• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• MISULJARYO - National Museum of Korea Art Journal
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• v.96
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• pp.123-154
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• 2019

Ancestral Burial Ground on the Inwangsan Mountain is a ten-panel folding screen with images and postscripts. Commissioned by Bak Gyeong-bin (dates unknown), this screen was painted by Jo Jung-muk (1820-after 1894) in 1868. The postscripts were written by Hong Seon-ju (dates unknown). The National Museum of Korea restored this painting, which had been housed in the museum on separate sheets, to its original folding screen format. The museum also opened the screen to the public for the first time at the special exhibition Through the Eyes of Joseon Painters: Real Scenery Landscapes of Korea held from July 23 to September 22, 2019. Ancestral Burial Ground on the Inwangsan Mountain depicts real scenery on the western slopes of Inwangsan Mountain spanning present-day Hongje-dong and Hongeun-dong in Seodaemun-gu, Seoul. In the distance, the Bukhansan Mountain ridges are illustrated. The painting also bears place names, including Inwangsan Mountain, Chumohyeon Hill, Hongjewon Inn, Samgaksan Mountain, Daenammun Gate, and Mireukdang Hall. The names and depictions of these places show similarities to those found on late Joseon maps. Jo Jung-muk is thought to have studied the geographical information marked on maps so as to illustrate a broad landscape in this painting. Field trips to the real scenery depicted in the painting have revealed that Jo exaggerated or omitted natural features and blended and arranged them into a row for the purposes of the horizontal picture plane. Jo Jung-muk was a painter proficient at drawing conventional landscapes in the style of the Southern School of Chinese painting. Details in Ancestral Burial Ground on the Inwangsan Mountain reflect the painting style of the School of Four Wangs. Jo also applied a more decorative style to some areas. The nineteenth-century court painters of the Dohwaseo(Royal Bureau of Painting), including Jo, employed such decorative painting styles by drawing houses based on painting manuals, applying dots formed like sprinkled black pepper to depict mounds of earth and illustrating flowers by dotted thick pigment. Moreover, Ancestral Burial Ground on the Inwangsan Mountain shows the individualistic style of Jeong Seon(1676~1759) in the rocks drawn with sweeping brushstrokes in dark ink, the massiveness of the mountain terrain, and the pine trees simply depicted using horizontal brushstrokes. Jo Jung-muk is presumed to have borrowed the authority and styles of Jeong Seon, who was well-known for his real scenery landscapes of Inwangsan Mountain. Nonetheless, the painting lacks an spontaneous sense of space and fails in conveying an impression of actual sites. Additionally, the excessively grand screen does not allow Jo Jung-muk to fully express his own style. In Ancestral Burial Ground on the Inwangsan Mountain, the texts of the postscripts nicely correspond to the images depicted. Their contents can be divided into six parts: (1) the occupant of the tomb and the reason for its relocation; (2) the location and geomancy of the tomb; (3) memorial services held at the tomb and mysterious responses received during the memorial services; (4) cooperation among villagers to manage the tomb; (5) the filial piety of Bak Gyeong-bin, who commissioned the painting and guarded the tomb; and (6) significance of the postscripts. The second part in particular is faithfully depicted in the painting since it can easily be visualized. According to the fifth part revealing the motive for the production of the painting, the commissioner Bak Gyeongbin was satisfied with the painting, stating that "it appears impeccable and is just as if the tomb were newly built." The composition of the natural features in a row as if explaining each one lacks painterly beauty, but it does succeed in providing information on the geomantic topography of the gravesite. A fair number of the existing depictions of gravesites are woodblock prints of family gravesites produced after the eighteenth century. Most of these are included in genealogical records and anthologies. According to sixteenth- and seventeenth-century historical records, hanging scrolls of family gravesites served as objects of worship. Bowing in front of these paintings was considered a substitute ritual when descendants could not physically be present to maintain their parents' or other ancestors' tombs. Han Hyo-won (1468-1534) and Jo Sil-gul (1591-1658) commissioned the production of family burial ground paintings and asked distinguished figures of the time to write a preface for the paintings, thus showing off their filial piety. Such examples are considered precedents for Ancestral Burial Ground on the Inwangsan Mountain. Hermitage of the Recluse Seokjeong in a private collection and Old Villa in Hwagae County at the National Museum of Korea are not paintings of family