• Journal of Information Technology Services
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• v.7 no.4
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• pp.199-208
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• 2008

Tagging represents one of the Web 2.0 technology, and has an appropriate mechanism for the classification of dynamically changing Web informations. This technique is capable of searching the Web informations using the user specified tags, but still it has a limitation of providing only the limited informations to the tags. Therefore, in order to search the related informations easily, we need to extend this technique further to search not only the desired informations through the designated tags and also the related informations. In this paper, we first have designed and developed an algorithm that can get a desired tag cluster, which is capable of collecting the searched tags along with the related tags. We first performed a test to compare the difference between the user collected tag data through RSS and the reduced data. The second test focused on the accuracy of extracted related tags that depends on the similarity functions, such as the Pearson Correlation and Euclidean. Finally, we showed the final results visually using the graph algorithm.

• The Journal of Information Technology
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• v.12 no.3
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• pp.7-17
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• 2009

This research is about the design of an opinion drawing and analysis system through statistical based Web Mining of web contents, where data of opinions are automatically drawn and analyzed concerning web documents that are scattered around in various web sites that exist within the internet. Furthermore, provides a search service that can easily classify positive/negative opinions and also provide searching and statistical information. Users, who want to search for opinions, can input a specific keyword to observe opinions of others easily. In addition, there is a merit in materializing the monitoring system.

• IE interfaces
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• v.9 no.3
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• pp.306-316
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• 1996

The easily use of WWW and Web browser of INTERNET makes the world our stage. But when we search for the information and resource that we want, the information supplied by search engine (e.g., Yahoo, Lycos, WebCrawler, Alta Vista) is inadequate to acquire the necessary and related information of research issues. This paper surveys AMT(Advanced Manufacturing Technology) which is the research topics recently on the WWW(WorLd Wide Web) and provides searching methods and information for academic research, technical report, proceedings, software, etc. It also briefly surveys WWW-VL(Virtual Library) and reviews the major three technology, CALS (Commerce At Light Speed), AMS(Agile Manufacturing System), CE(Concurrent Engineering), that is recently the focus of the research issue of Industrial Engineer.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.216-221
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• 2005

The rapid growth and spread of the World Wide Web has made it possible to easily access a variety of useful information. It is, however, very difficult to retrieve, manage, and use the desired information in web. Various kinds of systems such as Search engines, MetaSearch engines, Spiders, Softbots, Intelligent Agents or Web Agents have been developed by a large number of researchers and companies. Those systems as intelligent agent are employed to avoid the overload of information. To efficiently improve the Software Agents, it is necessary to represent and classify the retrieved data. And to improve performance of the Intelligent Agents to create the classification, it is offered how to evaluate the propriety with other information retrieved from the Web and to recommend to the user the most suitable information.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.86-93
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• 2012

In this paper, we propose keyword search and ranking methods for OWL documents that describe metadata and ontology on the Semantic Web. The proposed keyword search method defines a unit of keyword search result as an information resource and expands a scope of query keyword to names of class and property or literal data. And we reflected derived information by inference in the keyword search by considering the elements of OWL documents such as hierarchical relationship of classes or properties and equal relationship of classes. In addition, our method can search a large number of information resources that are relevant to query keywords because of information resources indirectly associated with query keywords through semantic relationship. Our ranking method can improve user's search satisfaction because of involving a variety of factors in the ranking by considering the characteristics of OWL. The proposed methods can be used to retrieve digital contents, such as broadcast programs.

