• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.23-43
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• 2016

As a result of the growth of Internet data and the rapid development of Internet technology, "big data" analysis has gained prominence as a major approach for evaluating and mining enormous data for various purposes. Especially, in recent years, people tend to share their experiences related to their leisure activities while also reviewing others' inputs concerning their activities. Therefore, by referring to others' leisure activity-related experiences, they are able to gather information that might guarantee them better leisure activities in the future. This phenomenon has appeared throughout many aspects of leisure activities such as movies, traveling, accommodation, and dining. Apart from blogs and social networking sites, many other websites provide a wealth of information related to leisure activities. Most of these websites provide information of each product in various formats depending on different purposes and perspectives. Generally, most of the websites provide the average ratings and detailed reviews of users who actually used products/services, and these ratings and reviews can actually support the decision of potential customers in purchasing the same products/services. However, the existing websites offering information on leisure activities only provide the rating and review based on one stage of a set of evaluation criteria. Therefore, to identify the main issue for each evaluation criterion as well as the characteristics of specific elements comprising each criterion, users have to read a large number of reviews. In particular, as most of the users search for the characteristics of the detailed elements for one or more specific evaluation criteria based on their priorities, they must spend a great deal of time and effort to obtain the desired information by reading more reviews and understanding the contents of such reviews. Although some websites break down the evaluation criteria and direct the user to input their reviews according to different levels of criteria, there exist excessive amounts of input sections that make the whole process inconvenient for the users. Further, problems may arise if a user does not follow the instructions for the input sections or fill in the wrong input sections. Finally, treating the evaluation criteria breakdown as a realistic alternative is difficult, because identifying all the detailed criteria for each evaluation criterion is a challenging task. For example, if a review about a certain hotel has been written, people tend to only write one-stage reviews for various components such as accessibility, rooms, services, or food. These might be the reviews for most frequently asked questions, such as distance between the nearest subway station or condition of the bathroom, but they still lack detailed information for these questions. In addition, in case a breakdown of the evaluation criteria was provided along with various input sections, the user might only fill in the evaluation criterion for accessibility or fill in the wrong information such as information regarding rooms in the evaluation criteria for accessibility. Thus, the reliability of the segmented review will be greatly reduced. In this study, we propose an approach to overcome the limitations of the existing leisure activity information websites, namely, (1) the reliability of reviews for each evaluation criteria and (2) the difficulty of identifying the detailed contents that make up the evaluation criteria. In our proposed methodology, we first identify the review content and construct the lexicon for each evaluation criterion by using the terms that are frequently used for each criterion. Next, the sentences in the review documents containing the terms in the constructed lexicon are decomposed into review units, which are then reconstructed by using the evaluation criteria. Finally, the issues of the constructed review units by evaluation criteria are derived and the summary results are provided. Apart from the derived issues, the review units are also provided. Therefore, this approach aims to help users save on time and effort, because they will only be reading the relevant information they need for each evaluation criterion rather than go through the entire text of review. Our proposed methodology is based on the topic modeling, which is being actively used in text analysis. The review is decomposed into sentence units rather than considering the whole review as a document unit. After being decomposed into individual review units, the review units are reorganized according to each evaluation criterion and then used in the subsequent analysis. This work largely differs from the existing topic modeling-based studies. In this paper, we collected 423 reviews from hotel information websites and decomposed these reviews into 4,860 review units. We then reorganized the review units according to six different evaluation criteria. By applying these review units in our methodology, the analysis results can be introduced, and the utility of proposed methodology can be demonstrated.

• The Journal of Korean Society for Radiation Therapy
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• v.28 no.1
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• pp.35-46
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• 2016

