• Journal of Wetlands Research
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• v.25 no.2
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• pp.145-158
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• 2023

Constructed wetlands (CWs) are effective technologies for urban wastewater management, utilizing natural physico-chemical and biological processes to remove pollutants. This study employed a bibliometric analysis approach to investigate the progress and future research trends in the field of CWs. A comprehensive review of 100 most-recently published and open-access articles was performed to analyze the performance of CWs in treating wastewater. Spain, China, Italy, and the United States were among the most productive countries in terms of the number of published papers. The most frequently used keywords in publications include water quality (n=19), phytoremediation (n=13), stormwater (n=11), and phosphorus (n=11), suggesting that the efficiency of CWs in improving water quality and removal of nutrients were widely investigated. Among the different types of CWs reviewed, hybrid CWs exhibited the highest removal efficiencies for BOD (88.67%) and TSS (95.67%), whereas VSSF, and HSSF systems also showed high TSS removal efficiencies (83.25%, and 78.83% respectively). VSSF wetland displayed the highest COD removal efficiency (71.82%). Generally, physical processes (e.g., sedimentation, filtration, adsorption) and biological mechanisms (i.e., biodegradation) contributed to the high removal efficiency of TSS, BOD, and COD in CW systems. The hybrid CW system demonstrated highest TN removal efficiency (60.78%) by integrating multiple treatment processes, including aerobic and anaerobic conditions, various vegetation types, and different media configurations, which enhanced microbial activity and allowed for comprehensive nitrogen compound removal. The FWS system showed the highest TP removal efficiency (54.50%) due to combined process of settling sediment-bound phosphorus and plant uptake. Phragmites, Cyperus, Iris, and Typha were commonly used in CWs due to their superior phytoremediation capabilities. The study emphasized the potential of CWs as sustainable alternatives for wastewater management, particularly in urban areas.

• Journal of Korea Entertainment Industry Association
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• v.13 no.7
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• pp.99-118
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• 2019

This study confirmed the followings based on analysis of language messages in 718 advertisement in , AMOREPACIFIC's beauty magazine, published from 1958 to 2018 by product categories, era, in terms of purchase information, persuasive expression, word type. First, the number of pieces among 1980s to 1990s advertisement were the largest and, in terms of product categories, there were the greatest number of pieces in skincare, makeup and mens products. Second, headline and bodycopy had a different aspect in persuasive expression. "focused on image-making" was mainly used for head lines. Specifically, "situational image" was generally dominant. While the "user image" was higher before 1990's, "brand image" was as recent times. "Informal" was mostly applied for bodycopies, especially, "general information" and "differentiated information" was used the most. It is important to know what kind of information the brand established in each brand should be embodied rather than simply dividing the appeal method into "rational appeal" and "emotional appeal."Third, persuasive expression has different aspects in headlines and body copies. "focused on image-making" was mainly used as headlines. Specifically, "situational image" is dominant. Also, "user image" was high before 1990s but "brand image" got higher in recent times. "Informal" was mostly used as body copies, especially "general information" and "differentiated information" were the most frequently selected. Therefore, it is important to apprehend which information to specify established images by brands, rather than to divide "rational appeals" and "emotional appeals". Lastly, categorizing word type into brand names and headlines, foreign language was the most dominant in brand names and Chinese characters in headline. Remarkably, brand names in native language temporarily high in 70's and 80's, which could be interpreted to be resulted from the government policy promoting native language brands in those times. In addition, foreign language was frequently used in cosmetics and Chinese characters in men's product. It could be explained that colors or seasons in cosmetic products were expressed in foreign language in most case. On the other hand, the inclination of men's product consumers, where they pursue prestige or confidence in Chinese character, was actively reflected to language messages.

• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.246-262
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• 2023

This study analyzed policy implementation factors focusing on how Donuimun, a demolished cultural heritage, was digitally restored and the policy implementation process of Donuimun Gate restoration. Through this, the characteristics of the implementation process of the digital Donuimun Gate restoration policy promoted by public-private multilateral collaboration were examined and implications were sought for how institutions with different interests solved problems and collaborated in the implementation process. The research method was focused on policy implementation factors including policy executive factors, policy content factors, policy resource factors, and policy environment factors, and the process was analyzed for each detailed component. Along with literature analysis, in-depth interviews were conducted with participants in policy implementation. As a result of the study, first, it was found in the policy executive factor that the quick decision-making leadership of the policy manager and the flexible attitude of the person in charge of the government agency had a positive effect on preventing conflicts between different interest groups. Second, in terms of policy content, establishing a common goal that everyone can accept and moving forward consistently gave trust and created synergy. Third, in the policy implementation resource factor, the importance of the budget was emphasized. Finally, as an environmental factor for policy implementation, the opening of 5G mobile communication for the first time along with the emergence of the Fourth Industrial Revolution at the time of policy implementation acted as a timely factor. The digital Donuimun Gate was the first case of restoring a lost cultural heritage with AR and VR, and received attention and support from the mass media and the public. This also shows that digital restoration can be a model case that can be a solution without conflicts with local residents where cultural heritages are located or conflicts between stakeholders in the preservation and restoration of real objects.

