• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.145-151
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• 2015

Since we use internet every day, the internet privacy has become important. We need to find out what kinds of personal information is exposed to the internet and to eliminate the exposed information. However, it is not efficient to search the personal information using only fragmentary clues in web search engines because the ranking results are not relevant to the exposure degree of personal information. In this paper, we introduced a personal information retrieval system and proposed a process to remove private data from the web easily. We also compared our proposed method with previous methods by evaluating the search performance.

• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.33-40
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• 1997

An optimization system, APROGA II using genetic algorithm, was developed to solve multi-modal and multiobjective problems. To begin with, Multi-Niche Crowding(MNC) algorithm was used for multi-modal optimization problem. Secondly, a new algorithm was suggested for multiobjective optimization problem. Pareto dominance tournaments and Sharing on the non-dominated frontier was applied to it to obtain multiple objectives. APROGA II uses these two algorithms and the system has three search engines(previous APROGA search engine, multi-modal search engine and multiobjective search engine). Besides, this system can handle binary and discrete variables. And the validity of APROGA II was proved by solving several test functions and case study problems successfully.

• Journal of Korea Multimedia Society
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• v.19 no.11
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• pp.1878-1890
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• 2016

Web 2.0 has features produced the content through the user of the participation and share. The content production activities have became active since social network service appear. The social bookmark, one of social network service, is service that lets users to store useful content and share bookmarked contents between personal users. Unlike Internet search engines such as Google and Naver, the content stored on social bookmark is searched based on tag keyword information and unnecessary information can be excluded. Social bookmark can make users access to selected content. However, quick access to content that users want is difficult job because of the user of the participation and share. Our paper suggests a method recommending search word to be able to access quickly to content. A method is suggested by using Collaborative Filtering and Jaccard similarity coefficient. The performance of suggested system is verified with experiments that compare by 'Delicious' and "Feeltering' with our system.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.95-114
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• 2010

Multimedia searching is an important activity on the Web, especially among the younger generation. The purpose of this study aims to examine college students’ multimedia information needs and searching on the Internet. While there is a clear pattern among students with respect to their multimedia uses, searching sources, relevance criteria and searching barriers, some differences exist especially according to searching of different multimedia types such as image, audio and video. For multimedia uses, information/data-focused uses are frequently found in image and video, while the use of audio is mainly for object-focused searches. As multimedia searching sources, audio and video files present a similar pattern of being high in media specific searching sources and low in generic search engines. Browsing through related blogs and homepages is an important part of searching for media files accounting for approximately 20% of total search for each media. The relevance criteria used by study participants when search for image files was primarily concerned with topicality while the contextual and media quality in the audio and video types are also considered important. Searching barriers for audio and video files are categorized into three broad aspects, including access and search quality, preview limitations and collection limitations, while obstacles for image files searching include access difficulties and low qualities of various collection.

• Journal of Information Management
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• v.37 no.2
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• pp.33-50
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• 2006

In this paper, after reviewing hyperlink based ranking methods, we saw various other parameters that effect ranking. Then, We analyzed the PageRank and HITS(Hypertext Induced Topic Search) algorithm, which are two popular methods that use eigenvector computations to rank results in terms of their characteristics. Finally, google and Ask.com search engines were examined as examples for applying those methods. The results showed that use of Hyperlink structure can be useful for efficiency of web site search.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.111-115
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• 1998

The Internet today is teemed with not only text data but also other media such as sound, still and moving images in a variety of formats. Unlike text, however, that can be retrieved easily with the help of numerous search engines, there has been few way to access data of other media unless the exact location or the URL is known. Multimedia data in the WWW are contained in or linked via anchors in the hyper-documents. They can most reliably be retrieved by analyzing the binary data content, which is far from being practical yet by the current state of the art. Instead we present another technique of searching based on textual descriptions which are found at or around the multimedia objects. The textual description used in this research includes file name (URL), anchor text and its context, alternative descriptions found in ALT HTML tage. These are actually the clues assumedly relevant to the contents. Although not without a possibility of missing or misinterpreting images and sounds, the description-based search is highly practical in terms of computation. The prototype search engine will soon be deployed to the public service through the prestige search engine, InfoDetective, in Korea.

• The Journal of Society for e-Business Studies
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• v.17 no.2
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• pp.73-85
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• 2012

Recently, as Social Network Services(SNS), such as Twitter, Facebook, are becoming more popular, much research has been doing actively. However, since SNS has been launched recently, related researches are also infant level. Especially, search engines serviced in web potals simply show the postings in order of upload time. Searching the postings in Twitter should be different from web search, which is based on traditional TF-IDF. In this paper, we present the new method of searching and ranking the interesting postings in Twitter. In proposed method, we utilize the frequency of retweets as a major factor for estimating the quality of postings. It can be an important criteria since users tend to retweet the valuable postings. Experimental results show that proposed method can be applied successfully in Twitter search system.

• Journal of the Korean Society for information Management
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• v.32 no.4
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• pp.289-305
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• 2015

This study aims to investigate information seeking behavior of Popshoes users. Transaction logs of Popshoes, a major Korean shopping search engine, were analyzed. These transaction logs were collected over 3 months period, from January 1 to March 31, 2015. The results of this study show that Popshoes users behave in a simple and passive way. In the total sessions, more users chose to browse a directory than typing and submitting a query. However, queries played a more crucial role in important decision makings such as search results clicks and product purchases than directory browsing. The results of this study can be implemented to the effective development of shopping search engines.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.62-65
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• 2010

Image annotations allow users to access a large image database with textual queries. But since the surrounding text of Web images is generally noisy. an efficient image annotation and retrieval system is highly desired. which requires effective image search techniques. Data mining techniques can be adopted to de-noise and figure out salient terms or phrases from the search results. Clustering algorithms make it possible to represent visual features of images with finite symbols. Annotationbased image search engines can obtains thousands of images for a given query; but their results also consist of visually noise. In this paper. we present a new algorithm Double-Circles that allows a user to remove noise results and characterize more precise representative annotations. We demonstrate our approach on images collected from Flickr image search. Experiments conducted on real Web images show the effectiveness and efficiency of the proposed model.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.57-65
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• 2019

In this paper, we propose a Rights Management Information(RMI) expression systems for individual sites are integrated and the performance evaluation is performed to find out an efficient comparing and updating method of RMI through various image feature point search techniques. In addition, we proposed a weighted scoring model for both public domain sites and posts in order to use the most latest RMI based on reliable data. To solve problem that most public domain sites are exposed to copyright infringement by providing inconsistent RMI(Rights Management Information) expression system and non-up-to-date RMI information. The weighted scoring model proposed in this paper makes it possible to use the latest RMI for duplicated images that have been verified through the performance evaluation experiments of SIFT and CNN techniques and to improve the accuracy when applied to search engines. In addition, there is an advantage in providing users with accurate original public domain images and their RMI from the search engine even when some modified public domain images are searched by users.