• Journal of Dental Anesthesia and Pain Medicine
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• v.21 no.2
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• pp.113-118
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• 2021

Background: Consumers and patients in the last two decades have increasingly turned to various internet search engines including Google for information. Google Trends records searches done using the Google search engine. Google Trends is free and provides data on search terms and related queries. One recent study found a large public interest in "dental anesthesia". In this paper, we further explore this interest in "dental anesthesia" and assess if any patterns emerge. Methods: In this study, Google Trends and the search term "dental pain" was used to record the consumer's interest over a five-year period. Additionally, using the search term "Dental anesthesia," a top ten related query list was generated. Queries are grouped into two sections, a "top" category and a "rising" category. We then added additional search term such as: wisdom tooth anesthesia, wisdom tooth general anesthesia, dental anesthetics, local anesthetic, dental numbing, anesthesia dentist, and dental pain. From the related queries generated from each search term, repeated themes were grouped together and ranked according to the total sum of their relative search frequency (RSF) values. Results: Over the five-year time period, Google Trends data show that there was a 1.5% increase in the search term "dental pain". Results of the related queries for dental anesthesia show that there seems to be a large public interest in how long local anesthetics last (Total RSF = 231) - even more so than potential side effects or toxicities (Total RSF = 83). Conclusion: Based on these results it is recommended that clinicians clearly advice their patients on how long local anesthetics last to better manage patient expectations.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.209-217
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• 2019

In this paper, the purpose of this paper is to lay the foundation for the search system by using and building an online search engine suitable for the search domain and enabling search, conversion, integration and sharing of information. It is to use the ontology to infer hierarchical relationships, deduce objects based on that layer, and extract attributes to search areas that are relevant to the data that the user wants. In order to search for information in this way, the information search system was implemented by entering key words related to 'qualifications'. The implemented system arranged the meaning and relationship of each attribute online so that the general public can search information quickly, easily, and accurately. In addition, the implementation results were compared with two different search engines. Comparable search engines are Naver and Daum, the two major search engines. The search engine of this study, which was built using an ontology suitable for the search domain to perform searches using the semantic web, was evaluated to have excellent results. However, it is thought that a more formalized online location is necessary to increase the accuracy and reliability of search engines and to include more comprehensive categories of search terms.

• The Journal of Korean Association of Computer Education
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• v.4 no.1
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• pp.11-18
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• 2001

As the usage of computer and internet is growing, ICT-based teaching is required in education. So far almost web-based coursewares are learner-based individual teaching. Current learning theories and learning model in WBI are too focusing on courseware or too general to apply in education directly. In this view, learning model with subject-specific search engine might be a solution. In this thesis, we developed systematic concept learning model, promoting traditional concept learning to suitable model in education field and also, we developed CEhunt(Computer Education Hunter), that is computer education search engine providing the teaching materials and supporting the design of teaching and effective concept learning environment to learners. Also, we verified that this model could have a positive effect in systematic concept forming process of learners for subject concerned.

• Journal of Intelligence and Information Systems
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• v.15 no.2
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• pp.61-74
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• 2009

With an exponential growth of blogs, lots of important data have appeared on blogs. However, since main topics mentioned in blog pages are quite different from general web pages, there are problems which can't be solved by general search engines. Therefore, many researchers have studied searching methods only for blogs to help users who want to have useful information on blog. We also present a blog classifying method based on similarity of titles. First, we analyze blogs and blog search engines to find problems and solution of current blog search. Second, applying our similarity algorithm on blog titles, we discuss a way to develop clustering method only for blog. Finally, by making a prototype system of our algorithm, we evaluate our algorithm's effectiveness and show conclusion and future work. We expect this algorithm could add its power to current search engine.

• Journal of the Korean Society for information Management
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• v.15 no.2
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• pp.47-68
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• 1998

Although the research information resources on Internet are spread out on thousands of computers, it is not always easy to get them on the right time by the right manner. The purpose of this study is to use DDC(Dewey Decimal Classification) scheme in subject-based directory search engine for research information resourcees to aid retrieval on the Internet. For the design of classification code, this study followed 'systematic order' of DDC to arrange subjects from the general o the specific in a logical order, and for the design of classification dictionary, 'Relative Index' of DDC was used to bring together the various aspects of subjects.

