• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.737-744
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• 2004

Retrieving relevant information well corresponding to the user`s request from web is a crucial task of search engines. However, most of conventional search engines based on pattern matching schemes to queries have a limitation that is not easy to provide results corresponding to the user`s request due to the uncertainty of queries. To overcome the limitation in this paper, we propose a framework for knowledge-based semantic meta-search engines with the following five processes: (i) Query formation, (ii) Query expansion, (iii) Searching, (iv) Ranking recreation, and (v) Knowledge base. From simulation results on english-based web documents, we can see that the Proposed knowledge-based semantic meta-search engine provides more correct and better searching results than those obtained by using the Google.

• Proceedings of the ESK Conference
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• 1995.10a
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• pp.185-191
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• 1995

This paper reviews how to access the ergonomic information through internet-the world-wide computer networks. Recently, with the growth of hypertext type Internet-the WWW (World-Wide Web), it becomes much easier to access to the Internet and we can retrieve information very effeciently. In order to search the ergonomic information, this paper also reviews the famous Web search engines like Lycos, Web Crawler, and meta-indices like YAHOO. Also, useful Web-sites of ergonomics/human factors such as ErgoWeb are summarised.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1101-1112
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• 2004

In this paper, we propose a Web page weighting scheme using the user preference in each sense of query word to improve the performance of Web search. Generally search engines assign weights to a web page by using relevancy only, which is obtained by comparing the query word and the words in a web page. In the information retrieval from huge data such as the Web, simple word comparison cannot distinguish important documents because there exist too many documents with similar relevancy In this paper we implement a WordNet-based user interface that helps to distinguish different senses of query word, and constructed a search engine in which the implicit evaluations by multiple users are reflected in ranking by accumulating the number of clicks. In accumulating click counts, they are stored separately according to senses, so that more accurate search is possible. The experimental results with several keywords show that the precision of proposed system is improved compared to conventional search engines.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.100-104
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• 2010

In the past decade, various search engines have been developed to retrieve web pages that web surfers want to find from world wide web. In search engines, one of the most important functions is to evaluate and rank web pages for a given web surfer query. The prior algorithms using hyperlink information like PageRank incur the problem of 'topic drift'. To solve the problem, relevance propagation models have been proposed. However, these models suffer from serious performance degradation, and thus cannot be employed in real search engines. In this paper, we propose a new ranking algorithm that alleviates the topic drift problem and also provides efficient performance. Through a variety of experiments, we verify the superiority of the proposed algorithm over prior ones.

• Journal of Information Technology Applications and Management
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• v.10 no.2
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• pp.33-41
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• 2003

It is not easy to find desired information in the world wide web. In this research, we introduce a notion of concept network that is useful in finding information if it is used in search engines that are specialized in domains such as medicine, law or engineering. The concept network that we propose is a network in which nodes represent significant concepts in the domain, and links represent relationships between the concepts. We may use the concept network constructor as a preprocessor to speci-alized search engines. When user enters a target word to find information, our system generates and displays a concept network in which nodes are con-cepts that are closely related with the target word. By reviewing the network, user may confirm that the target word is properly selected for his intention, otherwise he may replace the target word with better ones discovered in the network. In this research, we propose a detailed method to construct concept net-work, implemented a prototypical system that constructs concept networks, and illustrate its usefulness by demonstrating a practical case.

• Journal of the Korean Society for information Management
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• v.20 no.1
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• pp.417-455
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• 2003

Ontologies are formal theories that are suitable for implementing the semantic web. which is a new technology that attempts to achieve effective retrieval, integration, and reuse of web resources. Ontologies provide a way of sharing and reusing knowledge among people and heterogeneous applications systems. The role of ontologies is that of making explicit specified conceptualizations. In this context, domain and generic ontologies can be shared, reused, and integrated in the analysis and design stage of information and knowledge systems. This study aims to design an ontology for international organizations. and build an Internet web retrieval system based on the proposed ontology. and finally conduct an experiment to compare the system performance of the proposed system with that of internet search engines focusing relevance and searching time. This study found that average relevance of ontology-based searching and Internet search engines are 4.53 and 2.51, and average searching time of ontology-based searching and Internet search engines are 1.96 minutes and 4.74 minutes.

• Clinics in Shoulder and Elbow
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• v.26 no.3
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• pp.238-244
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• 2023

Background: Many patients use online resources to educate themselves on surgical procedures and make well-informed healthcare decisions. The aim of our study was to evaluate the quality and readability of online resources exploring shoulder arthroplasty. Methods: An internet search pertaining to shoulder arthroplasty (partial, anatomic, and reverse) was conducted using the three most popular online search engines. The top 25 results generated from each term in each search engine were included. Webpages were excluded if they were duplicates, advertised by search engines, subpages of other pages, required payments or subscription, or were irrelevant to our scope. Webpages were classified into different source categories. Quality of information was assessed by HONcode certification, Journal of the American Medical Association (JAMA) criteria, and DISCERN benchmark criteria. Webpage readability was assessed using the Flesch reading ease score (FRES). Results: Our final dataset included 125 web pages. Academic sources were the most common with 45 web pages (36.0%) followed by physician/private practice with 39 web pages (31.2%). The mean JAMA and DISCERN scores for all web pages were 1.96±1.31 and 51.4±10.7, respectively. The total mean FRES score was 44.0±11.0. Only nine web pages (7.2%) were HONcode certified. Websites specified for healthcare professionals had the highest JAMA and DISCERN scores with means of 2.92±0.90 and 57.96±8.91, respectively (P<0.001). HONcode-certified webpages had higher quality and readability scores than other web pages. Conclusions: Web-based patient resources for shoulder arthroplasty information did not show high-quality scores and easy readability. When presenting medical information, sources should maintain a balance between readability and quality and should seek HONcode certification as it helps establish the reliability and accessibility of the presented information. Level of evidence: IV.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.674-677
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• 2020

The cultural background of users utilizing image search engines has a significant impact on the satisfaction of the search results. Therefore, it is important to analyze and understand the cultural context of images for more accurate image search. In this paper, we investigate how the cultural context of images can affect the performance of image classification. To this end, we first collected various types of images (e.g,. food, temple, etc.) with various cultural contexts (e.g., Korea, Japan, etc.) from web search engines. Afterwards, a deep transfer learning approach using VGG19 and MobileNetV2 pre-trained with ImageNet was adopted to learn the cultural features of the collected images. Through various experiments we show the performance of image classification can be differently affected according to the cultural context of images.

• The KIPS Transactions:PartD
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• v.9D no.3
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• pp.345-354
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• 2002

HTML pages in the web change at any time. It could cause to decrease the functionality of meta-search engines which provide users with integrated results of search engines. To solve this problem, we propose an HTML pages modification detector. It utilities information of element positions in HTML pages and the modified Jaak Vilo algorithm. The HTML page modification detector uses patterns that represent the structure of HTML expressions occurring repeatedly in HTML pages. An experiment is carried out to verify the correctness of the modification detector.

• The KIPS Transactions:PartD
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• v.15D no.3
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• pp.305-312
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• 2008

Web documents with useful information are widely available on the internet and they are accessible with web search service. For this reason, web search services study better ways to collect more web documents, but have a difficulty figuring out the coverage of these web pages. This paper is intended to find ways to evaluate the current coverage assessment methods and suggest more effective coverage assessment technique that is, sampling internet web documents equally, monitoring how they are classified on web search services, in an attempt to assess both absolute and relative coverage of the web search engines. The paper also presents the comparison among Korean web search services using the suggested methods.the absolute and relative coverage was highest in Google followed by Naver and Empas. The result is expected to help estimating coverage of web search services.