• Journal of Internet Computing and Services
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• v.7 no.2
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• pp.71-80
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• 2006

In web search engines, there are two main methods: directory searching and keyword searching. Keyword searching shows high recall rate but tends to come up with too many search results to find which users want to see the pages. Directory searching has also a difficulty to find the pages that users want in case of selecting improper category without knowing the exact category, that is, it shows high precision rates but low recall rates. We designed and implemented a new web search engine to resolve the problems of directory search method. It regards a category as a fuzzy set which contains keywords and calculate the degree of inclusion between categories. The merit of this method is to enhance the recall rate of directory searching by expanding subcategories on the basis of similarity.

• Journal of The Korean Association of Information Education
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• v.15 no.2
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• pp.219-226
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• 2011

Web personalization has focused on extracting web pages interesting to users, to help users searching wanted information efficiently on the web. One of the main methods to achieve this is by using queries, links and users' preferred words in the pages. In this study, we surveyed from the web users the features of pages that are considered important to themselves in selecting web pages. The survey results showed that the content of the pages is the most important. However, images and readability of the page are rated as high as the content for some users. Based on this result, we present a method for maintaining relative weights of major page features differently in the profile for each user, which is used for personalizing web search results. Performance of the proposed personalization method is analyzed to prove its superiority such that it yields as much as 1.5 times higher rate than the system utilizing both queries and preferred words and about 2.3 times higher rate than a generic search engine.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.273-283
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• 2021

The aim of this paper is to review the current knowledge management (KM) practices and their importance in the public sector of Saudi Arabia. Using the term "knowledge management in public sector", a search for available works was done in Google Scholar. In the first stage, the search for literature published under anytime choice was done in the first 10 pages of the search engine. Then another nine pages of Goggle Scholar were searched for more recent works published setting the time as 2014 to 2018. The search yielded 37 usable works for this review. The results of this literature search and review indicated that out of the 37 works reviewed, only three works were related to Saudi Arabia. Number of papers on factors of KM were maximum, many of them giving diagrammatic presentation of their results. KM modelling itself is not easy as only very few papers on KM modelling were available. Problems of too much reliance on qualitative data and hypotheses not matching with the literature backgrounds for them were also found. Considering the works related to KM, the number of papers in various categories may indicate the dimensions of KM to be considered when KM is implemented or evaluated in any public sector of any country. This applies to Saudi Arabian public sector organizations also. There is a fertile ground of research waiting to be investigated by researchers in Saudi Arabia.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.6
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• pp.195-204
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• 2020

Nowadays there are over 1.6 billion web pages and it is hard to get necessary results that user wants. Most search engines allow you to search with logical form to get accurate results. However, normal users are not familiar to search information as logical form. Therefore, they search in natural language rather than in complicated logical form. In this paper there are some suggestions to improve quality of searching results, converting natural language input by the user into logical form which can able to use advanced search engine. Users tend to make short searches due to the 'Simplicity' which is one of the features of the search form. Therefore we suggest history retrieval method; advanced version of previous suggestion to provide convenience to the normal users. We had improvement on accuracy of the search results converting natural languages to logical form and also can contain every keyword without missing any keywords using searching methods on this paper. It is expected that these search methods will contribute to the development of search engines.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.137-142
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• 2012

Snippet is a summaries information of representing web pages which search engine provides user. Snippet and page rank in search engine abundantly influence user for visiting web pages. User sometime visits the wrong page with respect to user intention when uses snippet. The snippet extraction method is difficult to accurate comprehending user intention. In order to solve above problem, this paper proposes a new snippet extraction method using fuzzy association and pseudo relevance feedback. The proposed method uses pseudo relevance feedback to expand the use's query. It uses the fuzzy association between the expanded query and the web pages to extract snippet to be well reflected semantic user's intention. The experimental results demonstrate that the proposed method can achieve better snippet extraction performance than the other methods.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.3
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• pp.289-334
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• 2018