• Interdisciplinary Bio Central
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• v.3 no.2
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• pp.7.1-7.6
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• 2011

Background: Published manuscripts are the main source of biological knowledge. Since the manual examination is almost impossible due to the huge volume of literature data (approximately 19 million abstracts in PubMed), intelligent text mining systems are of great utility for knowledge discovery. However, most of current text mining tools have limited applicability because of i) providing abstract-based search rather than sentence-based search, ii) improper use or lack of ontology terms, iii) the design to be used for specific subjects, or iv) slow response time that hampers web services and real time applications. Results: We introduce an advanced text mining system called PubMine that supports intelligent knowledge discovery based on diverse bio-ontologies. PubMine improves query accuracy and flexibility with advanced search capabilities of fuzzy search, wildcard search, proximity search, range search, and the Boolean combinations. Furthermore, PubMine allows users to extract multi-dimensional relationships between genes, diseases, and chemical compounds by using OLAP (On-Line Analytical Processing) techniques. The HUGO gene symbols and the MeSH ontology for diseases, chemical compounds, and anatomy have been included in the current version of PubMine, which is freely available at http://pubmine.kobic.re.kr. Conclusions: PubMine is a unique bio-text mining system that provides flexible searches and analysis of biological entity relationships. We believe that PubMine would serve as a key bioinformatics utility due to its rapid response to enable web services for community and to the flexibility to accommodate general ontology.

• Journal of Information Management
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• v.34 no.2
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• pp.55-66
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• 2003

The Web is rich with various sources of information. It contains the contents of documents, multimedia data, shopping materials and so on. Due to the massive and heterogeneous web document collections, users want to find various types of target pages. We can classify user queries as three categories according to users'intent, content search, the site search, and the service search. In this paper, we present that different strategies are needed to meet the need of a user. Also we show the properties of content information, link information and URL information according to the class of a user query. In the content search, content information showed the good result. However, we lost the performance by combining link information and URL information. In the site search, we could increase the performance by combining link information and URL information.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.67-84
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• 2008

This paper proposes a design and realization for the semantic search system. The proposed model includes three Architecture Layers of a Semantic Search System ; (they are conceptually named as) the Knowledge Acquisition, the Knowledge Representation and the Knowledge Utilization. Each of these three Layers are designed to interactively work together, so as to maximize the users' information needs. The Knowledge Acquisition Layer includes index and storage of Semantic Metadata from various source of web contents(eg : text, image, multimedia and so on). The Knowledge Representation Layer includes the ontology schema and instance, through the process of semantic search by ontology based query expansion. Finally, the Knowledge Utilization Layer includes the users to search query intuitively, and get its results without the users'knowledge of semantic web language or ontology. So far as the design and the realization of the semantic search site is concerned, the proposedsemantic search system will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.

• Journal of Global Scholars of Marketing Science
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• v.15 no.3
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• pp.93-116
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• 2005

This study explored factors affecting consumer's external information search effort on online shopping malls through three approaches(cost-benefit approach, psychological motivation approach, and web-site theory approach) respectively, and designed the integrative model through searching the relationships among them. In this study search motivation are designed to be explained by search benefit and search cost that are explained by factors related to the web site and search efforts are designed to be explained by search benefit, search cost and search motivation. The results from our empirical research showed that search motivation, search benefits and prior knowledge on online shopping malls have a direct effect on consumer external information search effort. On the other hand, it was verified that the search motivation was affected by search benefits and purchase involvement, and the search benefits are directly influenced by purchase involvement, constructive simplicity, search convenience and trust. In addition, purchase involvement, time press, constructive simplicity and search convenience had direct effects on the search cost.

• Journal of KIISE
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• v.42 no.3
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• pp.390-398
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• 2015

Spatial web objects refer to web documents that contain geographic information. Recently, services that create spatial web objects have increased greatly because of the advancements in devices such as smartphones. For services such as Twitter or Facebook, simple texts posted by users is stored along with information about the post's location. To search for such spatial web objects, a method that uses spatial information and text information simultaneously is required. Conventional spatial web object search methods mostly use R-tree and inverted file methods. However, these methods have a disadvantage of requiring a large volume of space when building indices. Furthermore, such methods are efficient for searching with many keywords but are inefficient for searching with a few keywords.. In this paper, we propose a spatial web object search method that uses a quad-tree and a patricia-trie. We show that the proposed technique is more effective than existing ones in searching with a small number of keywords. Furthermore, we show through an experiment that the space required by the proposed technique is much smaller than that required by existing ones.