a troublesomeness that have to use the stored-procedure or trigger for the data integrity during the stores of XML documents. This paper proposes a improved Inlining technique to create effective relations and to preserve semantics which can be inferred from DTD.

• Journal of Korea Society of Industrial Information Systems
• /
• v.17 no.6
• /
• pp.31-40
• /
• 2012

Ubiquitous technology influences on various firms of contents needed for self-healthcare, as it fuses into medical services. Particularly, rapid changes in the web and mobile environment, requiring various sorts of healthcare and its related contents, make efficiency of search more important. Personalized contents needs to be more refined as well as the existing simple keyword-centered searching method needs to be more effective in order to meet both requirements and characteristics of each patient or each user. A precise semantic searching method is required for a system to understand promptly the meaning of a contents. In this respect, to build a healthcare ontology has its own significance. This study builds up a system model that can be utilized practically in existing systems by setting up the Food Class and its sub-class among the healthcare contents with Protege tool and then materializing constraints and its relationships between each class. The healthcare contents ontology provides patients or users with a platform which can search the needed information promptly and precisely.

• Journal of KIISE:Software and Applications
• /
• v.30 no.1_2
• /
• pp.40-50
• /
• 2003

Ontology is the artifacts for representing the truth or the states of objects by defining objects and their relations. In this paper, we propose an agent that classifies Web documents and provides personalized information towards user`s information needs using ontology. the agent uses ontology in which semantic relations on Web documents are represented in ta hierarchical form to classify Web documents. In this paper, ontology consists of concepts, features(describing concepts), relations(among concepts) and constraints(among elements in a feature). The agent can capture user's information needs efficiently by using ontology and assist Web navigation by using users profiles and the results of identification of semantic relations in Web documents. Also, the agent obtains Web documents by a look-ahead search and represents them as concepts, therefore users can understand them easily by receiving recommendations expressed in the form of high-level concepts.

• Journal of Information Science Theory and Practice
• /
• v.9 no.2
• /
• pp.66-82
• /
• 2021

Recommender Systems have gained immense popularity due to their capability of dealing with a massive amount of information in various domains. They are considered information filtering systems that make predictions or recommendations to users based on their interests and preferences. The more recent technology, Linked Open Data (LOD), has been introduced, and a vast amount of Resource Description Framework data have been published in freely accessible datasets. These datasets are connected to form the so-called LOD cloud. The need for semantic data representation has been identified as one of the next challenges in Recommender Systems. In a LOD-enabled recommendation framework where domain awareness plays a key role, the semantic information provided in the LOD can be exploited. However, dealing with a big chunk of the data from the LOD cloud and its integration with any domain datasets remains a challenge due to various issues, such as resource constraints and broken links. This paper presents the challenges of interconnecting and extracting the DBpedia data with the MovieLens 1 Million dataset. This study demonstrates how LOD can be a vital yet rich source of content knowledge that helps recommender systems address the issues of data sparsity and insufficient content analysis. Based on the challenges, we proposed a few alternatives and solutions to some of the challenges.

• The KIPS Transactions:PartD
• /
• v.12D no.1 s.97
• /
• pp.165-178
• /
• 2005

A product classification scheme is the foundation on which product databases are designed, and plays a central role in almost all aspects of management and use of product information. It needs to meet diverse user views to support efficient and convenient use of product information. It needs to be changed and evolved very often without breaking consistency in the cases of introduction of new products, extinction of existing products, class reorganization, and class specialization. It also needs to be merged and mapped with other classification schemes without information loss when B2B transactions occur. For these requirements, a classification scheme should be so dynamic that it takes in them within right time and cost. The existing classification schemes widely used today such as UNSPSC and eCl@ss, however, have a lot of limitations to meet these requirements for dynamic features of classification. Product information implies a plenty of semantics such as class attributes like material, time, place, etc., and integrity constraints. In this Paper, we analyze the dynamic features of product databases and the limitation of existing code based classification schemes, and describe the semantic classification model proposed in [1], which satisfies the requirements for dynamic features of product databases. It provides a means to explicitly and formally express more semantics for product classes and organizes class relationships into a graph.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.11a
• /
• pp.592-594
• /
• 2005