Purpose : BoS(Base of Skull) Frame, the fixation tool which is used for the proton of brain cancer increases the lateral penumbra by increasing the airgap (the distance between patient and beam jet), due to the collision of the beam of the posterior oblique direction. Thus, we manufactured the fixation tool per se for improving the limits of BoS frame, and we'd like to evaluate the utility of the manufactured fixation tool throughout this study. Materials and Methods : We've selected the 3 patients of brain cancer who have received the proton therapy from our hospital, and also selected the 6 beam angles; for this, we've selected the beam angle of the posterior oblique direction. We' ve measured the planned BoS frame and the distance of Snout for each beam which are planned for the treatment of the patient using the BoS frame. After this, we've proceeded with the set-up that is above the location which was recommended by the manufacturer of the BoS frame, at the same beam angle of the same patient, by using our in-house Bos frame fixation tool. The set-up was above 21 cm toward the superior direction, compared to the situation when the BoS frame was only used with the basic couch. After that, we've stacked the snout to the BoS frame as much as possible, and measured the distance of snout. We've also measured the airgap, based on the gap of that snout distance; and we've proceeded the normalization based on each dose (100% of each dose), after that, we've conducted the comparative analysis of lateral penumbra. Moreover, we've established the treatment plan according to the changed airgap which has been transformed to the Raystation 5.0 proton therapy planning system, and we've conducted the comparative analysis of DVH(Dose Volume Histogram). Results : When comparing the result before using the in-house Bos frame fixation tool which was manufactured for each beam angle with the result after using the fixation tool, we could figure out that airgap than when not used in accordance with the use of the in-house Bos frame fixation tool was reduced by 5.4 cm ~ 15.4 cm, respectively angle. The reduced snout distance means the airgap. Lateral Penumbra could reduce left, right, 0.1 cm ~ 0.4 cm by an angle in accordance with decreasing the airgap while using each beam angle in-house Bos frame fixation tool. Due to the reduced lateral penumbra, Lt.eyeball, Lt.lens, Lt. hippocampus, Lt. cochlea, Rt. eyeball, Rt. lens, Rt. cochlea, Rt. hippocampus, stem that can be seen that the dose is decreased by 0 CGE ~ 4.4 CGE. Conclusion : It was possible to reduced the airgap by using our in-house Bos frame fixation tool for the proton therapy; as a result, it was possible to figure out that the lateral penumbra reduced. Moreover, it was also possible to check through the comparative analysis of the treatment plan that when we reduce the lateral penumbra, the reduction of the unnecessary irradiation for the normal tissues. Therefore, Using the posterior oblique the Brain cancer proton therapy should be preceded by decreasing the airgap, by using our in-house Bos frame fixation tool; also, the continuous efforts for reducing the airgap as much as possible for the proton therapy of other area will be necessary as well.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

• Journal of Food Hygiene and Safety
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• v.21 no.2
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• pp.100-106
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• 2006

The use of underarm and body care cosmetics with oestrogenic chemical excipients (particularly the parabens) and the hypothesized association with breast cancer incidence, particularly in women. It is noted that the type of cosmetic product is irrelevant (e.g. antiperspirant/deodorant versus body lotion, moisturizers or sprays versus creams) and attention must focus on issues of actual exposure to chemicals through continued dermal application of body care products and the endocrine/hormonal activity and toxicity of the chemicals in the formulations. To evaluate the estrogenic activities of parabens such as ethylparaben, butylparaben, propylparaben, isobutylparaben and isopropylparaben, we used recombinant yeasts containing the human estrogen receptor [Saccharomyces cerevisiae ER+LYS 8127], human breast cancer MCF-7 cell lines and human estrogen receptor ${\alpha}\;and\;{\beta}$. In E-screen assays, isopropylparaben is the most estrogenic paraben, and in ER competition assay, isobutylparaben is the most estrogenic paraben. We evaluated isopropylparaben was most active in the recombinant yeast assay, followed by propylparaben, ethylparaben, isobutylparaben and butylparaben. Results from this study demonstrate that parabens are observed in human endocrine system. Therefore, we have shown that the parabens is induced the estrogenic activities similar to $17{\beta}$-estradiol and Bisphenol-A.

• Journal of Korean Society of Forest Science
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• v.51 no.1
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• pp.56-65
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• 1981

