• Journal of KIISE:Databases
• /
• v.30 no.4
• /
• pp.381-396
• /
• 2003

Subsequence matching is an operation that finds subsequences whose changing patterns are similar to a given query sequence from time-series databases. This paper points out the performance bottleneck in subsequence matching, and then proposes an effective method that improves the performance of entire subsequence matching significantly by resolving the performance bottleneck. First, we analyze the disk access and CPU processing times required during the index searching and post processing steps through preliminary experiments. Based on their results, we show that the post processing step is the main performance bottleneck in subsequence matching, and them claim that its optimization is a crucial issue overlooked in previous approaches. In order to resolve the performance bottleneck, we propose a simple but quite effective method that processes the post processing step in the optimal way. By rearranging the order of candidate subsequences to be compared with a query sequence, our method completely eliminates the redundancy of disk accesses and CPU processing occurred in the post processing step. We formally prove that our method is optimal and also does not incur any false dismissal. We show the effectiveness of our method by extensive experiments. The results show that our method achieves significant speed-up in the post processing step 3.91 to 9.42 times when using a data set of real-world stock sequences and 4.97 to 5.61 times when using data sets of a large volume of synthetic sequences. Also, the results show that our method reduces the weight of the post processing step in entire subsequence matching from about 90% to less than 70%. This implies that our method successfully resolves th performance bottleneck in subsequence matching. As a result, our method provides excellent performance in entire subsequence matching. The experimental results reveal that it is 3.05 to 5.60 times faster when using a data set of real-world stock sequences and 3.68 to 4.21 times faster when using data sets of a large volume of synthetic sequences compared with the previous one.

• Journal of Intelligence and Information Systems
• /
• v.20 no.4
• /
• pp.89-105
• /
• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Korean Security Journal
• /
• no.13
• /
• pp.145-168
• /
• 2007

Like to change to the information-oriented society, the guard service needs to be changed. The communication and hardware technology develop rapidly and according to the internet environment change from cable to wireless, modern person can approach every kinds of information service using wireless communication machinery which can be moved such as laptop, computer, PDA, mobile phone and so on, LBS field which presents the needing information and service at anytime, anywhere, and which kinds of device expands it's territory all the more together with the appearance of ubiquitous concept. LBS use the chip in the mobile phone and make to confirm the position of the joining member anytime within several tens centimeters to hundreds meters. LBS can be divided by the service method which use mobile communication base station and apply satellite. Also each service type can be divided by location chase service, public safe service, location based information service and so on, and it is the part which will plan with guard service development. It will be prospected 8.460 hundred million in 2005 years and 16.561 hundred million in 2007 years scale of market. Like this situation, it can be guessed that the guard service has to change rapidly according to the LBS application. Study method chooses documentary review basically, and at first theory method mainly uses the second documentary examination which depends on learned journal and independent volume which published in the inside and the outside of the country, internet searching, other kinds of all study report, statute book, thesis which published at public order research institute of the Regional Police Headquarter, police operation data, data which related with statute, documents and statistical data which depend on private guard company and so on. So the purpose of the study gropes in accordance with the LBS application, and present the problems and improvement method to analyze indirect of manager side of operate guard adaptation service of LBS, government side which has to activate LBS, systematical, operation management, manpower management and education training which related with guard course side which has to study and educate in accordance with application of the new guard service, as well as intents to excellent quality service of guard.

• Journal of Intelligence and Information Systems
• /
• v.17 no.2
• /
• pp.97-107
• /
• 2011

