• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.730-733
• /
• 2004

Recently XML (eXtensible Markup Language) is becoming the standard for exchanging the documents on the web. And as the amount of information is increasing because of the development of the technique in the Internet, semantic web is becoming to appear for more exact result of information retrieval than the existing one on the web. Ontology which is the basis of the semantic web provides the basic knowledge system to express a particular knowledge. So it can show the exact result of the information retrieval. Ontology defines the particular concepts and the relationships between the concepts about specific domain and it has the hierarchy similar to the taxonomy. In this paper, we propose the generation of semi-automatic ontology based on XML documents that are interesting to many researchers as the means of knowledge expression. To construct the ontology in a particular domain, we suggest the algorithm to determine the domain. So we determined that the domain of ontology is to extract the information of movie on the web. And we used the generalized association rules, one of data mining methods, to generate the ontology, using the tag and contents of XML documents. And XTM (XML Topic Maps), ISO Standard, is used to construct the ontology as an ontology language. The advantage of this method is that because we construct the ontology based on the terms frequently used documents related in the domain, it is useful to query and retrieve the related domain.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.27 no.1
• /
• pp.42-49
• /
• 2017

Studies for efficient information retrieval and reuse of information resources using the ontology techniques are being in progress in various fields. In this paper, we build an ontology to provide a food additive information for consumers given by the KFDA and food safety information portal. Food additives were represented in OWL based knowledge using $Prot{\acute{e}}g{\acute{e}}$. We defined Class, Property, Relationships for providing food additives names, origins, purposes and basic information. In order to retrieve the information of the food additive, we built 679 instances with an ontology, and confirmed the results through DL Query queries. We can expect that the food additives ontology shown in this paper will help the integration and improvement of the information retrieval systems of the related fields in future.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.19 no.40
• /
• pp.81-90
• /
• 1996

It is one of the most important thing to select pneumatic components in pneumatic system design. For the purpose of selecting pneumatic components, case objects are described as a knowledge representation and the most similar case object must be selected by decision making in computer. In this paper, case objects are represented using the methodology that is used for CBR(Case Base Reasoning) and methodology that the most similar case can be selected is Proposed. Algorithm VIWNNR(Varying Index Weight-based Nearer Neighbor Retrieval) is accomplished by varying index weight, that is not considering a index matching as true or false but varying a size of weight according to the degree of matching and enhance the flexibility of SCRM(Similar Case Retrieval Module) involving fuzzy concept in matching the cases. SCRM is tested In verify the feasibility to select pneumatic linear components and is peformed effectively.

• Journal of Korea Multimedia Society
• /
• v.13 no.12
• /
• pp.1843-1854
• /
• 2010

The utilization of underground space has recently increased with the complication of road, the rise of the land price, and the development of green technology. Underground space ranges from classical excavations to subway, underground cities, and shopping malls where there are crowds of people. At this time, government has spent a lot of money in installing various types of safety facilities for preparations of increasing potential disasters. Therefore, an effective facility management system is required. In this paper, we propose an information retrieval process to effectively extract the facilities' information based on the ontology and spatial analysis in underground space. The ontology-based searching supports hierarchical and associated results as well as knowledge sharing with hierarchy concepts. The spatial analysis based searching has "Buffer" and "Near" functions to operate on a map without understanding any property of the facility information.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2001.05a
• /
• pp.774-779
• /
• 2001

If rotating machinery have a fault, we can detect it using vibration or noise signals. However some maintenance engineers who doesn't have expert knowledge, needs the help of vibration experts for diagnosing rotating machinery. But qualified experts are rare, therefore we have been developed the case based reasoning (CBR) system which is able to manipulate the past experiences of vibration diagnosis experts. In the CBR system, the maintenance engineers can retrieve too information from previous cases which are most similar to new problem and they can solve new problem using solutions from the previous cases. In this paper, we propose a new method which is the case retrieval of CBR system using Petri net and we also applied it to diagnosis for electric motors as a practical problem.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.11 no.9
• /
• pp.414-421
• /
• 2001

If a machine has some faults, we can detect them using vibration or noise signals. However some maintenance engineers who don\`t have export knowledge, need the help of vibration experts for diagnosing the machine. In this paper a case based reasoning (CBR) system is developed which is able to manipulate the past experiences of vibration diagnosis experts. In the CBR system, the maintenance engineers can retrieve the information form previous cases which are most similar to new problem s that they can solve new problem using solutions form the previous cases. In this paper, a new case retrieval method of CBR system using Petri net is proposed and also applied to diagnosis for electric motors as a practical problem.

