• Journal of KIISE
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• v.44 no.8
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• pp.782-790
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• 2017

The service, 'Hot Search Keywords', provides a list of the most hot search terms of different web services such as Naver or Daum. The service, bases the changes in rank of a specific search keyword on changes in its users' interest. This paper introduces a temporal modelling framework for predicting the rank change of hot search keywords using past rank data and machine learning. Past rank data shows that more than 70% of hot search keywords tend to disappear and reappear later. The authors processed missing rank value, using deletion, dummy variables, mean substitution, and expectation maximization. It is however crucial to calculate the optimal window size of the past rank data. We proposed an optimal window size selection approach based on the minimum amount of time a topic within the same or a differing context disappeared. The experiments were conducted with four different machine-learning techniques using the Naver, Daum, and Nate 'Hot Search Keywords' datasets, which were collected for 2 years.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8A
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• pp.598-606
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• 2003

In this paper, we analyze the performance of the PCM cell search algorithm proposed for fast cell search of WCDMA systems. In order to improve both performance and complexity of the cell search algorithm standardized for WCDMA systems the PCM scheme uses a group of the polarization codes produced by a Gold code generator. The PCM scheme only uses one synchronization channel since the polarization codes modulated on P-SCH can replace the RS codes of S-SCH. Thus, the PCM reduces the BS's transmission power since only one synchronization channel can be used, and it can also reduce the complexity of receiver as compared with the conventional one. In this paper, by defining a numerical model, we analyze the performance of the PCM cell search algorithm in terms of detection probability and mean acquisition time. Consequently, we could demonstrate that the PCM cell search algorithm is superior to the standard WCDMA cell search algorithm.

• Journal of Information Technology and Architecture
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• v.9 no.3
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• pp.323-331
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• 2012

With the advancement of the area of knowledge and information, Intellectual Property, especially, patents have captured attention more and more emergent. The increasing need for efficient way of patent information search has been essential, but the prevailing patent search engines have included too many noises for the results due to the Boolean models. This has occasioned too much time for the professional experts to investigate the results manually. In this paper, we reveal the differences between the conventional document search and patent search and analyze the limitations of existing patent search. Furthermore, we propose a specialized in patent search, so that the relationship between the keywords within each document and their significance within each patent document search keyword can be identified. Which in turn, the keywords and the relationships have been appointed a ranking for this patent in the upper ranks and the noise in the data sub-ranked. Therefore this approach is proposed to significantly reduce noise ratio of the data from the search results. Finally, in, we demonstrate the superiority of the proposed methodology by comparing the Kipris dataset.

• 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.

• The Korean Journal of Franchise Management
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• v.13 no.3
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• pp.45-55
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• 2022

Purpose: Consumers' experience of functional attributes is remembered, and the experience lowers the cost of consumers' input from their point of view and reduces uncertainty. It also plays an important role in consumers' positive emotions and responses. Accordingly, if information search costs are reduced in terms of the costs perceived by consumers about restaurants, a strategy differentiated from other companies can be established. Therefore, this study investigated the effect of functional congruence of restaurant stores on information search cost reduction, positive/negative emotions, and loyalty. Research Design, Data, and Methodology: This study investigated functional congruence, information search cost reduction, and positive/negative emotions. The structural relationship between loyalty was analyzed. To verify this, a research hypothesis was established based on previous studies and a research model was constructed. The questionnaire items were modified and used according to the current study, based on previous studies. The data were collected using the questionnaire method from 187 people who had dining out experience. Frequency analysis was performed to confirm demographic characteristics. Reliability, convergent validity, and discriminant validity of the collected data were verified. The research model was analyzed with a structural equation modeling (SmartPLS 4). Results: The findings show that functional congruence had significant positive effects on information search cost reduction and positive emotion, but no significant effect on negative emotion. Information search cost reduction had significant positive effects on positive emotion/negative emotion but did not significantly affect loyalty. Lastly, both positive and negative emotions had significant positive effects on loyalty. Conclusion: Based on transaction cost theory, this study found how functional congruence and information search cost reduction influence consumers' emotions. The functional attributes of restaurants were perceived by customers as information, thus uncertainty was decreased. Finally, appropriate management strategies and implications of functional congruence and information search cost in the restaurant were suggested.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.57-66
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• 2022

In this paper, we propose a legal document search method that uses the Sentence-BERT model. The general public who wants to use the legal search service has difficulty searching for relevant precedents due to a lack of understanding of legal terms and structures. In addition, the existing keyword and text mining-based legal search methods have their limits in yielding quality search results for two reasons: they lack information on the context of the judgment, and they fail to discern homonyms and polysemies. As a result, the accuracy of the legal document search results is often unsatisfactory or skeptical. To this end, This paper aims to improve the efficacy of the general public's legal search in the Supreme Court precedent and Legal Aid Counseling case database. The Sentence-BERT model embeds contextual information on precedents and counseling data, which better preserves the integrity of relevant meaning in phrases or sentences. Our initial research has shown that the Sentence-BERT search method yields higher accuracy than the Doc2Vec or TF-IDF search methods.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.155-164
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• 2006

This paper focuses on a new optimization technique of a fuzzy logic based proportional integral (FLPI) load frequency controller by the multiple tabu search (MTS) algorithm. Conventionally, the membership functions and control rules of fuzzy logic control are obtained by trial and error method or experiences of designers. To overcome this problem, the MTS algorithm is proposed to simultaneously tune proportional integral gains, the membership functions and control rules of a FLPI load frequency controller in order to minimize the frequency deviations of the interconnected power system against load disturbances. The MTS algorithm introduces additional techniques for improvement of the search process such as initialization, adaptive search, multiple searches, crossover and restart process. Simulation results explicitly show that the performance of the proposed FLPI controller is superior to conventional PI and FLPI controllers in terms of overshoot and settling time. Furthermore, the robustness of the proposed FLPI controller under variation of system parameters and load change are higher than that of conventional PI and FLPI controllers.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.911-917
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• 2017

There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, which is a balance optimization strategy used in the design of PNNC when running space search optimization. Unlike the conventional probabilistic neural network classifier, the proposed neural network classifier adopts two type of polynomials for developing discriminant functions. The overall optimization of PNNC is realized with the aid of so-called structure optimization and parameter optimization with the use of simultaneous tuning strategy. Space search optimization algorithm is considered as a optimize vehicle to help the implement both structure and parameter optimization in the construction of PNNC. Furthermore, principal component analysis and linear discriminate analysis are selected as the data preprocessing techniques for PNNC. Experimental results show that the proposed neural network classifier obtains better performance in comparison with some other well-known classifiers in terms of accuracy classification rate.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.61-73
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• 2004

The efficiency of the real-time route guidance system(RGS) depends largely on the quality of route search algorithms. In this paper, we implement the coarse grid method(CGM) in mathematical programming for finding a good quality route of real-time RGS in large-scale networks. The proposed CGM examines coarser and wider networks as the search phase proceeds, in stead of searching the whole network at once. Naturally, we can significantly reduce computational efforts in terms of search time and memory requirement. We demonstrate the practical effectiveness of the proposed CGM with nationwide real road network simulation.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.2
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• pp.241-262
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• 2010

This study aims to perform an evaluation of classification systems provided by major Korean search portals, Naver, Nate, Daum, and Yahoo-Korea. These classification systems are evaluated in terms of the consistency of classification system, logicality of classification system, ease of interface, clarity of category names, order of category and site listing, and hierarchical structure. The results of this study show that each search portal provides separate classification systems for their services. These results imply that it is crucial for search portals to implement a common classification system and a common interface for their services. This study could contribute to the development and improvement of portals' classification systems.