Nowadays there are a lot of issues about copyright infringement in the Internet world because the digital content on the network can be copied and delivered easily. Indeed the copied version has same quality with the original one. So, copyright owners and content provider want a powerful solution to protect their content. The popular one of the solutions was DRM (digital rights management) that is based on encryption technology and rights control. However, DRM-free service was launched after Steve Jobs who is CEO of Apple proposed a new music service paradigm without DRM, and the DRM is disappeared at the online music market. Even though the online music service decided to not equip the DRM solution, copyright owners and content providers are still searching a solution to protect their content. A solution to replace the DRM technology is digital audio watermarking technology which can embed copyright information into the music. In this paper, the author proposed a new audio watermarking algorithm with two approaches. First, the watermark information is generated by two dimensional barcode which has error correction code. So, the information can be recovered by itself if the errors fall into the range of the error tolerance. The other one is to use chirp sequence of CDMA (code division multiple access). These make the algorithm robust to the several malicious attacks. There are many 2D barcodes. Especially, QR code which is one of the matrix barcodes can express the information and the expression is freer than that of the other matrix barcodes. QR code has the square patterns with double at the three corners and these indicate the boundary of the symbol. This feature of the QR code is proper to express the watermark information. That is, because the QR code is 2D barcodes, nonlinear code and matrix code, it can be modulated to the spread spectrum and can be used for the watermarking algorithm. The proposed algorithm assigns the different spread spectrum sequences to the individual users respectively. In the case that the assigned code sequences are orthogonal, we can identify the watermark information of the individual user from an audio content. The algorithm used the Walsh code as an orthogonal code. The watermark information is rearranged to the 1D sequence from 2D barcode and modulated by the Walsh code. The modulated watermark information is embedded into the DCT (discrete cosine transform) domain of the original audio content. For the performance evaluation, I used 3 audio samples, "Amazing Grace", "Oh! Carol" and "Take me home country roads", The attacks for the robustness test were MP3 compression, echo attack, and sub woofer boost. The MP3 compression was performed by a tool of Cool Edit Pro 2.0. The specification of MP3 was CBR(Constant Bit Rate) 128kbps, 44,100Hz, and stereo. The echo attack had the echo with initial volume 70%, decay 75%, and delay 100msec. The sub woofer boost attack was a modification attack of low frequency part in the Fourier coefficients. The test results showed the proposed algorithm is robust to the attacks. In the MP3 attack, the strength of the watermark information is not affected, and then the watermark can be detected from all of the sample audios. In the sub woofer boost attack, the watermark was detected when the strength is 0.3. Also, in the case of echo attack, the watermark can be identified if the strength is greater and equal than 0.5.

• Journal of Korean Philosophical Society
• /
• v.145
• /
• pp.167-194
• /
• 2018

According to the result of 2017 youth statistics, the first rank of the death cause of Korean youth is suicide for nine years. The recent study on factors affecting juvenile suicide presents: family factors; character and psychological factors; mental disease factors; suicide-triggering factors; school factors; and protection factors; and so on. What is required to the youth who are vulnerable to the confusion of identity and the adjustment of emotion or impulse is not only drug treatment or mental therapy but also the support of family or society where adolescents are encouraged to be introspective and form their identity in a healthy approach in the diverse humanistic philosophical dimension. This study is going to pay attention to the aesthetic existence of Kierkegaard who provided the foundation of human existential identity centered on three stages of existence. For this purpose, we attempt to search for the philosophical basis for the understanding of juvenile identity centered on the analysis of Kierkegaard's Either / Or Volume I (Entweder - Oder Teil I). Especially, we are going to attempt the understanding of aesthetics of youth through the analysis of three stages of desire (Begierde) suggested in Chapter 2 of this book. Herewith he suggests aesthetic existence through 'desire', and aesthetic existence as the desire again through three stages of 'dreaming ($tr{\ddot{a}}umend$)' desire, 'searching (suchend)' desire, and 'desiring (begehrend)' desire. Based on this analysis of three stages, we plan to graft the roots of sociological factors presented as the cause of youth's suicide onto the analysis of existential philosophy. Through this, we attempt to grope for the diagnostic and healing discourse which Kierkegaard's existential analysis can present in the formation and recognition of youth identity and disclose a factor of the emotion or the disorder of impulse adjustment as well as depression suggested as the main contributing factor of youth's suicide and search for philosophical discourse for the prevention of juvenile suicide.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.40 no.4
• /
• pp.67-80
• /
• 2022

