• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1195-1214
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• 2018

Typical search engines may not be the most efficient means of returning images in accordance with user requirements. With the help of semantic web technology, it is possible to search through images more precisely in any required domain, because the images are annotated according to a custom-built ontology. With appropriate annotations, a search can then, return images according to the context. This paper reports on the design of a tourism ontology relevant to touristic images. In particular, the image features and the meaning of the images are described using various properties, along with other types of information relevant to tourist attractions using the OWL language. The methodology used is described, commencing with building an image and tourism corpus, creating the ontology, and developing the search engine. The system was tested through a case study involving the western region of Thailand. The user can search specifying the specific class of image or they can use text-based searches. The results are ranked using weighted scores based on kinds of properties. The precision and recall of the prototype system was measured to show its efficiency. User satisfaction was also evaluated, was also performed and was found to be high.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.177-185
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• 2006

It is a difficult problem that learner have to need much times and efforts to search informations for problem solving. This is caused that the web based search system used by this time have the searching method of simple keyword matching. The searching method of simple keyword matching search informations by method of whether it is simply matched with keyword. Therefore, Learner have to much times and efforts to search informations, and may lose or be out of his bearing. To solve this problems, We design and implement a ontology based search system. This system is apply to PBL of social studies on middle school students. As a result, This system is more effect than the web based search system used by this time.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.101-108
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• 2010

In this paper, how fast and accurate the companies provides exponentially increasing information to the users is the most important in the corporate competitiveness. The enhancement of the retrieval relevance became the important element in enhancing company competitiveness and it is required to provide the services that are beyond simple retrieval service for good quality search service. This paper proposes the effective scheme that enhances retrieval relevance by utilizing registered tag information. By proposed scheme, we can overcome the limitations of retrieval relevance that usual search engines provide. And we compare the proposed scheme with existing web retrieval service on retrieval relevance evaluation and related search keyword.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.4
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• pp.317-334
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• 2015

This study aims to investigate information seeking behavior of mobile-based Web users, especially, college students. This study also evaluates mobile search services based on various criteria, and suggests how to improve portal's mobile search services. The results of this study show that the most urgent improvement is needed in the contents of mobile search services. Improvements are also required in the area of interface design followed by accessibility and mobile search functionalities. The results of this study can be applied to the portal's effective development of mobile search services.

• Journal of the Korean Society for information Management
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• v.19 no.1
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• pp.5-22
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• 2002

Users usually search for the required information via search engines which contain locations of the information. However. as the amount of data gets large, the result of the search is often not the information that users actually want. In this paper a web guide is proposed in order to resolve this problem. The web guide uses case-based learning method which stores and utilizes cases based on the keywords of user's action and agent's visit. The proposed agent system learns the user's visiting actions following the input of the data to be searched, and then helps rapid searches of the data wanted.

• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.1-9
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• 2010

In the new generation of Web, commonly called "Web 2.0", blogging has facilitated the publishing information or his/her opinion on the web. Various blog retrieval algorithms have been proposed to search for blogs more effectively. However, actually keyword-based searching or link-analysis blog ranking system cannot satisfy the user's requirement. In this paper, we suggest a topic-based weighting blog retrieval system in which the links between blog writings and searching words are considered to improve the search results. Our system extracts topics from each blog and weights them much higher than other guide words. In the comparison with other systems, we see that the proposed topic-base system has better recall rate of search results.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.169-179
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• 2018

Recently, web search query information has been applied in advanced predictive model research. Google dominates the global web search market in the Korean market; however, Naver possesses a dominant market share. Based on this characteristic, this study intends to compare the utility of the Korean web search query information of Google and Naver using predictive models. Therefore, this study develops three time-series predictive models to estimate the youth unemployment rate in Korea using the ARIMA model. Model 1 only used the youth unemployment rate in Korea, whereas Models 2 and 3 added the Korean web search query information of Naver and Google, respectively, to Model 1. Compared to the predictability of the models during the training period, Models 2 and 3 showed better fit compared with Model 1. Models 2 and 3 correlated different query information. During predictive periods 1 (continuous with the training period) and 2 (discontinuous with the training period), Model 3 showed the best performance. During predictive period 2, only Model 3 exhibited a significant prediction result. This comparative study contributes to a general understanding of the usefulness of Korean web query information using the Naver and Google search engines.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.100-104
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• 2010

In the past decade, various search engines have been developed to retrieve web pages that web surfers want to find from world wide web. In search engines, one of the most important functions is to evaluate and rank web pages for a given web surfer query. The prior algorithms using hyperlink information like PageRank incur the problem of 'topic drift'. To solve the problem, relevance propagation models have been proposed. However, these models suffer from serious performance degradation, and thus cannot be employed in real search engines. In this paper, we propose a new ranking algorithm that alleviates the topic drift problem and also provides efficient performance. Through a variety of experiments, we verify the superiority of the proposed algorithm over prior ones.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.669-679
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• 2008

With the increasing demands of information sharing and searches via the web, the web search engine has drawn much attention. Although many researches have been done to solve technical challenges to build the web search engine, the issue regarding its query processing system is rarely dealt with. Since the software architecture and operational schemes of the query processing system are hard to elaborate, we here present related techniques implemented on a commercial system. The implemented system is a very large-scale system that can process 5-million user queries per day by using index files built on about 65-million web pages. We implement a multi-level cache scheme to save already returned query results for performance considerations, and the multi-level cache is managed in 4-level cache storage areas. Using the multi-level cache, we can improve the system throughput by a factor of 4, thereby reducing around 70% of the server cost.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.329-334
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• 2018

Web services are standardized software technologies that enable interoperability of operating systems and programming languages through networks and related standards. Web services are distributed computing services that provide and discover services making it possible to access various services. Since the search method of web service considers only the functional aspect, it has a limitation on user-oriented search when selecting a service. In order to solve these problems, this study proposes an automatic IoT information generation tool, and provides IoT extension information when searching a web service, thereby improving the problem so that a suitable service can be selected for a user. Automatic IoT extension information generation tool proposed in this study collects and stores various information generated in the process of sensing, networking, and information processing by collaborating autonomously in a distributed environment of user, object, and service. The proposed method supports the service search suitable for the user by providing the information generated by the user as extended information when searching the web service. The proposed method can be applied to the 4th industry sector to provide a customized service that meets various environment requirements.