The training of forest ranger level and forest worker level to push the sound forest management and to increase the employment effects in forestry will be done without delay as soon as possible. So several opinions to be considered are here discussed. 1. The ranger level will be at first completely trained with the technics developed and modernized, to process really the sound forest management based on the concept of ecological and economical technic. 2. The organization of vocational training and it's systematical training method will be newly adopted to increase the labour efficiency in forestry. The case of fulltime worker level should be more intensively trained and part-time worker or forest famer level should be trained by the forest ranger and skilled worker with visiting circularly their working place. And the daily employed workers and village people for working should be done by the skilled workers. 3. The training subjects for them at the beginning step will be exploited by the instructors and concerned experts with studying their current conditions. Their practical training is more reasonable to do in the practically managing forest and to carry out under the responsible of leader of this forest. 4. The instructors included rangers of training forest will get specially certain intensive training through the aids of outside experts or through the group instruction with them. 5. The training fields and their reasons to be learned by them are discussed in this paper from the basic knowledge to the skill technics. 6. In oder to systematize and mordernize more rapidly our forest technics that need for training them and also applying directly in the forest management, a total effort of certain type by scientists and technicians scattered individually all over the country is now earnestly demanded to synthesize their knowledge, technic and experience. So to do like this, the establishment of certain organization through which can do their total efforts together will be considered and assisted by the concerned authority. 7. For better lieving of full-time workers, the whole-round year working amount have to be supplied though the work technic-and working plan development. And under the conditions that the timber harvesting work is still not so enough and it has a bad climatic season, the in-side working system and side - job aids will be developed for their sound lieving. 8. The organization of labour management will be soon introduced in the concerning administrativ authority to solve the forest labour problems and to increase the employing effects in forestry in future. 9. The supply programm of improved and trained tools and maschines for forest work is also considered to use by the trained persons. If not to do so, the training results will return to the original condition and will get nothing any more.

• Journal of Korean Society of Forest Science
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• v.77 no.4
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• pp.429-444
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• 1988

Considering the recent trent toward the development of multiple-use of forest trees, investigations for comprehensive information on these young stands of Hinoki cypress are necessary for rational forest management. From this point of view, 83 sample trees were selected and cut down from 23-ear old stands of Hinoki cypress at Changsung-gun, Chonnam-do. Various stem growth factors of felled trees were measured and canonical correlaton analysis, principal component analysis and factor analysis were applied to investigate the stem growth characteristics, relationships among stem growth factors, and to get potential information and comprehensive information. The results are as follows ; Canonical correlation coefficient between stem volume and quality growth factor was 0.9877. Coefficient of canonical variates showed that DBH among diameter growth factors and height among height growth factors had important effects on stem volume. From the analysis of relationship between stem-volume and canonical variates, which were linearly combined DBH with height as one set, DBH had greater influence on volume growth than height. The 1st-2nd principal components here adopted to fit the effective value of 85% from the pincipal component analysis for 12 stem growth factors. The result showed that the 1st-2nd principal component had cumulative contribution rate of 88.10%. The 1st and the 2nd principal components were interpreted as "size factor" and "shape factor", respectively. From summed proportion of the efficient principal component fur each variate, information of variates except crown diameter, clear length and form height explained more than 87%. Two common factors were set by the eigen value obtained from SMC (squared multiple correlation) of diagonal elements of canonical matrix. There were 2 latent factors, $f_1$ and $f_2$. The former way interpreted as nature of diameter growth system. In inherent phenomenon of 12 growth factor, communalities except clear length and crown diameter had great explanatory poorer of 78.62-98.30%. Eighty three sample trees could he classified into 5 stem types as follows ; medium type within a radius of ${\pm}1$ standard deviation of factor scores, uniformity type in diameter and height growth in the 1st quadrant, slim type in the 2nd quadrant, dwarfish type in the 3rd quadrant, and fall-holed type in the 4 th quadrant.

• Korean Security Journal
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• no.36
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• pp.93-109
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• 2013