• International Journal of Contents
• /
• v.5 no.3
• /
• pp.14-18
• /
• 2009

Traditional methods and materials used for Korean buildings need to be well organized and managed so that they can be utilized in modernization of old buildings. Supporting web-based management of information of Korean traditional building materials helps spread the related knowledge. This paper identifies the characteristics of traditional building materials data, and develops an information structure to represent the related information effectively. It also describes design decisions on web-based user interfaces to support flexible browsing and retrieval of the managed data. As the traditional building data are described by old domain-specific technical terms, utility of the developed service might be limited to those who are familiar with the terms. As an approach to tackle this problem, the proposed system supports user tagging by allowing users to classify the stored information using their own terms, and also to retrieve data using the user-supplied tags.

• Asia pacific journal of information systems
• /
• v.25 no.1
• /
• pp.25-60
• /
• 2015

Use cases are commonly used to represent customer requirements during systems development. In a large software development environment, finding relevant use cases from a library of past or related projects is a complex, error-prone and expensive task. This study proposes an ontological methodology to support use case retrieval in an interactive manner. The architecture of a prototype system that implements this methodology is presented. To evaluate whether the proposed approach can provide satisfactory results to users, this study develops a research model and hypotheses based on interaction theory. These hypotheses are empirically tested using a laboratory experiment which controls information filtering and perceived interaction. Our study suggests that a system which interacts with a user intelligently reduces cognitive load and increases self-efficacy and satisfaction.

• Journal of Information Management
• /
• v.42 no.3
• /
• pp.71-94
• /
• 2011

Query by visual example is the principal query paradigm for expressing queries in a content-based image retrieval environment. Query by image and query by sketch have long been purported as being viable methods of query formulation yet there is little empirical evidence to support their efficacy in facilitating query formulation. The ability of the searcher to express their information problem to an information retrieval system is fundamental to the retrieval process. The aim of this research was to investigate the query by image and query by sketch methods in supporting a range of information problems through a usability experiment in order to contribute to the gap in knowledge regarding the relationship between searchers' information problems and the query methods required to support efficient and effective visual query formulation. The results of the experiment suggest that query by image is a viable approach to visual query formulation. In contrast, the results strongly suggest that there is a significant mismatch between the searchers information problems and the expressive power of the query by sketch paradigm in supporting visual query formulation. The results of a usability experiment focusing on efficiency (time), effectiveness (errors) and user satisfaction show that there was a significant difference, p<0.001, between the two query methods on all three measures: time (Z=-3.597, p<0.001), errors (Z=-3.317, p<0.001), and satisfaction (Z=-10.223, p<0.001). The results also show that there was a significant difference in participants perceived usefulness of the query tools Z=-4.672, p<0.001.

• Journal of KIISE:Software and Applications
• /
• v.35 no.10
• /
• pp.608-615
• /
• 2008

In Knowledge Q&A services where information is created by unspecified users, document quality is an important factor of user satisfaction with search results. Previous work on quality prediction of Knowledge Q&A documents evaluate the quality of documents by using non-textual information, such as click counts and recommendation counts, and focus on enhancing retrieval performance by incorporating the quality measure into retrieval model. Although the non-textual information used in previous work was proven to be useful by experiments, data sparseness problem may occur when predicting the quality of newly created documents with such information. To solve data sparseness problem of non-textual features, this paper proposes new features for document quality prediction, namely text-confidence features, which indicate how trustworthy the content of a document is. The proposed features, extracted directly from the document content, are stable against data sparseness problem, compared to non-textual features that indirectly require participation of service users in order to be collected. Experiments conducted on real world Knowledge Q&A documents suggests that text-confidence features show performance comparable to the non-textual features. We believe the proposed features can be utilized as effective features for document quality prediction and improve the performance of Knowledge Q&A services in the future.