gravesites. However, they serve as references for seventeenth-century paintings depicting family gravesites in that they are hanging scrolls in the style of the paintings of literary gatherings and they illustrate geomancy. As an object of worship, Ancestral Burial Ground on the Inwangsan Mountain recalls a portrait. As indicated in the postscripts, the painting made Bak Gyeong-bin "feel like hearing his father's cough and seeing his attitudes and behaviors with my eyes." The fable of Xu Xiaosu, who gazed at the portrait of his father day and night, is reflected in this gravesite painting evoking a deceased parent. It is still unclear why Bak Gyeong-bin commissioned Ancestral Burial Ground on the Inwangsan Mountain to be produced as a real scenery landscape in the folding screen format rather than a hanging scroll or woodblock print, the conventional formats for a family gravesite paintings. In the nineteenth century, commoners came to produce numerous folding screens for use during the four rites of coming of age, marriage, burial, and ancestral rituals. However, they did not always use the screens in accordance with the nature of these rites. In the Ancestral Burial Ground on the Inwangsan Mountain, the real scenery landscape appears to have been emphasized more than the image of the gravesite in order to allow the screen to be applied during different rituals or for use to decorate space. The burial mound, which should be the essence of Ancestral Burial Ground on the Inwangsan Mountain, might have been obscured in order to hide its violation of the prohibition on the construction of tombs on the four mountains around the capital. At the western foot of Inwangsan Mountain, which was illustrated in this painting, the construction of tombs was forbidden. In 1832, a tomb discovered illegally built on the forbidden area was immediately dug up and the related people were severely punished. This indicates that the prohibition was effective until the mid-nineteenth century. The postscripts on the Ancestral Burial Ground on the Inwangsan Mountain document in detail Bak Gyeong-bin's efforts to obtain the land as a burial site. The help and connivance of villagers were necessary to use the burial site, probably because constructing tombs within the prohibited area was a burden on the family and villagers. Seokpajeong Pavilion by Yi Han-cheol (1808~1880), currently housed at the Los Angeles County Museum of Art, is another real scenery landscape in the format of a folding screen that is contemporaneous and comparable with Ancestral Burial Ground on the Inwangsan Mountain. In 1861 when Seokpajeong Pavilion was created, both Yi Han-cheol and Jo Jung-muk participated in the production of a portrait of King Cheoljong. Thus, it is highly probable that Jo Jung-muk may have observed the painting process of Yi's Seokpajeong Pavilion. A few years later, when Jo Jungmuk was commissioned to produce Ancestral Burial Ground on the Inwangsan Mountain, his experience with the impressive real scenery landscape of the Seokpajeong Pavilion screen could have been reflected in his work. The difference in the painting style between these two paintings is presumed to be a result of the tastes and purposes of the commissioners. Since Ancestral Burial Ground on the Inwangsan Mountain contains the multilayered structure of a real scenery landscape and family gravesite, it seems to have been perceived in myriad different ways depending on the viewer's level of knowledge, closeness to the commissioner, or viewing time. In the postscripts to the painting, the name and nickname of the tomb occupant as well as the place of his surname are not recorded. He is simply referred to as "Mister Bak." Biographical information about the commissioner Bak Gyeong-bin is also unavailable. However, given that his family did not enter government service, he is thought to have been a person of low standing who could not become a member of the ruling elite despite financial wherewithal. Moreover, it is hard to perceive Hong Seon-ju, who wrote the postscripts, as a member of the nobility. He might have been a low-level administrative official who belonged to the Gyeongajeon, as documented in the Seungjeongwon ilgi (Daily Records of Royal Secretariat of the Joseon Dynasty). Bak Gyeong-bin is presumed to have moved the tomb of his father to a propitious site and commissioned Ancestral Burial Ground on the Inwangsan Mountain to stress his filial piety, a conservative value, out of his desire to enter the upper class. However, Ancestral Burial Ground on the Inwangsan Mountain failed to live up to its original purpose and ended up as a contradictory image due to its multiple applications and the concern over the exposure of the violation of the prohibition on the construction of tombs on the prohibited area. Forty-seven years after its production, this screen became a part of the collection at the Royal Yi Household Museum with each panel being separated. This suggests that Bak Gyeong-bin's dream of bringing fortune and raising his family's social status by selecting a propitious gravesite did not come true.