• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.3
• /
• pp.361-367
• /
• 2021

Information search in video streaming services such as YouTube is replacing traditional information search services. To find desired detailed information in such a video, users should repeatedly navigate several points in the video, resulting in a waste of time and network traffic. In this paper, we propose a method to assist users in searching for information in a video by using DBSCAN clustering and LSTM. Our LSTM model is trained with a dataset that consists of user search sequences and their final target points categorized by DBSCAN clustering algorithm. Then, our proposed method utilizes the trained model to suggest an expected category for the user's desired target point based on a partial search sequence that can be collected at the beginning of the search. Our experiment results show that the proposed method successfully finds user destination points with 98% accuracy and 7s of the time difference by average.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.3 no.2
• /
• pp.222-226
• /
• 2003

Information retrieval must be able to search the most suitable document that user need from document set. If foretell document adaptedness by similarity degree about QL(Query Language) of document, documents that search person does not require are searched. In this paper, showed that can search the most suitable document on user's request searching document of the whole space using genetic algorithm and used knowledge-base operator to solve various model's problem.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.7
• /
• pp.3699-3719
• /
• 2017

Conjunctive keyword search encryption is an important technique for protecting sensitive personal health records that are outsourced to cloud servers. It has been extensively employed for cloud storage, which is a convenient storage option that saves bandwidth and economizes computing resources. However, the process of searching outsourced data may facilitate the leakage of sensitive personal information. Thus, an efficient data search approach with high security is critical. The multi-user search function is critical for personal health records (PHRs). To solve these problems, this paper proposes a novel multi-user conjunctive keyword search scheme (mNCKS) without a secure channel against keyword guessing attacks for personal health records, which is referred to as a secure channel-free mNCKS (SCF-mNCKS). The security of this scheme is demonstrated using the Decisional Bilinear Diffie-Hellman (DBDH) and Decision Linear (D-Linear) assumptions in the standard model. Comparisons are performed to demonstrate the security advantages of the SCF-mNCKS scheme and show that it has more functions than other schemes in the case of analogous efficiency.

• Journal of Communications and Networks
• /
• v.7 no.4
• /
• pp.471-477
• /
• 2005

This paper proposes an efficient constraint-based optimization model for the design of 3G mobile networks, such as universal mobile telecommunications system (UMTS). The model concerns about finding a set of sites for locating radio network controllers (RNCs) from a set of pre-defined candidate sites, and at the same time optimally assigning node Bs to the selected RNCs. All these choices must satisfy a set of constraints and optimize an objective function. This problem is NP-hard and consequently cannot be practically solved by exact methods for real size networks. Thus, this paper proposes a hybrid search strategy for tackling this complex and combinatorial optimization problem. The proposed hybrid search strategy is composed of three phases: A constraint satisfaction method with an embedded problem-specific goal which guides the search for a good initial solution, an optimization phase using local search algorithms, such as tabu algorithm, and a post­optimization phase to improve solutions from the second phase by using a constraint optimization procedure. Computational results show that the proposed search strategy and the model are highly efficient. Optimal solutions are always obtained for small or medium sized problems. For large sized problems, the final results are on average within $5.77\%$ to $7.48\%$ of the lower bounds.

• Journal of Intelligence and Information Systems
• /
• v.9 no.2
• /
• pp.87-100
• /
• 2003

In managing organizational tacit knowledge, recent researches have shown that it is more applicable in many ways to provide expert search mechanisms in KMS to pinpoint experts in the organizations with searched expertise. In this paper, we propose an intelligent expert search framework to provide search capabilities for experts in similar or related fields according to the user′s information needs. In enabling intelligent expert searches, Fuzzy Abstraction Hierarchy (FAH) framework has been adopted, through which finding experts with similar or related expertise is possible according to the subject field hierarchy defined in the system. To improve FAH, a text categorization approach called Vector Space Model is utilized. To test applicability and practicality of the proposed framework, the prototype system, "Knowledge Portal for Researchers in Science and Technology" sponsored by the Ministry of Science and Technology (MOST) of Korea, was developed.