SipWooDo (十牛圖: Painting of Ten Bulls), a Buddhist painting, is a kind of Zen Sect Buddhism painting, which is shown as a mural in many of main halls of Korean Buddhist temples. MokWooDo has been painted since Song Dynasty of China. It paints a cow, a metaphor of mind and a shepherd boy who controls the cow. It comes also with many other types of works such as poetry called GyeSong, HwaWoonSi and etc. That is, it appeared as a pan-cultural phenomenon beyond ideology and nation not limited to Chinese Buddhist ideology of an era. This study, therefore, selects MokWooDo chants that represent Confucianism, Buddhism and Taoism to compare the writing purposes, mind discipline methods and ultimate goals of such chant literatures in order to integrate and comprehend the ideologies of such three schools in the ideologically cultural aspect, which was not fully dealt with in the existing studies. In particular, the study results are: First, the SipWooDo of Buddhist School is classified generally into Bo Myoung's MokWooDo and Kwak Ahm's SimWooDo (尋牛圖: Painting of Searching out a Bull). Zen Sect Buddhism goes toward nirvana through enlightenment. Both MokWooDo and SimWooDo of Buddhist School are the discipline method of JeomSu (漸修: Discipline by Steps). They were made for SuSimJeungDo (修心證道: Enlightenment of Truth by Mind Discipline), which appears different in HwaJe (畫題: Titles on Painting) and GyeSong (偈頌: Poetry Type of Buddhist Chant) between Zen Sect Buddhism and Doctrine Study Based Buddhism, which are different from each other in viewpoints. Second, Bo Myoung's MokWooDo introduces the discipline processes from MiMok (未牧: Before Tamed) to JinGongMyoYu (眞空妙有: True Vacancy is not Separately Existing) of SsangMin (雙泯: the Level where Only Core Image Appears with Every Other Thing Faded out) that lie on the method called BangHalGiYong (棒喝機用: a Way of Using Rod to Scold). On the other side, however, it puts its ultimate goal onto the way to overcome even such core image of SsangMin. Third, Kwak Ahm's SimWooDo shows the discipline processes of JeomSu from SimWoo (尋牛: Searching out a Bull) to IpJeonSuSu (入鄽垂手: Entering into a Place to Exhibit Tools). That is, it puts its ultimate goal onto HwaGwangDongJin (和光同塵: Harmonized with Others not Showing your own Wisdom) where you are going together with ordinary people by going up to the level of 'SangGuBori (上求菩提: Discipline to Go Up to Gain Truth) and HaHwaJungSaeng (下化衆生: Discipline to Go Down to Be with Ordinary People)' through SaGyoIpSeon (捨敎入禪: Entering into Zen Sect Buddhism after Completing a Certain Volume of Doctrine Study), which are working for leading the ordinary people of all to finding out their Buddhist Nature. Fourth, Shimiz Shunryu (清水春流)'s painting YuGaSipMaDo (儒家十馬圖: Painting of Ten Horses of Confucian School) borrowed Bo Myoung's MokWooDo. That is, it borrowed the terms and pictures of Buddhist School. However, it features 'WonBulIpYu (援佛入儒: Enlightenment of Buddhist Nature by Confucianism)', which is based on the process of becoming a greatly wise person through Confucian study to go back to the original good nature. From here, it puts its goal onto becoming a greatly wise person, GunJa who is completely harmonized with truth, through the study of HamYang (涵養: Mind Discipline by Widening Learning and Intelligence) that controls outside mind to make the mind peaceful. Its ultimate goal is in accord with "SangCheonJiJae, MuSeongMuChee (上天之載, 無聲無臭: Heaven Exists in the Sky Upward; It is Difficult to Get the Truth of Nature, which has neither sound nor smell)' words from Zhōngyōng. Fifth, WonMyeongNhoYin (圓明老人)'s painting SangSeungSuJinSamYo (上乘修真三要: Painting of Three Essential Things to Discipline toward Truth) borrowed Bo Myoung's MokWooDo while it consists of totally 13 sheets of picture to preach the painter's will and preference. That is, it features 'WonBulIpDo (援佛入道: Following Buddha to Enter into Truth)' to preach the painter's doctrine of Taoism by borrowing the pictures and poetry type chants of Buddhist School. Taoism aims to become a miraculously powerful Taoist hermit who never dies by Taoist healthcare methods. Therefore, Taoists take the mind discipline called BanHwanSimSeong (返還心性: Returning Back to Original Mind Nature), which makes Taoists go ultimately toward JaGeumSeon (紫金仙) that is the original origin by changing into a saint body that is newly conceived with the vital force of TaeGeuk abandoning the existing mind and body fully. This is a unique feature of Taoism, which puts its ultimate goal onto the way of BeopShinCheongJeong (法身淸淨: Pure and Clean Nature of Buddha) that is in accord with JiDoHoiHong (至道恢弘: Getting to Wide and Big Truth).