XML은 현재 어플리케이션에서 데이터를 저장하는 W3C 표준으로 많은 응용 분야에서 사용되고 있다. 어떤 응용 프로그램에서 사용하던 기존의 XML문서를 다른 응용 프로그램에서 재사용하기 위해서는 변환 XML 문서가 가지고 있는 정보와 구조의 손실 없이 피 변환 XML의 구조에 합당하게 변환해야 한다. XML 문서 정보의 의미는 엘리먼트를 통해 표현되는데 자동으로 분석하여 변환에 적용하기 어렵다. 그러나 XML 문서는 DTD나 XML 스키마와 같은 구조적 정보를 가지고 있고 XML의 구조 정보는 엘리먼트에 속성을 표현한다. 이에 착안하여 DTD의 의미정보를 분석하여 XML 문서의 변환에 적용하는 방법이 제안되었다. 하지만 DTD는 지원하는 데이터 형식이 한정되어 있고 엘리먼트의 반복 속성도 제안되어 있다. 본 논문은 XML의 엘리먼트 정보를 분석하기 위해서 XML 스키마를 사용한다. XML 스키마는 기존에 DTD보다 다수의 데이터 타일과 엘리먼트의 반복적 속성을 다양하게 제공하고 있다. 그러므로 기존 방법보다 더 많은 정보를 변환에 적용할 수 있는 장점을 가지고 있다. 제안하는 시스템은 한번 작성한 XML 문서를 다른 XML 어플리케이션에서 재사용함으로써 XML 문서 제작성에 따른 비용을 절감할 것으로 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.3
• /
• pp.576-599
• /
• 2013

Protocol reverse engineering is useful for many security applications, including intelligent fuzzing, intrusion detection and fingerprint generation. Since manual reverse engineering is a time-consuming and tedious process, a number of automatic techniques have been proposed. However, the accuracy of these techniques is limited due to the complexity of binary instructions, and the derived formats have missed constraints that are critical for security applications. In this paper, we propose a new approach for protocol format extraction. Our approach reasons about only the evaluation behavior of a program on the input message from concolic execution, and enables field identification and constraint inference with high accuracy. Moreover, it performs binary analysis with low complexity by reducing modern instruction sets to BIL, a small, well-specified and architecture-independent language. We have implemented our approach into a system called Icefex and evaluated it over real-world implementations of DNS, eDonkey, FTP, HTTP and McAfee ePO protocols. Experimental results show that our approach is more accurate and effective at extracting protocol formats than other approaches.

• The KIPS Transactions:PartD
• /
• v.14D no.7
• /
• pp.819-828
• /
• 2007

In this paper, we propose a topic maps matching and merging approach based on the syntactic or semantic characteristics and constraints of the topic maps. Previous schema matching approaches have been developed to enhance effectiveness and generality of matching techniques. However they are inefficient because the approaches should transform input ontologies into graphs and take into account all the nodes and edges of the graphs, which ended up requiring a great amount of processing time. Now, standard languages for developing ontologies are RDF/OWL and Topic Maps. In this paper, we propose an enhanced version of matching and merging technique based on topic partitioning, several matching operations and merging conflict detection.

• Journal of KIISE:Databases
• /
• v.33 no.1
• /
• pp.102-116
• /
• 2006

Electronic catalogs (or e-catalogs) hold information about the goods and services offered or requested by the participants, and consequently, form the basis of an e-commerce transaction. Catalog management is complicated by a number of factors and product classification is at the core of these issues. Classification hierarchy is used for spend analysis, custom3 regulation, and product identification. Classification is the foundation on which product databases are designed, and plays a central role in almost all aspects of management and use of product information. However, product classification has received little formal treatment in terms of underlying model, operations, and semantics. We believe that the lack of a logical model for classification Introduces a number of problems not only for the classification itself but also for the product database in general. It needs to meet diverse user views to support efficient and convenient use of product information. It needs to be changed and evolved very often without breaking consistency in the cases of introduction of new products, extinction of existing products, class reorganization, and class specialization. It also needs to be merged and mapped with other classification schemes without information loss when B2B transactions occur. For these requirements, a classification scheme should be so dynamic that it takes in them within right time and cost. The existing classification schemes widely used today such as UNSPSC and eClass, however, have a lot of limitations to meet these requirements for dynamic features of classification. In this paper, we try to understand what it means to classify products and present how best to represent classification schemes so as to capture the semantics behind the classifications and facilitate mappings between them. Product information implies a plenty of semantics such as class attributes like material, time, place, etc., and integrity constraints. In this paper, we analyze the dynamic features of product databases and the limitation of existing code based classification schemes. And describe the semantic classification model, which satisfies the requirements for dynamic features oi product databases. It provides a means to explicitly and formally express more semantics for product classes and organizes class relationships into a graph. We believe the model proposed in this paper satisfies the requirements and challenges that have been raised by previous works.