• Research in Plant Disease
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• v.30 no.3
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• pp.229-235
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• 2024

Conidial production is a critical factor in testing pathogenicity and studying the physiology and ecology of fungal pathogens. Therefore, selecting an appropriate condition and medium for consistent conidia production is essential. In this study, we investigated light conditions and suitable medium conditions using the slide culture method to establish optimal conditions for continuous spore acquisition of Bipolaris oryzae. Primarily, we observed conidial production using two B. oryzae isolates, CM23-042 and 23CM10, under two different light conditions: (1) consistent near-ultraviolet (NUV) with fluorescent light, and (2) a 12-hr shift of the NUV-dark cycle. Secondly, we examined conidial formation under seven different media on potato dextrose agar (PDA), V8-Juice agar, minimal medium (MM), sucrose-proline agar (SPA), rabbit food agar (RFA), rice bran agar (RBA), and rice leaf agar (RLA). Under consistent NUV light with fluorescent conditions, conidia were induced in both isolates, whereas conidia were not produced under other conditions after 7 days post-inoculation (dpi). Moreover, B. oryzae isolate CM23-042 produced the highest number of conidia in MM, while isolate 23CM10 yielded the highest number of conidia in PDA after 7 dpi. In summary, our data demonstrated that the consistent NUV light with fluorescent conditions were most conducive for conidia induction in B. oryzae. The selection of a medium for conidiation may vary depending on the B. oryzae isolates, but using MM and PDA or SPA and RFA medium could be effective for spore induction. These findings will contribute to improving conidiation according to the characteristics of collected isolates of B. oryzae.

• Journal of Global Scholars of Marketing Science
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• v.17 no.2
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• pp.1-29
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• 2007