• Journal of Intelligence and Information Systems
• /
• v.20 no.2
• /
• pp.109-122
• /
• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.197-218
• /
• 2019

In addition to economic growth and national income increase, China is also experiencing rapid growth in consumption of cosmetics. About 67% of the total trade volume of Chinese cosmetics is made by e-commerce and especially K-Beauty products, which are Korean cosmetics are very popular. According to previous studies, 80% of consumer goods such as cosmetics are affected by the word of mouth information, searching the product information before purchase. Mostly, consumers acquire information related to cosmetics through comments made by other consumers on SNS such as SINA Weibo and Wechat, and recently they also use information about beauty related video channels. Most of the previous online word-of-mouth researches were mainly focused on media itself such as Facebook, Twitter, and blogs. However, the informational characteristics and the expression forms are also diverse. Typical types are text, picture, and video. This study focused on these types. We analyze the unstructured data of SINA Weibo, the SNS representative platform of China, and Meipai, the video platform, and analyze the impact of K-Beauty brand sales by dividing online word-of-mouth information with quantity and direction information. We analyzed about 330,000 data from Meipai, and 110,000 data from SINA Weibo and analyzed the basic properties of cosmetics. As a result of analysis, the amount of online word-of-mouth information has a positive effect on the sales of cosmetics irrespective of the type of media. However, the online videos showed higher impacts than the pictures and texts. Therefore, it is more effective for companies to carry out advertising and promotional activities in parallel with the existing SNS as well as video related information. It is understood that it is important to generate the frequency of exposure irrespective of media type. The positiveness of the video media was significant but the positiveness of the picture and text media was not significant. Due to the nature of information types, the amount of information in video media is more than that in text-oriented media, and video-related channels are emerging all over the world. In particular, China has made a number of video platforms in recent years and has enjoyed popularity among teenagers and thirties. As a result, existing SNS users are being dispersed to video media. We also analyzed the effect of online type of information on the online cosmetics sales by dividing the product type of cosmetics into basic cosmetics and color cosmetics. As a result, basic cosmetics had a positive effect on the sales according to the number of online videos and it was affected by the negative information of the videos. In the case of basic cosmetics, effects or characteristics do not appear immediately like color cosmetics, so information such as changes after use is often transmitted over a period of time. Therefore, it is important for companies to move more quickly to issues generated from video media. Color cosmetics are largely influenced by negative oral statements and sensitive to picture and text-oriented media. Information such as picture and text has the advantage and disadvantage that the process of making it can be made easier than video. Therefore, complaints and opinions are generally expressed in SNS quickly and immediately. Finally, we analyzed how product diversity affects sales according to online word of mouth information type. As a result of the analysis, it can be confirmed that when a variety of products are introduced in a video channel, they have a positive effect on online cosmetics sales. The significance of this study in the theoretical aspect is that, as in the previous studies, online sales have basically proved that K-Beauty cosmetics are also influenced by word-of-mouth. However this study focused on media types and both media have a positive impact on sales, as in previous studies, but it has been proven that video is more informative and influencing than text, depending on media abundance. In addition, according to the existing research on information direction, it is said that the negative influence has more influence, but in the basic study, the correlation is not significant, but the effect of negation in the case of color cosmetics is large. In the case of temporal fashion products such as color cosmetics, fast oral effect is influenced. In practical terms, it is expected that it will be helpful to use advertising strategies on the sales and advertising strategy of K-Beauty cosmetics in China by distinguishing basic and color cosmetics. In addition, it can be said that it recognized the importance of a video advertising strategy such as YouTube and one-person media. The results of this study can be used as basic data for analyzing the big data in understanding the Chinese cosmetics market and establishing appropriate strategies and marketing utilization of related companies.

• Journal of Intelligence and Information Systems
• /
• v.24 no.3
• /
• pp.67-88
• /
• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.