• Journal of Information Technology Applications and Management
• /
• v.27 no.6
• /
• pp.53-73
• /
• 2020

Many prior studies have been conducted that positive reviews increase the intention to purchase. However, there are very few papers that have studied the impact of review search on purchase satisfaction. It is meaningful to study the impact of review search on purchase satisfaction as it can lead the business successfully by inducing repurchase. There is also no study of how review search have different effects on purchase satisfaction among countries. Given the growing number of cross-border e-commerce, we believe that the need for research is high because identifying these differences between countries can have a very important impact on a company's successful overseas expansion. Therefore, in this study, the impact of positive and negative review search on purchase satisfaction and the national impact were set up as a research model. In order to verify this research model, the survey was distributed to those who experienced online purchase in Korea and China, and a total of 234 copies were collected, including 125 copies in Korea, 109 copies in China, and the research model was verified using Smart-PLS structural equation analysis tools. First, positive review search has been shown to positively affect purchase satisfaction. Second, it has been shown that negative review search also has a positive effect on purchase satisfaction. Third, the impact of positive and negative review search on purchase satisfaction was different between Korea and China. While Korea is more aggressive in review search than China due to its high tendency to avoid uncertainty, China is less likely to avoid uncertainty than Korea and is more likely to rely on brand familiarity. Therefore, according to the uncertainty avoidance moderation effect the impact of positive and negative review search on purchase satisfaction was higher in Korea than in China. In this study, Shopping mall managers need to take strategic measures to maximize shopping mall performance by recognizing positive aspects of negative review search on purchase satisfaction. Companies and managers in Korea and China can establish strategies to promote product sales when companies enter the global market.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.683-689
• /
• 2003

Information retrieval must be able to search the most suitable document that user need from document set. If foretell document adaptedness by similarity degree about QL(Query Language) of document, documents that search person does not require are searched. In this paper, showed that can search the most suitable document on user's request searching document of the whole space using genetic algorithm and used knowledge-base operator to solve various model's problem.

• Journal of the Korean Society for information Management
• /
• v.29 no.4
• /
• pp.101-121
• /
• 2012

Since IR systems which adopt only Boolean IR model can not provide ranked search result, users have to conduct time-consuming checking process for huge result sets one by one. This study proposes a method to provide search results ranked by using coupling information between tags instead of index weight information in Boolean IR model. Because document queries are used instead of general user queries in the proposed method, key tags used as queries in a relevant document are extracted. A variety of groups of Boolean queries based on tag couplings are created in the process of extracting queries. Ranked search result can be extracted through the process of matching conducted with differential information among the query groups and tag significance information. To prove the usability of the proposed method, the experiment was conducted to find research trend analysis information on selected research information. Aslo, the service based on the proposed methods was provided to get user feedback for a year. The result showed high user satisfaction.

• Spatial Information Research
• /
• v.18 no.2
• /
• pp.57-65
• /
• 2010

Users often visit many stores while comparing the products for purchasing products or products related to it. Given a service providing location information of these stores, users can make their purchase efficiently because of reducing the time and effort they spent for wandering around and obtaining new purchase opportunities by knowing a kind of relevant stores near there. In this paper, for the purpose of providing relevant stores information efficiently, we suggest an Ambient Service Model that consists of three layers: "structured(purchase-related) information space", "real space", and "ambient information space". In the model, stores information collected from the web is grouped and structured automatically by relationships in terms of purchase. And users search relevant stores information by using an Ambient Query that is created by their context in real space. Finally, users obtain relevant stores information that is in the form of hierarchy structure on map interface. Then, users can search other kinds of relevant stores information additionally by using hierarchy structure. Consequently, It is possible to develope a service that users can obtain relevant stores information intuitively without complex search processes through the model. Also, we expect that the model can be used for developing services that provide objects information related to various objects besides stores.

• Journal of Intelligence and Information Systems
• /
• v.10 no.3
• /
• pp.27-37
• /
• 2004

XML has been proposed as a document standard for the representation and exchange of data on the WWW, and also becoming a standard for the search and reuse of scattered documents. When implementing a XML contents management system, special consideration should be imposed on how to model data and how to store the modelled data for effective and efficient management of the semi-structured data. In this paper, we proposed a new data model for the storage and search of XML document data. This proposed data model could represent both of data and structure views of XML documents, and be applied to the new data system for XML documents as well as the existing data systems.