Seok-Hyoung Lee

An Evaluation of Applying Knowledge Base to Academic Information Service

Through a series of precise text handling processes, including automatic extraction of information from documents with knowledge from various fields, recognition of entity names, detection of core topics, analysis of the relations between the extracted information and topics, and automatic inference of new knowledge, the most efficient knowledge base of the relevant field is created, and plans to apply these to the information knowledge management and service are the core requirements necessary for intellectualization of information. In this paper, the knowledge base, which is a necessary core resource and comprehensive technology for intellectualization of science and technology information, is described and the usability of academic information services using it is evaluated. The knowledge base proposed in this article is an amalgamation of information expression and knowledge storage, composed of identifying code systems from terms to documents, by integrating terminologies, word intelligent networks, topic networks, classification systems, and authority data.

A Preliminary Study on the Multiple Mapping Structure of Classification Systems for Heterogeneous Databases

While science and technology information service portals and heterogeneous databases produced in Korea and other countries are integrated, methods of connecting the unique classification systems applied to each database have been studied. Results of technologists’ research, such as, journal articles, patent specifications, and research reports, are organically related to each other. In this case, if the most basic and meaningful classification systems are not connected, it is difficult to achieve interoperability of the information and thus not easy to implement meaningful science technology information services through information convergence. This study aims to address the aforementioned issue by analyzing mapping systems between classification systems in order to design a structure to connect a variety of classification systems used in the academic information database of the Korea Institute of Science and Technology Information, which provides science and technology information portal service. This study also aims to design a mapping system for the classification systems to be applied to actual science and technology information services and information management systems.

Method of Improving Personal Name Search in Academic Information Service

All academic information on the web or elsewhere has its creator, that is, a subject who has created the information. The subject can be an individual, a group, or an institution, and can be a nation depending on the nature of the relevant information. Most information is composed of a title, an author, and contents. An essay which is under the academic information category has metadata including a title, an author, keyword, abstract, data about publication, place of publication, ISSN, and the like. A patent has metadata including the title, an applicant, an inventor, an attorney, IPC, number of application, and claims of the invention. Most web-based academic information services enable users to search the information by processing the meta-information. An important element is to search information by using the author field which corresponds to a personal name. This study suggests a method of efficient indexing and using the adjacent operation result ranking algorithm to which phrase search-based boosting elements are applied, and thus improving the accuracy of the search results of personal names. It also describes a method for providing the results of searching co-authors and related researchers in searching personal names. This method can be effectively applied to providing accurate and additional search results in the academic information services.

The Fast Bully Algorithm: For Electing a Coordinator Process in Distributed Systems

Many of software in distributed systems require a special process called the coordinator or the leader. The coordinator is elected among the processes participating a particular distributed service when the service begins operation or the existing coordinator fails. The procedure of selecting the coordinator is called the election. One of the most popular election algorithms is the bully algorithm. However, this algorithm is costly because it generates O(n2) messages for n processes. Also the time delay till the completion of the election is considerably long. This paper proposes a new election algorithm called the fast bully algorithm. The algorithm is described and performance of the algorithm has been analyzed. The fast bully algorithm shows a clear performance improvement. It works with less messages, O(n) messages, and with shorter time delay than the bully algorithm. Also the problem of having two coordinators at the same time that appears by the bully algorithm can be avoided by the FBA.

Author Identification and Analysis for Papers, Reports and Patents

In recent years, the demand for improved transparency and sharing of data from government organizations, private companies, and data information centers has been increasing. However, the public release of metadata alone is of limited impact. In order to ensure the integrity of such reciprocal interactions, secure individual data identification is required. The present study attempts to analyze methods for reciprocal identification of metadata comprising scientific or technical content that may have diverse origins, such as domestic and foreign dissertations, domestic patents, and domestic research reports.

Category-Based an Intelligent Search System Using a Variety of Recommendation Data

As the number of Internet users and the number of accessible Web pages grows, it is becoming increasingly difficult for users to find documents that are relevant to their particular needs. In ubiquitous computing environments, personalized agents have to learn user’s preferences in order to assist them. If users search using their profile data, they are able to find relevant documents. So the proposed intelligent search system is collecting information of a user activity and automatically creates the user profile. In addition, this system provides a variety of recommendation data for users. In other words, topics cloud, similar to the user, author navigation and frequently seen keyword/documentation systems are automatically recommended. The feature of the proposed system is re-cycling system using the user’s search results and used recommend systems. In this paper, we had implemented and evaluated the category-based personalized search system.