• Journal of Korea Multimedia Society
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• v.21 no.3
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• pp.369-381
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• 2018

Nowadays a personalization algorithm is gaining huge attention. It gives users selective information which is helpful and interesting in a deluge of information based on their past behavior on the internet. However there is also a fatal side effect that the user can only get restricted information on restricted topics selected by the algorithm. Basically, the personalization algorithm makes users have a narrower perspective and even stronger bias because users have less chances to get views of opponent. Eli Pariser called this problem the 'filter bubble' in his book. It is important to understand exactly what a filter bubble is to solve the problem. Therefore, this paper shows how much Google's personalized search algorithm influences search result through an experiment with deep neural networks acting like users. At the beginning of the experiment, two Google accounts are newly created, not to be influenced by the Google's personalized search algorithm. Then the two pure accounts get politically biased by two methods. We periodically calculate the numerical score depending on the character of links and it shows how biased the account is. In conclusion, this paper shows the formation process of filter bubble by a personalization algorithm through the experiment.

• 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.

• Culinary science and hospitality research
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• v.23 no.4
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• pp.22-32
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• 2017

The purpose of this study was to explore awareness of food tourism using big data analysis. For this, this study collected data containing 'food tourism' keywords from google web search, google news, and google scholar during one year from January 1 to December 31, 2016. Data were collected by using SCTM (Smart Crawling & Text Mining), a data collecting and processing program. From those data, degree centrality and eigenvector centrality were analyzed by utilizing packaged NetDraw along with UCINET 6. The result showed that the web visibility of 'core service' and 'social marketing' was high. In addition, the web visibility was also high for destination, such as rural, place, ireland and heritage; 'socioeconomic circumstance' related words, such as economy, region, public, policy, and industry. Convergence of iterated correlations showed 4 clustered named 'core service', 'social marketing', 'destinations' and 'social environment'. It is expected that this diagnosis on food tourism according to changes in international business environment by using these web information will be a foundation of baseline data useful for establishing food tourism marketing strategies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.290-293
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• 2017

최근 IoT 기술발달로 인한 스마트폰 및 대용량 미디어기기 사용증가로 인터넷 네트워크 사용량이 폭발적으로 증가되고 있고, 이러한 데이터 사용량 급증으로 대량의 데이터를 지칭하는 빅데이터 수집 및 분석에 많은 기업과 정부가 주목하고 있다. 빅데이터는 기존에 없던 새로운 데이터의 구축이 아니며, 그동안 축적된 다방면의 방대한 데이터의 집합이라 할 수 있다. 빅데이터의 이용 및 분석에 대한 기업 정부 학계의 수요는 증가하고 있지만, 고난도의 빅데이터 분석을 위한 인프라 구축이 선결과제이어서, 이러한 인프라구축 비용 때문에 빅데이터 분석이 일선 산업분야에 바로 적용하는데 많은 장애요인이 되어 데이터 분석가들의 빅데이터 분석에 애로사항으로 존재하고 있다. 이러한 어려움을 해소하기 위한 방안으로 새로운 인프라 구축 없이 Google Analytics API를 연동한 R 프로그래밍의 데이터 시각화를 활용한 데이터 분석 방안을 제시하고자 한다. 본 연구에서는 구글 애널리틱스 API를 연동하여 사용자 웹사이트의 사용자접속, 사이트운영, 이벤트 발생 등의 데이터를 R 프로그램을 활용하여 사이트 현황을 데이터 시각화로 분석하고 운영중인 웹사이트에 적용 가능한 콘텐츠 개발 방안에 대해 연구하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.10-13
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• 2015

