• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.2
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• pp.397-404
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• 2016

Illegal and harmful contents on the Internet has been an issue and been increased in Korea. They are often posted on the billboard and website of small enterprise and government office. Those illegal and harmful contents can relate to crime and suspicious activity, so, we need a detection system. However, to date the detection itself has been conducted manually by a person. In this paper, we develop an automated URL detection scheme for detecting a drug trafficking by using Google. This system works by analyzing the frequently used keywords in a drug trafficking and generate a keyword dictionary to store words for future search. The suspected drug trafficking URL are automatically collected based on the keyword dictionary by using Google search engine. The suspicious URL can be detected by classifying and numbering each domain from the collection of the suspected URL. This proposed automated URL detection can be an effective solution for detecting a drug trafficking, also reducing time and effort consumed by human-based URL detection.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.397-404
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• 2018

As the usage of internet is increasing, a lot of user behavior are written in a log file and the researches and industries using the log files are getting activated recently. This paper uses the Hadoop based on open source distributed computing platform and proposes a customized tourism system by analyzing user behaviors in the log files. The proposed system uses Google Analytics to get user's log files from the website that users visit, and stores search terms extracted by MapReduce to HDFS. Also it gathers features about the sight-seeing places or cities which travelers want to tour from travel guide websites by Octopus application. It suggests the customized cities by matching the search terms and city features. NBP(next bit permutation) algorithm to rearrange the search terms and city features is used to increase the probability of matching. Some customized cities are suggested by analyzing log files for 39 users to show the performance of the proposed system.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.11-18
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• 2009

Ajax based on Java Script receives attention as an alternative to ActiveX technology. Most portal sites in korea show a tendency to reopen existing services by combining the technology, because it supports most web browsers, and has the advantages of such a brilliant interface, excellent speed, and traffic reduction through asynchronous interaction. This paper modeled and implemented a multilingual meta-search service using the Ajax and open APIs provided by international famous sites. First, a Korean query is translated into one of the language of 54 countries around the world by Google translation API, and then the translated result is used to search the information of the social web sites such as Flickr, Youtube, Daum, and Naver. Searched results are displayed fast by dynamic loading of portion of the screen using Ajax. Our system can reduce server traffic and per-packet communications charges by preventing redundant transmission of unnecessary information.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.109-119
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• 2017

This paper is to analyse empirically using the data collected from Korea portal Naver's ad management system and show online ad platform may not be two-sided market. It is aim of this study to propose the appropriate approach to define the market, based on the empirical result. Here are two research questions to be reviewed. First, is there any consistency between business model of search advertising and definition of two-sided market which Rochet-Tirole proposed in 2006? Second, do indirect network externalities exist significantly in search advertising market? if so, this study is going to estimate the level of it through empirical measurement. Based on Luchetta's paper which suggested that google may be one-sided market, it performed the correlation & regression analysis to prove his suggestion. The result is that online search advertising costs increased by more than 50 won when advertisers increased by one unit. However, there was no significant correlation and regression between the search frequency and online search advertising cost. It means that there is little possibility to identify two-sidedness in online search advertising service(market) because of no(or little) indirect network externalities which are a necessary condition for two-sided market. This result has three implications, such as the availability to adapt traditional market definition tools to online search advertising market, the possibility enhancement to find the fundamental competition elements in defined market and promotion of the powers of persuasion in competitive market reality. It is significant that the gap between legal scholars including regulatory practitioners and economists can be overcome to some extent. who have shown the different perspective on the two-sided market.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.43-53
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• 2009

Knowledge retrieval service that uses collective intelligence which has special quality of open structure and can share the accumulative data is gaining popularity. However, acquiring the right needs for users from massive public knowledge is getting harder. Recently, search results from Google which is known for it's exquisite algorism, shows results for collective intelligence such as Wikipedia, Yahoo Q/A at the highest rank. Objective of this paper is to show that most answers come from human and to find the most influential people in on-line knowledge retrieval service. Hereupon, this paper suggest the influence value calculation algorism by analyzing user relation as centrality which social network is based on user activeness and reliance in Naver 지식iN. The influence value calculated by the suggested algorism will be an important index in distinguishing reliable and the right user for the question by ranking users with troubleshooting solutions in the knowledge retrieval service. This will contribute in search satisfaction by acquiring the right information and knowledge for the users which is the most important objective for knowledge retrieval service.

• Journal of Information Management
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• v.38 no.3
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• pp.183-209
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• 2007

The representative example of the business model on internet environment, the business of the Naver, Empas and Google which provides information retrieval service is the internet portal. The portal sites provide information retrieval service which provides users information what they want to find, that is a huge social contribution. The portal site which provides a search service leads much problems. Consequently, the regulation against information retrieval is asserted powerfully in spite of the public interest. Namely, the regulation regarding the search business owner is tried. Finally, portal business owner puts the social responsibility as OSP. But, there is a doubt that portal business owner who has much problem which occurred on the portal site indirectly has responsibility directly. That is duty on portal site owner the censorship on the contents transferred. So, this thesis researches on the social critical opinion relating with a information retrieval from the legal side against the problem of the Internet.

• Cartoon and Animation Studies
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• s.36
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• pp.553-572
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• 2014

In this paper, for the evaluation of the ease of a particular Web site (www.appbelt.net), insert the log tracking code for Google Analytics in a page of the Web site to collect behavioral data of visitor and has studied the improvement measures for the problems of the Web site, after the evaluation of the overall quality of the Web site through the evaluation of Coolcheck. These findings set the target value of the company's priority (importance) companies want to influence the direction of the business judgment are set up correctly, and the user's needs and behavior will be appropriate for the service seems to help improvement.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.1-28
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• 2022

In recent years, many Internet giants have begun providing their own content services, which attract online users by offering personalized services based on artificial intelligence technologies. This study investigates the role of two firms' content services within the firms' online service network. We examine the role of Naver Webtoon, which can be characterized as a professional-generated content, within Naver's service portfolio, and that of Google YouTube, which can be characterized as a user-generated content, within Google's service portfolio. Using survey data on viewers' use of the two services, we analyze a valued directed service network, where a node denotes an online service and a relationship between two nodes denotes a sequential use of two services. We found that both Webtoon and YouTube show higher out-degree centrality than in-degree centrality, which implies these content services are more likely to be starting services rather than arriving services within the firms' interactive network. The gap between the out-degree and in-degree centrality of YouTube is much smaller than that of Webtoon. The high centrality of YouTube, a user-generated content service, within the Google service network shows that YouTube's initial role of providing specific-content videos (e.g., entertainment) has expanded into a general search service for users.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.93-101
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• 2017

This study investigate the effect of each type of search volume on the number of Facebook fans and the number of tourists. According to the hierarchy effect model, the effect of communication appears to be the sequentiality of cognition-attitude-behavior. Applying this theory, this study predicted that when consumers who have higher involvement and knowledge on specific cities through search behavior, they will be more active in information search through Facebook fan page subscription and will lead to direct tourism behavior. To verify the prediction, we examined the influences among search volume of Seoul shown in Google Trend, the number of fans of official facebook page named 'Seoul Korea', and the number of foreign tourists. As a result, the type of search keyword was divided into four categories: tourism attraction keyword, natural environment keyword, symbolic keyword, and accessibility keyword. The regression analysis showed that tourism attraction keyword and symbolic keyword have influence on Facebook fanpage 'Like'. In addition, facebook fanpage fan size have mediation effect between search volume and number of tourists. All in all, it would be useful to appeal to foreign tourists with a message that emphasizes tourism attraction and Korea-related contents.