• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.128-134
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• 2016

IoT devices including smart devices are connected with internet, thus they have security threats everytime. Particularly, IoT devices are composed of low performance MCU and small-capacity memory because they are miniaturized, so they are likely to be exposed to various security threats like DoS attacks. In addition, in case of IoT devices installed for a remote place, it's not easy for users to control continuously them and to install immediately security patch for them. For most of IoT devices connected directly with internet under user's intention, devices exposed to outside by setting IoT gateway, and devices exposed to outside by the DMZ function or Port Forwarding function of router, specific protocol for IoT services was used and the devices show a response when services about related protocol are required from outside. From internet search engine for IoT devices, IP addresses are inspected on the basis of protocol mainly used for IoT devices and then IP addresses showing a response are maintained as database, so that users can utilize related information. Specially, IoT devices using HTTP and HTTPS protocol, which are used at usual web server, are easily searched at usual search engines like Google as well as search engine for the sole IoT devices. Ill-intentioned attackers get the IP addresses of vulnerable devices from search engine and try to attack the devices. The purpose of this study is to find the problems arisen when HTTP, HTTPS, CoAP, SOAP, and RestFUL protocols used for IoT devices are detected by search engine and are maintained as database, and to seek the solution for the problems. In particular, when the user ID and password of IoT devices set by manufacturing factory are still same or the already known vulnerabilities of IoT devices are not patched, the dangerousness of the IoT devices and its related solution were found in this study.

• The Journal of Korean Association of Computer Education
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• v.12 no.6
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• pp.21-32
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• 2009

This paper proposes a method to extract a user's intention automatically and implementation of intention map that support a user can appropriate search results using a user' information need accurately. It selects user intention based on searching history obtained from previous users' same queries and extracts user intentions by using clustering algorithm and user intention extraction algorithm, extracted user intentions are represented in an intention map base on a theory of knowledge representation. For the efficiency analysis of intention map, we extracted user intentions using 2,600 search history data which provided by a current domestic commercial search engine. The experimental results using the information intention map search when using general search engines represent more than satisfaction was statistically significant.

• Journal of Korean Library and Information Science Society
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• v.32 no.3
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• pp.397-417
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• 2001

The purpose of this study is to suggest the guidelines for developing the effective classification scheme of woman studies on the Internet. In order to do that, fuve search engines and three subject web databases are analyzed based on the characteristics, problems of their classification schemes. In addition their classification schemes are measured in terms of coverage of subject fields and systematic logic. The results suggest the guidelines far classification scheme reflecting the characteristics of women's studies that ice interdisciplinary and multidisciplinary fields.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.2
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• pp.26-31
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• 2005

In this paper, we present the document summarizers which are simpler and more condense than the existing ones generally used in the web search engines. This method is a statistic-based summarization method using the concept of the complete graph. We suppose that each sentence as a vertex and the similarity between two sentences as a link of the graph. We compare this summarizer with those of Clustering and MMR techniques which are well-known as the good summarization methods. For the comparison, we use FScore using the summarization results generated by human subjects. Our experimental results verify the accuracy of this method, being about $30\%$ better than the others.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.98-104
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• 2003

While the impact or internet on our everyday life keeps increasing, the internet users are turning toward the value added information only that suits their purpose instead of just wandering over a sea (pool) or information. Although it is easy to locate the information using various search engines. we still finds it time and cost consuming to update the existing information or to add similar Information. There are several portal sites managed by each industrial types or associations/organizations for the purpose or strengthening the competitiveness or small and medium-sized enterprises And currently, tremendous manpower and expenses are put into the selection and quality improvement or information to satisfy the needs toward the high qualify information by the specialized users in their fields collection and updating or the information is partially available manually during He period or budget allocation by the government it becomes problematic, however, to continue this service when the project expires. This report presents the system for the information collection, analysis and classification of portal sites operated for the special purposes and automatic upload to the proper sites. In addition. expression or web robots and application of robots and several information types are suggested which will eventually accomplish currency or information and automatic updates and addition or documents with the least expenses or maintenance.

• The Journal of Pediatrics of Korean Medicine
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• v.25 no.2
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• pp.102-110
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• 2011

Objectives: The purpose of this study is to analyze the baby bath preparation and provide necessary information on the upcoming herbal bath preparation for atopic dermatitis. Methods: We selected 113 baby bath preparation by searching typing in "baby bath preparation" in 6 major web-search-engines, and 17 web shopping malls in Korea. 11 items were evaluated under three criteria : type of product, function and ingredient of goods. Results: Result showed that the most common type of bath preparation were liquid type. 96% of the products contained medical agents. Ingredients of the medical agents were herbal medicine, aroma oil, spring and sea ingredients, vitamin and extract. 33% of the products were bath preparation for the atopic dermatitis and 74% of the products were only for the baby. Conclusions: It is necessary to make a government level guideline for natural materials used in bath preparation, and to develop new products contained herbal medicine abide by oriental medical theory.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.3
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• pp.281-288
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• 2010

In the web search engines, the proximity is used to compute the relevance of a document to the given query. There exist various research results about the proximity problems and the ordered proximity problems. In this paper, we present O(n) time algorithms for the k-keyword ordered proximity problems where n is the total number of occurrences of the k keywords in a document. Experimental results show that the proposed algorithms are about 1.2 times and over 3 times faster than the previous results when k=2 and k=5, respectively.

• Journal of the Korean Society for Library and Information Science
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• v.36 no.3
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• pp.181-200
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• 2002

This paper starts by exploring the definition and scope of digital culture contents under digital environments. It then analyzes the classification system of search engines about digital culture contents in terms of subject catagories and the number of web documents. Finally, this study suggests the recommendations for effective retreival and management of digital culture contents.

• Fisheries and Aquatic Sciences
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• v.26 no.1
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• pp.1-23
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• 2023

Marine bioactive substances (MBS), such as phlorotannins, collagens, peptides, sterols, and polysaccharides, are increasing attention as therapeutic agents for several diseases due to their pharmacological effects. Previous studies have demonstrated the biological activities of MBS including antibacterial, anticoagulant, antidiabetic, antimicrobial, anti-inflammatory activities. Among numerous human diseases, periodontitis is one of the high-prevalence inflammatory diseases in the world. To treat periodontitis, several surgeries (bone grafting, flap surgery, and soft tissue graft) are usually used. However, the surgery for patients with chronic periodontitis induces several side effects, including additional inflammatory responses at the operated site, chronic wound healing, and secondary surgery. Therefore, this review assessed the most recent trends in MBS using Google Scholar, PubMed, and Web of Science search engines to develop marine-derived therapeutic agents for periodontitis. Further, we summarized the current applications and therapeutic potential of MBS to serve as a reference for developing novel technologies applied to MBS against periodontitis treatment.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.