• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.472-476
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• 2010

Nowadays, as the indices of the major search engines grow to a tremendous proportion, vertical search services can help customers to find what they need. Real time search is valuable because it lets you know what's happening right now on any given topic. In this paper, we designed a new architecture to implement a high performance real time search system. Based on the real time search's characters, we divided the whole system to two parts which are collection system and search system. The evaluation results showed that our design has the potential to provide the real time search transparent scalability while maintaining the replication overhead costs in check.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.255-260
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• 2019

Real-time search keywords are not only limited to search keywords that are rapidly increasing interest in real-time, but also have a limitation that they are difficult to determine the sustainability as there is a difference in ranking between portal sites. Estimating sustainability for real-time search keywords is significant in terms of overcoming these limitations and providing some predictability. In particular, long-term search keywords that last for more than a month are of high value as long-lasting social issues. Therefore, in this paper, we analyze the interest based on the ranking of the real-time search keywords and the duration based on sustained weeks, days and hours of real-time search keywords by each portal site and the integrated portal site, and then estimating sustainability based on high level of interest and duration, and present a method to derive real-time search issues with high long-term sustainability.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2470-2476
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• 1997

We propose a new real-time search algorithm and provide experimental evaluation and comparison of the new algorithm with mini-min lookahead algorithm. Many other real-time heuristic-search approached often divide the problem space to several sub-problems. In this paper, the proposed algorithm guarantees not only the sub-problem deadline but also total deadline. Several heuristic real-time search algorithms such as $RTA^{\ast}$, SARTS and DYNORA have been proposed. The performance of such algorithms depend on the quality of their heuristic functions, because such algorithms estimate the search time based on the heuristic function. In real-world problem, however, we often fail to get an effective heuristic function beforehand. Therefore, we propose a new real-time algorithm that determines the sub-problem deadline based on the status of search space during sub-problem search process. That uses the cut-off method that is a dynamic stopping-criterion-strategy to search the sub-problem.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.335-342
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• 2018

The search service, which is a core service of the portal site, presents search queries that are rapidly increasing among the inputted search queries based on the highest instantaneous search frequency, so it is difficult to immediately notify a search query having a high degree of interest for a certain period. Therefore, it is necessary to overcome the above problems and to provide more intelligent information retrieval service by bringing improved analysis results on the change of the search queries. In this paper, we present the criteria for measuring the interest, continuity, and attention of real-time search queries. In addition, according to the criteria, we measure and summarize changes in real-time search queries in hours, days, weeks, and months over a period of time to assess the issues that are of high interest, long-lasting issues of interest, and issues that need attention in the future.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.21-41
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• 2010

This paper proposes a system that can serve users with appropriate search results through real time filtering, and implemented adaptive user profiling based personalized information retrieval system(PIRS) using users' implicit feedbacks in order to deal with the problem of existing search systems such as Google or MSN that does not satisfy various user' personal search needs. One of the reasons that existing search systems hard to satisfy various user' personal needs is that it is not easy to recognize users' search intentions because of the uncertainty of search intentions. The uncertainty of search intentions means that users may want to different search results using the same query. For example, when a user inputs "java" query, the user may want to be retrieved "java" results as a computer programming language, a coffee of java, or a island of Indonesia. In other words, this uncertainty is due to ambiguity of search queries. Moreover, if the number of the used words for a query is fewer, this uncertainty will be more increased. Real-time filtering for search results returns only those results that belong to user-selected domain for a given query. Although it looks similar to a general directory search, it is different in that the search is executed for all web documents rather than sites, and each document in the search results is classified into the given domain in real time. By applying information filtering using real time directory classifying technology for search results to personalization, the number of delivering results to users is effectively decreased, and the satisfaction for the results is improved. In this paper, a user preference profile has a hierarchical structure, and consists of domains, used queries, and selected documents. Because the hierarchy structure of user preference profile can apply the context when users perfomed search, the structure is able to deal with the uncertainty of user intentions, when search is carried out, the intention may differ according to the context such as time or place for the same query. Furthermore, this structure is able to more effectively track web documents search behaviors of a user for each domain, and timely recognize the changes of user intentions. An IP address of each device was used to identify each user, and the user preference profile is continuously updated based on the observed user behaviors for search results. Also, we measured user satisfaction for search results by observing the user behaviors for the selected search result. Our proposed system automatically recognizes user preferences by using implicit feedbacks from users such as staying time on the selected search result and the exit condition from the page, and dynamically updates their preferences. Whenever search is performed by a user, our system finds the user preference profile for the given IP address, and if the file is not exist then a new user preference profile is created in the server, otherwise the file is updated with the transmitted information. If the file is not exist in the server, the system provides Google' results to users, and the reflection value is increased/decreased whenever user search. We carried out some experiments to evaluate the performance of adaptive user preference profile technique and real time filtering, and the results are satisfactory. According to our experimental results, participants are satisfied with average 4.7 documents in the top 10 search list by using adaptive user preference profile technique with real time filtering, and this result shows that our method outperforms Google's by 23.2%.

• International Journal of Contents
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• v.12 no.2
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• pp.31-36
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• 2016

The purpose of this research is to realize interactive art based on user's motions information using real time internet search terms. For this purpose, real-time search terms and related news information were extracted from three domestic and foreign portal sites, and the extracted information was used to generate content for interaction with the user. For interaction between the generated content and the user, a motion-based interactive technology that optimizes the intentions and experiences of the user was developed. A motion-based interactive system can be used to develop an immersive interface that induces user interest.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.584-588
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• 2002

The real-time characteristic of the adaptive leaning control algorithms is validated based on the applied results of the hydraulic servo system that has very strong a non-linearity. The evolutionary strategy automatically adjusts the search regions with natural competition among many individuals. The error that is generated from the dynamic system is applied to the mutation equation. Competitive individuals are reduced with automatic adjustments of the search region in accordance with the error. In this paper, the individual parents and offspring can be reduced in order to apply evolutionary algorithms in real-time. The feasibility of the newly proposed algorithm was demonstrated through the real-time test.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.730-734
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• 2001

In this study in order to confirm the algorithms that are suggested from paper (I) as the experimental result, as the applied results of the hydraulic servo system are very strong a non-linearity of the fluid in the computer simulation, the real-time adaptive learning control algorithms is validated. The evolutionary strategy has characteristics that are automatically. adjusted in search regions with natural competition among many individuals. The error that is generated from the dynamic system is applied to the mutation equation. Competitive individuals are reduced with automatic adjustments of the search region in accord with the error. In this paper, the individual parents and offspring can be reduced in order to apply evolutionary algorithms in real-time as the description of the paper (I). The possibility of a new approaching algorithm that is suggested from the computer simulation of the paper (I) would be proved as the verification of a real-time test and the consideration its influence from the actual experiment.

• 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.

• KIEE International Transactions on Power Engineering
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• v.5A no.2
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• pp.177-185
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• 2005

This paper proposes an expert system that can enhance the accuracy of real-time bus reconfiguration strategy by adopting the local minimum tree search method and that can minimize the spreading effect of the fault by considering the operating condition when a main transformer fault occurs in an automated substation. The local minimum tree search method is used to expand the best-first search method. This method has the advantage that it can improve the solution performance within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. The second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules from the obtained switching candidate set. Also, this paper proposes generalized distribution substation modeling using graph theory, and a substation database based on the study results is designed.