The flow theory becomes one of the most important frameworks in the internet research arena. Hoffman and Novak proposed a hierarchical flow model showing the antecedents and outcomes of flow and the relationship among these variables in the hyper-media computer circumstances (Hoffman and Novak 1996). This model was further tested after their initial research (Novak, Hoffman, and Yung 2000). At their paper, Hoffman and Novak explained that the balance of challenge and skill leads to flow which means the positive optimal state of mind (Hoffman and Novak 1996). An imbalance between challenge and skill, leads to negative states of mind like anxiety, boredom, apathy (Csikszentmihalyi and Csikszentmihalyi 1988). Almost all research on the flow 4-channel model have been focusingon flow, the positive state of mind (Ellis, Voelkl, and Morris 1994 Mathwick and Rigdon 2004). However, it also needs to examine the formation of the negative states of minds and their outcomes. Flow researchers explain play or playfulness as antecedents or the early state of flow. However, play has been regarded as a distinct concept from flow in the flow literatures (Hoffman and Novak 1996; Novak, Hoffman, and Yung 2000). Mathwick and Rigdon discovered the influences of challenge and skill on play; they also observed the influence of play on web-loyalty and brand loyalty (Mathwick and Rigdon 2004). Unfortunately, they did not go so far as to test the influences of play on state of mind. This study focuses on the relationships between state of mind in the flow 4-channel model and play. Early research has attempted to hypothetically explain state of mind in flow theory, but has not been tested except flow until now. Also the importance of play has been emphasized in the flow theory, but has not been tested in the flow 4-channel model context. This researcher attempts to analyze the relationships among state of mind, skill of play, challenge, state of mind and web loyalty. For this objective, I developed a measure for state of mind and defined the concept of play as a trait. Then, the influences of challenge and skill on the state of mind and play under on-line shopping conditions were tested. Also the influences of play on state of mind were tested and those of flow and play on web loyalty were highlighted. 294 undergraduate students participated in this research survey. They were asked to respond about their perceptions of challenge, skill, state of mind, play, and web-loyalty to on-line shopping mall. Respondents were restricted to students who bought products on-line in a month. In case of buying products at two or more on-line shopping malls, they asked to respond about the shopping mall where they bought the most important one. Construct validity, discriminant validity, and convergent validity were used to check the measurement validations. Also, Cronbach's alpha was used to check scale reliability. A series of exploratory factor analyses was conducted. This researcher conducted confirmatory factor analyses to assess the validity of measurements. All items loaded significantly on their respective constructs. Also, all reliabilities were greater than.70. Chi-square difference tests and goodness of fit tests supported discriminant and convergent validity. The results of clustering and ANOVA showed that high challenge and high skill leaded to flow, low challenge and high skill leaded to boredom, and low challenge and low skill leaded to apathy. But, it was different from my expectation that high challenge and low skill didnot lead to anxiety but leaded to apathy. The results also showed that high challenge and high skill, and high challenge and low skill leaded to the highest play. Low challenge leaded to low play. 4 Structural Equation Models were built by flow, anxiety, boredom, apathy for analyzing not only the impact of play on state of mind and web-loyalty, but also that of state of mind on web-loyalty. According the analyses results of these models, play impacted flow and web-loyalty positively, but impacted anxiety, boredom, and apathy negatively. Results also showed that flow impacted web-loyalty positively, but anxiety, boredom, and apathy impacted web-loyalty negatively. The interpretations and implications of the test results of the hypotheses are as follows. First, respondents belonging to different clusters based on challenge and skill level experienced different states of mind such as flow, anxiety, boredom, apathy. The low challenge and low skill group felt the highest anxiety and apathy. It could be interpreted that this group feeling high anxiety or fear, then avoided attempts to shop on-line. Second, it was found that higher challenge leads to higher levels of play. Test results show that the play level of the high challenge and low skill group (anxiety group) was higher than that of the high challenge and high skill group (flow group). However, this was not significant. Third, play positively impacted flow and negatively impacted boredom. The negative impacts on anxiety and apathy were not significant. This means that the combination of challenge and skill creates different results. Forth, play and flow positively impacted web-loyalty, but anxiety, boredom, apathy had negative impacts. The effect of play on web-loyalty was stronger in case of anxiety, boredom, apathy group than fl ow group. These results show that challenge and skill influences state of mind and play. Results also demonstrate how play and flow influence web-loyalty. It implies that state of mind and play should be the core marketing variables in internet marketing. The flow theory has been focusing on flow and on the positive outcomes of flow experiences. But, this research shows that lots of consumers experience the negative state of mind rather than flow state in the internet shopping circumstance. Results show that the negative state of mind leads to low or negative web-loyalty. Play can have an important role with the web-loyalty when consumers have the negative state of mind. Results of structural equation model analyses show that play influences web-loyalty positively, even though consumers may be in the negative state of mind. This research found the impacts of challenge and skill on state of mind in the flow 4-channel model, not only flow but also anxiety, boredom, apathy. Also, it highlighted the role of play in the flow 4-channel model context and impacts on web-loyalty. However, tests show a few different results from hypothetical expectations such as the highest anxiety level of apathy group and insignificant impacts of play on anxiety and apathy. Further research needs to replicate this research and/or to compare 3-channel model with 4-channel model.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.57-77
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• 2013

Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.

• Journal of Science of Art and Design
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• v.10
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• pp.5-50
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• 2006