• Korean Journal of Oriental Medicine
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• v.16 no.3
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• pp.141-147
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• 2010

In this paper, we designed and implemented an integrated search and collaboration system. Users can search the traditional korean medicine knowledge in our system, which consists of medicinal materials, formulas, diseases, terminology, and clinical information. In general, the existing information systems providing the korean medicine knowledge do not provide the update function. Thus, it can be a problem if there are incomplete information. In order to solve this problem, our system implements the functions that users can work together to improve the knowledge. Therefore, wrong information can be updated easily so that flexible management about the korean medicine information is possible.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.202-214
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• 2005

The semantic web is the web paradigm that represents not general link of documents but semantics and relation of document. In addition it enables software agents to understand semantics of documents. We propose a semantic search based on inference with ontologies, which has the following characteristics. First, our search engine enables retrieval using explicit ontologies to reason though a search keyword is different from that of documents. Second, although the concept of two ontologies does not match exactly, can be found out similar results from a rule based translator and ontological reasoning. Third, our approach enables search engine to increase accuracy and precision by using explicit ontologies to reason about meanings of documents rather than guessing meanings of documents just by keyword. Fourth, domain ontology enables users to use more detailed queries based on ontology-based automated query generator that has search area and accuracy similar to NLP. Fifth, it enables agents to do automated search not only documents with keyword but also user-preferable information and knowledge from ontologies. It can perform search more accurately than current retrieval systems which use query to databases or keyword matching. We demonstrate our system, which use ontologies and inference based on explicit ontologies, can perform better than keyword matching approach .

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2278-2291
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• 2023

Imported ornamental fish should be quarantined because they can have dangerous diseases depending on their habitat. The quarantine requires a lot of time because quarantine officers collect various information on the imported ornamental fish. Inefficient quarantine processes reduce its work efficiency and accuracy. Also, long-time quarantine causes the death of environmentally sensitive ornamental fish and huge financial losses. To improve existing quarantine systems, information on ornamental fish was collected and structured, and a server was established to develop quarantine performance support software equipped with a text search engine. However, the long names of ornamental fish in general can cause many typos and time bottlenecks when we type search words for the target fish information. Therefore, we need a technique that can correct typos. Typical typo character calibration compares input text with all characters in a calibrated candidate text dictionary. However, this approach requires computational power proportional to the number of typos, resulting in slow processing time and low calibration accuracy performance. Therefore, to improve the calibration accuracy of characters, we propose a fusion system of simple Artificial Neural Network (ANN) models and character preprocessing methods that accelerate the process by minimizing the computation of the models. We also propose a typo character generation method used for training the ANN models. Simulation results show that the proposed typo character correction system is about 6 times faster than the conventional method and has 10% higher accuracy.

• The Journal of Society for e-Business Studies
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• v.1 no.2
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• pp.161-173
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• 1996

It Is a typical scenario in concurrent engineering/design that different perspectives of each team members participating In the project exist, and those perspectives lead to conflicting decisions. The model 'resolution network' proposed in this work provides system-mediated resolution for all related team engineers to consider to optimize the manufacture in general. This paper focuses on development of the general architecture of the model and a search engine called Mediator to determine a resolution network from a given constraint network. The Mediator manages the constraint network, determines the most optimistic resolution called optimal point in terms of satisfying overall production goal , and use the optimal point to mediate controversial issues among teams. The biggest merit of our model is that it provides teams with resolution with logical and rational reasoning.

• East Asian Economic Review
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• v.23 no.1
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• pp.89-107
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• 2019

This paper ranks higher education in Korea based upon research productivity in business and economics disciplines. The number of SCI-level journal articles are tabulated using the Web of Science search engine, over the sample period from 1990 to 2016. The league table shows that many private universities dominate top-tier ranks, which is consistent with the school reputations most commonly cited by the general public in Korea. In contrast, many national universities appear in the second-tier, and their scanty performance in business and economics is in sharp contrast with our earlier findings in which national universities performed well in science and engineering fields (Jin and Kim, 2018). In addition, the ranking order in lower-ranked schools is found to be sensitive to a small change in publications, whereas the publication gap among top-tier schools is relatively large. Finally, unlike our general perception, the size of school does not matter for collaborative research. Some policy implications are discussed as a conclusion.