Google App Engine(GAE)은 플랫폼 서비스 형태(Platform as a Service, PaaS)의 클라우드 인프라이며 GAE를 기반으로 웹어플리케이션을 제작할 수 있도록 다양한 개발 도구를 제공해 준다. 본 논문에서는 Python 및 Go를 이용하여 GAE 상에서 구현한 클라우드 기반의 web application들의 성능을 비교하고자 한다. 각 web application의 주요 기능은 회원가입, 로그인, 채팅 등으로 구성되어 있고 특히, 회원목록이나 채팅 데이터를 처리하기 위하여 GAE에서 제공하는 Google Datastore를 사용하였다. 성능비교를 위하여 Python2.5, Python 2.7 및 Go를 사용하여 통일한 기능의 web application을 구현하였으며 각각의 메뉴에 대하여 서버 로직의 실행과 장고 (Django) 스타일의 HTML 템플릿을 렌더링하는데 걸리는 시간을 구하고 이를 비교 분석하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.248-251
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• 2010

Smart Phones from a PC using the Internet using a multimedia data service provides a scalable and user convenience is provided in the form of an application. Wired and wireless communications, especially with the reduction of royalty free WiFi or the Internet to download the application program on the PC you're using on the Smart Phone. In this paper, the location API in Android-based Smart Phone, using GPS coordinates identified in the latitude and longitude coordinates can be transferred to the server, Android Smart Phone to know the possibility of retracing the location. You are smart trace back information from the user application program design, development, and real-time GPS location signals combined backtrack to read the GPS location in Google Earth application is to study the trace back.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.672-674
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• 2010

There are various ways for expressing map on android system. The typical method is to use the API provided by Google, called geocoding although simple display of location of GPS is possible, but node expression of road or the detail information on map for various location service are not available. And it is difficult to express a location in shadow area. In this paper, to solve these problems, we propose a map expression method for location service in specific area based on geocoding and apply the method.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.65-71
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• 2017

Since existing Internet of Things(IoT) is vulnerable, it may cause property damage due to the information leakage. Especially, the smart door lock system built on the IoT can cause more damage. To solve these problems, this paper classify the data generated by the sensor according to the condition and send an alarm message to the user's smartphone through Google Cloud Message (GCM). We made it possible to check the images in real time through the smartphone application and control the door lock using the TCP / IP protocol. Also, we applied OTP-Based Matrix SEED algorithm to door lock system to improve security.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.149-156
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• 2021

Gambling negatively affects the economy, and it brings unwanted financial, social, and health outcomes to gamblers. On the one hand, unemployment is argued to be a leading cause of gambling. On the other hand, gambling can cause unemployment in the second-order via gambling-induced poor health, falling productivity, and crime. In terms of significant effects, previous studies were able to establish an association, but not causality. The current study examines the time-sequence and contemporaneous causalities between lottery gambling and unemployment in Thailand. The Granger causality and directed acyclic graph (DAG) tests employ time-series data on gambling- and unemployment-related Google Trends indexes from January 2004 to April 2021 (208 monthly observations). These tests are based on the estimates from a vector autoregressive (VAR) model. Granger causality is a way to investigate causality between two variables in a time series. However, this approach cannot detect the contemporaneous causality among variables that occurred within the same period. The contemporaneous causal structure of gambling and unemployment was identified via the data-determined DAG approach. The use of time-series Google Trends indexes in gambling studies is new. Based on this data set, unemployment is found to contemporaneously cause gambling, whereas gambling Granger causes unemployment. The causalities are circular and last for four months.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.79-85
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• 2021

Speech recognition technology refers to a technology in which a computer interprets the speech language spoken by a person and converts the contents into text data. This technology has recently been combined with artificial intelligence and has been used in various fields such as smartphones, set-top boxes, and smart TVs. Examples include Google Assistant, Google Home, Samsung's Bixby, Apple's Siri and SK's NUGU. Google and Daum Kakao offer free open APIs for speech recognition technologies. This paper selects three APIs that are free to use by ordinary users, and compares each recognition rate according to the three types. First, the recognition rate of "numbers" and secondly, the recognition rate of "Ga Na Da Hangul" are conducted, and finally, the experiment is conducted with the complete sentence that the author uses the most. All experiments use real voice as input through a computer microphone. Through the three experiments and results, we hope that the general public will be able to identify differences in recognition rates according to the applications currently available, helping to select APIs suitable for specific application purposes.