The terminology "human body" simply means a physical body but also more often, as an object in art works, carries symbolic concepts incorporating the whole history of human lives. Human body has been employed as an artistic object capturing physical body, delivering artist's idea expressing life indicators from different standpoints of times and places. This point of view about human body in art works has in fact rather short history since 1960's when modern thinking paradigm focusing upon rationality and reasoning has begun declining and on the contrary when the body used to be the servant of the mind and soul for a long time has begun attracting artist's attention as a real entity from the viewpoint of dichotomy. During the 1960's, frequent performances in Pop art and of Fluxus showed that the human body has been an important media for artistic communication after importance of body performances had been raised in Action painting in 1940's. The human body became a more determined media in body art works that had got into stride after Yves Kline's conceptual works applying body and its traces. These kinds of art works have continued and consolidated into the Feminism came into blossom in 1980's and into fragmentated and disembodied body art trend in 1990's. Through development of trends in body works, human body now might well be regarded as a clue provide from individual identity with implication over the world. This thesis is to analyse in semiotic way main works of Kiki Smith who is a representative artist devoting to Feminism and proposing extended significance of human body. In the analysis process of works done by two great artists with histrorical background of art trend in order to find and open an significance horizon of human body, semiotics and bodism are therefore perceived as pertinent and applied as basic tools. The first stage of analysis is to get the significances emerged in between expression part and contextual parts, which are separated structually from the most basic level. The study deals with body works furthermore in the way of structual cohesion of the expression and the context from the view of A J. Greimas' Structural Semantics and tried to build up a basic frame for the extended significances of human body. This thesis is, on the other hand, to attempt to contribute for extension of disembodied and fragmentated body discussed in the structural semantic frame earlier by Julia Kriesteva who delivers abjection concepts and phenomenology of Maurice Merleau-Ponty who enables to overview relationship between the body and the world from the viewpoint of Bodism, further into interpretation level. The other works are Kiki smith's that showed epics about death in mid-1980's, detailed humbleness of vulnerable human body exposed to dichotomy and fragmentation in 1990's and religion and mythology incorporating wouln healing in 2000's and henceforth. Through the analysis of Kiki Smith's representative work 'Pee body', it is verified and confirmed that fragmentated body showed beyond boundary gap of the human body and ultimately tends to imply human healing owing to divine maternity. Bodily symbols in Kiki Smith's are extended to the universal world to imply human life and death on the one hand and religion and mythology of human wound and divine healing one the other hand. This thesis through these process and results of analysis is in a broad context, to emphasize that human body as objectified text has a key indicator role to understand world as well as semiotic extension in art works in late 20th century so that we might confirm bodily symbol as a cultural context constitutes a section of contemporary visual arts.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.163-176
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• 2014

Social media is becoming the platform for users to communicate their activities, status, emotions, and experiences to other people. In recent years, microblogs, such as Twitter, have gained in popularity because of its ease of use, speed, and reach. Compared to a conventional web blog, a microblog lowers users' efforts and investment for content generation by recommending shorter posts. There has been a lot research into capturing the social phenomena and analyzing the chatter of microblogs. However, measuring television ratings has been given little attention so far. Currently, the most common method to measure TV ratings uses an electronic metering device installed in a small number of sampled households. Microblogs allow users to post short messages, share daily updates, and conveniently keep in touch. In a similar way, microblog users are interacting with each other while watching television or movies, or visiting a new place. In order to measure TV ratings, some features are significant during certain hours of the day, or days of the week, whereas these same features are meaningless during other time periods. Thus, the importance of features can change during the day, and a model capturing the time sensitive relevance is required to estimate TV ratings. Therefore, modeling time-related characteristics of features should be a key when measuring the TV ratings through microblogs. We show that capturing time-dependency of features in measuring TV ratings is vitally necessary for improving their accuracy. To explore the relationship between the content of microblogs and TV ratings, we collected Twitter data using the Get Search component of the Twitter REST API from January 2013 to October 2013. There are about 300 thousand posts in our data set for the experiment. After excluding data such as adverting or promoted tweets, we selected 149 thousand tweets for analysis. The number of tweets reaches its maximum level on the broadcasting day and increases rapidly around the broadcasting time. This result is stems from the characteristics of the public channel, which broadcasts the program at the predetermined time. From our analysis, we find that count-based features such as the number of tweets or retweets have a low correlation with TV ratings. This result implies that a simple tweet rate does not reflect the satisfaction or response to the TV programs. Content-based features extracted from the content of tweets have a relatively high correlation with TV ratings. Further, some emoticons or newly coined words that are not tagged in the morpheme extraction process have a strong relationship with TV ratings. We find that there is a time-dependency in the correlation of features between the before and after broadcasting time. Since the TV program is broadcast at the predetermined time regularly, users post tweets expressing their expectation for the program or disappointment over not being able to watch the program. The highly correlated features before the broadcast are different from the features after broadcasting. This result explains that the relevance of words with TV programs can change according to the time of the tweets. Among the 336 words that fulfill the minimum requirements for candidate features, 145 words have the highest correlation before the broadcasting time, whereas 68 words reach the highest correlation after broadcasting. Interestingly, some words that express the impossibility of watching the program show a high relevance, despite containing a negative meaning. Understanding the time-dependency of features can be helpful in improving the accuracy of TV ratings measurement. This research contributes a basis to estimate the response to or satisfaction with the broadcasted programs using the time dependency of words in Twitter chatter. More research is needed to refine the methodology for predicting or measuring TV ratings.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.1-21
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• 2012

In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.