This research is mainly based on the experimental result due to seek different outcomes whena certain security motion with a paticular gear is applied in a plausible confrontational situation. For the purpose of this research an Expandable Baton, which is one of the most commonsecurity equipments, was chosen to be applied in a situation of hitting a person's head. Alsothe results will be studied in the view of Kinematic theory. To demonstrate, 10 students who were majeored in Escort Crane studies at 'H' university werechosen as testees. The participants were grouped into two-one is practiced with the 'expanadable baton use program' and the other is pre-practiced. In this report two groups abovewill be reffered as 'group A' and 'group B' for conveniency. There were a number of differences and changes between two groups. Group B took more timethan the other group did. Group A spent about 0.428sec in section 'e2' and 0.230sec in section'e3' while Group B took 0.435sec, 0.232sec in each sections.To add on, more distinctive results were out when it was more focused on physical movements. Two gropus presented considerable changes- in an 'left-right' moving displacement-Group A;$2.16{\pm}0.9cm$ (left side), $3.78{\pm}1.42cm$ (right side), total $5.94{\pm}2.03cm$. Group B; $2.97{\pm}1.01cm$ (left side),$4.56{\pm}1.57cm$ (right side), total $7.53{\pm}2.13cm$.Continuously, different outcomeswere shown between two groups in a 'back and forth' moving displacement-Group A;$32.48{\pm}3.86cm$, $35.21{\pm}4.64cm$, total $69.36{\pm}5.72$. Group B; $34.50{\pm}6.12cm$, $37.04{\pm}3.70cm$, total $71.46{\pm}7.17cm$. Furthermore, changes in an 'up and down' moving displacement were - GroupA; $5.62{\pm}2.41cm$, $4.54{\pm}1.87cm$, total $10.11{\pm}1.57cm$. Group B; $6.33{\pm}1.78cm$, $4.86{\pm}1.85cm$,total $10.68{\pm}1.81cm$. To continue, there were few modifications of degree on participants' joints, espcially on 'Wristjoint', 'Elbow joint' and 'Shoulder joint', depend on different sections -Wrist joint;Group A; e1 $114.62{\pm}7.13$, e2 $68.27{\pm}6.37$, e3 $131.64{\pm}6.27$. Group B; e1 $112.62{\pm}6.13$, e2 $66.28{\pm}7.38$, e3$137.42{\pm}4.28$ and Elbow joint ; Group A e1 $132.31{\pm}6.55$, e2 $117.92{\pm}8.42$, e3 $144.41{\pm}6.32$. Group B; e1 $133.58{\pm}8.56$, e2 $114.45{\pm}8.21$, e3 $139.89{\pm}4.38$. Lastly, degree changes ofshoulder joint were; Group A; e1 $13.55{\pm}3.85$, e2 $131.42{\pm}11.24$, e3 $78.32{\pm}6.28$. Group B; e1$9.45{\pm}1.23$, e2 $136.74{\pm}13.21$, e3 $79.75{\pm}4.24$.

• Korean Journal of Soil Science and Fertilizer
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• v.10 no.4
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• pp.225-233
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• 1978

Uptake and distribution of labelled urea, $NH{_4}^+$, and $NO{_3}^-$ by Tongil and Jinheung rice grown with each nitrogen source until ear formation stage under water culture system were as follows. 1. When the previous nitrogen source was same as one tested the uptake rate ($mg^{15}N/g$ d.w. root 2hrs, at $28^{\circ}C$ light) was great in the order of $NH_4$ >urea> $NO_3$ and higher (especially $NH_4$) in Tongil than in Jinheung. Rate limiting step (slowest) seems to be exist at R (root)${\rightarrow}$LS(leaf sheath) for urea, LS${\rightarrow}$LB(leaf blade) for $NH_4$ and M(medium)${\rightarrow}$R for $NO_3$. The fast step of translocation appeare to be at M${\rightarrow}$R for urea R${\rightarrow}$LS for $NH_4$ and LS${\rightarrow}$LB for $NO_3$. 2. The uptake rate of $NH_4$ by the urea-fed plant increased almost linearly from $18^{\circ}C$ via $28^{\circ}C$ to $38^{\circ}C$ in Tongil ($Q_{10}$=1.21 and 1.32 respectively) while no change in Jinheung ($Q_{10}$=0.99 and 1.00 respectively). It decreased by 12% in Jinheung under dark but uo change in Tongil. 3. The uptake rate of nitrogen source by different source-fed plant was great in the order of $NH_4{\rightarrow}^{15}NO_3$ $NO_3{\rightarrow}^{15}NH_4$, $urea{\rightarrow}^{15}NO_3$ and higher (especially $NH_4{\rightarrow}^{15}NO_3$) in Tongil. In the case of $urea{\rightarrow}^{15}NH_4$ it was same in $NH_4{\rightarrow}^{15}NO_3$ for Tongil and slightly lower than that in $NO_3{\rightarrow}^{15}NH_4$ for Jinheung. It was lower (especially Tongil) in $NH_4{\rightarrow}^{15}NO_3$ than in $NH_4{\rightarrow}^{15}NH_4 $ 4. The uptake rate (in $NH_4{\rightarrow}^{15}NO_3$) was higher during 15 minutes than during 2 hours and always higher in Tongil. 5. $^{15}N$ excess % and content in each part, and uptake rate of root seems to have their own significance relatling with metabolism and translocation respectively. The change of nitrogen nutritional environment and source preference of varieties were discussed in relation to field condition and efficient use of nitrogen fertilizer.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

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