• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.158-159
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• 2017

Sentiment analysis is the review of written or verbal communications to determine some measure of emotion or feeling in the communication. Search engines are one of the most popular sites visited on the Internet generating hundreds of billions of hits per month worldwide. Obviously privacy policies related to these search sites are extremely important. Our study reviews the privacy policies of the two largest search engines, Google and Baidu to determine the overall sentiment of their privacy policies. Significant individual findings and significant differences were found using several sentiment and opinion analysis methods.

• 중국학논총
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• no.67
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• pp.25-41
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• 2020

当我们翻开中韩词典时, 就不难发现令人莫名其妙的词汇不在少数, 而且在部分词汇的解释上也存在着不少问题。本文主要探讨了这些词汇被收录于词典是否合适和词语释义是否正确的问题。为此, 先从中韩词典里筛选出在中国教育部语言文字应用研究所和北京大学中国语言学研究中心所提供的现代汉语语料库中出现频率较低的词汇。若考虑到这两个语料库为全方位收集现代汉语而做了巨大的努力, 而且肯定这一学术成果的话, 就能推测此文里筛选出的这些词汇很可能不太正规或现在不怎幺使用等事实。为了使这种推测能得到更准确的印证, 作者在百度网上又检索了是否出现它们的用例, 且对词语释义和实际用例是否一致做了详细的比较, 就发现不少词汇确实存在各种问题, 根本不适合被收录到词典, 或必须修改释义内容。

• 중국학논총
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• no.70
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• pp.39-60
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• 2021

当我们翻开中韩词典时, 就不难发现令人莫名其妙的词汇不在少数, 而且在部分词汇的解释上也存在着不少问题。本文主要探讨了这些词汇被收录于词典是否合适和词语释义是否正确的问题。为此, 先从中韩词典里筛选出在中国教育部语言文字应用研究所和北京大学中国语言学研究中心所提供的现代汉语语料库中出现频率较低的词汇。若考虑到这两个语料库为全方位收集现代汉语而做了巨大的努力, 而且肯定这一学术成果的话, 就能推测此文里筛选出的这些词汇很可能不太正规或现在不怎幺使用等事实。为了使这种推测能得到更准确的印证, 作者在百度网上又检索了是否出现它们的用例, 且对词语释义和实际用例是否一致做了详细的比较, 就发现不少词汇确实存在各种问题, 根本不适合被收录到词典, 或必须修改释义内容。

• 중국학논총
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• no.61
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• pp.1-18
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• 2019

当我们翻开中韩词典时, 就不难发现令人莫名其妙的词汇不在少数, 而且在部分词汇的解释上也存在着不少问题. 本文主要探讨了这些词汇被收录于词典是否合适和词语释义是否正确的问题. 为此, 先从中韩词典里筛选出在中国教育部语言文字应用研究所和北京大学中国语言学研究中心所提供的现代汉语语料库中出现频率较低的词汇. 若考虑到这两个语料库为全方位收集现代汉语而做了巨大的努力, 而且肯定这一学术成果的话, 就能推测此文里筛选出的这些词汇很可能不太正规或现在不怎幺使用等事实. 为了使这种推测能得到更准确的印证, 作者在百度网上又检索了是否出现它们的用例, 且对词语释义和实际用例是否一致做了详细的比较, 就发现不少词汇确实存在各种问题, 根本不适合被收录到词典, 或必须修改释义内容.

• Asia Marketing Journal
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• v.16 no.3
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• pp.23-33
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• 2014

The selection of keywords for bidding is a critical component of paid search advertising. When the number of possible keywords is enormous, it becomes difficult to choose the best keywords for advertising and then subsequently to assess their effect. To this end, we propose an ultrahigh dimensional keyword selection approach that not only reduces the dimension for selections, but also generates the top listed keywords for profits. An empirical analysis using a unique panel dataset from a large online clothes retailer that advertises on the largest search engine in China (i.e., Baidu) is presented to illustrate the usefulness of our approach.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.71-82
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• 2021

The main purpose of this study was to investigate K-pop stars' images in photos presented by social networks in China. In this study photos of K-pop stars were collected from a community site of Baidu as one of the biggest portal sites and were five idol groups (EXO, IKON, T-ara, Wonder Girls, and Girls' Generation) which have beeb getting famous in China. For this musical styles and backgrounds of the K-pop idol stars were scrutinized in brief and explored in respect with its images. The results of the study were follows: First, the overall pictorial images of K-pop boys' groups were characterized in masculine and stylish images emphasizing the western appearance. In case of K-pop girl groups, sexy, gorgeous, feminine and youthful images were identified. In conclusion, K-pop idol stars is contributing to expand Korean pop arts into Chinese public culture as Chinese people produced and circulated the pictorial images of K-pop stars and facilitated consumption activities of K-pop contents.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.1
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• pp.115-122
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• 2017

Deep learning is artificial intelligence technology that can teach people like themselves who need machine learning. Deep learning has become of the most promising in the development of artificial intelligence to understand the world and detection technology, and Google, Baidu and Facebook is the most developed in advance. In this paper, we discuss the kind of deep learning frameworks, compare and analyze the efficiency of the image and speech recognition field of it.

• Electronics and Telecommunications Trends
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• v.33 no.6
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• pp.107-117
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• 2018

In recent years, with the development of autonomous driving technology, high-performance artificial intelligence computing hardware platforms have been developed that can process multi-sensor data, object recognition, and vehicle control for autonomous vehicles. Most of these hardware platforms have been developed overseas, such as NVIDIA's DRIVE PX, Audi's zFAS, Intel GO, Mobile Eye's EyeQ, and BAIDU's Apollo Pilot. In Korea, however, ETRI's artificial intelligence computing platform has been developed. In this paper, we discuss the specifications, structure, performance, and development status centering on hardware platforms that support autonomous driving rather than the overall contents of autonomous driving technology.

• 중국학논총
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• no.65
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• pp.23-38
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• 2020

The dictionary is the most important tool for every Chinese learner to confirm the meaning and usage of words. Therefore, accuracy of headword's interpretation in the dictionary is crucial. This study aims to discuss the accuracy and the adequacy of headwords' interpretation in the Chinese-Korean dictionary through the Chinese corpus and Baidu. The scope of this study are 3000 words in the D3H1 region. According to the research results, the main problems of the vocabulary in this region can be divided into three categories: the first is the problem of lexical interpretation, the second is the problem of missing interpretation, and the third is other problems. In the D3H1 area, there are a total of 719 low-frequency vocabularies, and 54 headword's interpretations are not accurate or appropriate. This study is a detailed investigation and analysis of the problems of these 54 vocabularies.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.