Even though information in many languages other than English is quickly increasing, English is still playing the role of the lingua franca and being accounted for the largest proportion on the web. Therefore, it is necessary to investigate the key features and differences between "information searching behavior using mother tongue as a search language" and "information searching behavior using English as a search language" of users who are non-mother tongue speakers of English to acquire more diverse and abundant information. This study conducted the experiment on the web searching which is applied in concurrent think-aloud method to examine the information searching behavior and the cognitive process in Korean search and English search through the twenty-four undergraduate students at a private university in South Korea. Based on the qualitative data, this study applied the frequency analysis to web search pattern under search language. As a result, it is active, aggressive and independent information searching behavior in Korean search, while information searching behavior in English search is passive, submissive and dependent. In Korean search, the main features are the query formulation by extract and combine the terms from various sources such as users, tasks and system, the search range adjustment in diverse level, the smooth filtering of the item selection in search engine results pages, the exploration and comparison of many items and the browsing of the overall contents of web pages. Whereas, in English search, the main features are the query formulation by the terms principally extracted from task, the search range adjustment in limitative level, the item selection by rely on the relevance between the items such as categories or links, the repetitive exploring on same item, the browsing of partial contents of web pages and the frequent use of language support tools like dictionaries or translators.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.140-143
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• 2019

The Internet has been expanded constantly and greatly such that we are having vast number of web pages with dynamic changes. Especially, the fast development of wireless communication technology and the wide spread of various smart devices enable information being created at speed and changed anywhere, anytime. In this situation, web crawling, also known as web scraping, which is an organized, automated computer system for systematically navigating web pages residing on the web and for automatically searching and indexing information, has been inevitably used broadly in many fields today. This paper aims to implement a prototype web crawler with Python and to improve the execution speed using threads on multicore CPU. The results of the implementation confirmed the operation with crawling reference web sites and the performance improvement by evaluating the execution speed on the different thread configurations on multicore CPU.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.669-679
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• 2008

With the increasing demands of information sharing and searches via the web, the web search engine has drawn much attention. Although many researches have been done to solve technical challenges to build the web search engine, the issue regarding its query processing system is rarely dealt with. Since the software architecture and operational schemes of the query processing system are hard to elaborate, we here present related techniques implemented on a commercial system. The implemented system is a very large-scale system that can process 5-million user queries per day by using index files built on about 65-million web pages. We implement a multi-level cache scheme to save already returned query results for performance considerations, and the multi-level cache is managed in 4-level cache storage areas. Using the multi-level cache, we can improve the system throughput by a factor of 4, thereby reducing around 70% of the server cost.

• Health Communication
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• v.13 no.2
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• pp.125-132
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• 2018

Purpose: The aim of this study is to investigate the quality of basic life support (BLS) information for primary Korean-speaking individuals on the internet. Methods: Using the $Google^{(C)}$ search engine, we searched for the terms 'CPR', 'cardiopulmonary resuscitation (in Korean)' and 'cardiac arrest (in Korean)'. The accuracy, reliability and accessibility of web pages was evaluated based on the 2015 American heart association(AHA) guidelines for CPR & emergency cardiovascular care, the health on the net foundation code of conduct and Korean web content accessibility guidelines 2.1, respectively. Results: Of the 178 web pages screened, 50 met criteria for inclusion. The overall quality of BLS information was not enough (median 5/7, IQR 4.75-6). 23(36%) pages were created in accordance with 2010 AHA guidelines. Only 24(48%) web pages educated on how to use the automated electrical defibrillator. The attribution and transparency of the reliability of pages was relatively low, 20(40%) and 16(32%). The web accessibility score was relatively high. Conclusion: A small of proportion of internet web pages searched by Google have high quality BLS information for a Korean-speaking population. Web pages based on past guideline were still being searched. The notation of the source of CPR information and the transparency of the author should be improved. The verification and evaluation of the quality of BLS information exposed to the Internet are continuously needed.

• Journal of KIISE:Databases
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• v.33 no.7
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• pp.708-714
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• 2006

The World Wide Web has become an entrenched global medium for storing and searching information. Most people begin at a Web search engine to find information, but the user's pertinent search results are often greatly diluted by irrelevant data or sometimes appear on target but still mislead the user in an unwanted direction. One of the intentional, sometimes vicious manipulations of Web databases is Web spamming as Google bombing that is based on the PageRank algorithm, one of the most famous Web structuring techniques. In this paper, we regard the Web as a directed labeled graph that Web pages represent nodes and the corresponding hyperlinks edges. In the present work, we define the label of an edge as having a link context and a similarity measure between link context and the target page. With this similarity, we can modify the transition matrix of the PageRank algorithm. A motivating example is investigated in terms of the Singular Value Decomposition with which our algorithm can outperform to filter the Web spamming pages effectively.