• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.73-82
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• 2021

Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.168-182
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• 2019

The objectives of this study were to examine the production processes and methods of "Forest Type Map Actualization Production (Database (DB) Construction Work Manual)" (Work Manual) identify issues associated with the production processes and methods, and suggest solutions for them by applying evaluation items to a 1:5k digital forest type map. The evaluation items applied to a forest type map were divided into zoning and attributes, and the issues associated with the production processes and methods of Work Manual were derived through analyzing the characteristics of the stand structure and fragmentation by administrative districts. Korea is divided into five divisions, where one is set as the area changed naturally and the other four areas set as the area changed artificially. The area changed naturally has been updated every five years, and those changed artificially have been updated annually. The fragmentation of South Korea was analyzed in order to examine the consistency of the DB established for each region. The results showed that, in South Korea, the number of patches increased and the mean patch size decreased. As a result, the degree of fragmentation and the complexity of shapes increased. The degree of fragmentation and the complexity of shapes decreased in four regions out of 17 regions (metropolitan cities and provinces). The results indicated that there were spatial variations. The "Forest Classification" defines the minimum area of a zoning as 0.1ha. This study examined the criteria for the minimum area of a zoning by estimating the divided object (polygon unit) in a forest type map. The results of this study revealed that approximately 26% of objects were smaller than the minimum area of a zoning. The results implied that it would be necessary to establish the definition and the regeneration interval of "Areas Changed Artificially and Areas Changed Naturally", and improve the standard for the minimum area of a zoning. Among the attributes of Work Manual, "Species Change" item classifies terrain features into 52 types, and 43 types of them belong to stocking land. This study examined distribution ratios by extracting species information from the forest type map. It was found that each of 23 species, approximately 53% of species, occupied less than 0.1% of Forested land. The top three species were pine and other species. Although undergrowth on unstocked forest land are classified in the terrain feature system, their definition and classification criteria are not established in the "Forest Classification" item. Therefore, it will be needed to reestablish the terrain feature system and set the definitions of undergrowth.

• Journal of East-West Nursing Research
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• v.1 no.1
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• pp.50-71
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• 1997

The intention of this study is to apprehend the con. tents and methods of herb remedies that are commonly conducted when there are health-problem cases of ENT, eyes, teeth and skin. Methods of this study are divided into two stages : 1) For a period of six months from December 1994 to June 1995, some 40 persons who are believed to be well versed with herb remedies have been randomly chosen, and we made a survey on herb remedies by symptoms: and 2) we have endeavored to make their grounds evident through the studies on literatures with the focus on the basic data collected. Their results are as follows: 1) When one feels a pain in ears, such herb remedies are employed as pouring the vapor into ears, which is made by steaming Alaska pollack, or as applying or wiping with the juices of radish or the ginkgo, or' alum. Applying the radish juice is effective for sterilization and fever removal: and applying the ginkgo juice is effective for cleanliness. But, plastering alum, sesame oil or castor oil, or pouring the vapor of Alaska pollack into ears are perhaps effective but do not have any pharmacologic grounds. 2) When one bleeds at the nose, such kinds of herb remedies are applied as stimulating nose or head with cold water, pressing nose or ridge of nose, or filling up nares with mashed mugworts. In addition, they have utilized garlic or leeks. Such methods as stimulating with cold water or just pressing nose and ridge of nose is based on reasonable grounds, i.e. vasoconstriction and vascular compression ; and applying mashed garlic on the sole of foot is good for the circulation of Qui ; and the use of mugworts and leeks is based upon the pharmacological function of hemostasis. 3) When one feels a sore throat such kinds of herb remedies are employed as gargling or rinsing throat with brine, drinking hot gruel or water, or drinking the juice of mugwort, radish, ginger or Chinese quince. Gargling with brine or drinking the juice of mugwort, radish or ginger is based upon the pharmacological function of pain alleviation, fever removal, and detoxication. 4) When a boil is formed in mouth, such herb remedies are applied as spreading honey, brine or alum water, and taking gall nut, Chinese matrimony vine, lotus root, etc, for drugs. Spreading honey, brine or water that is made by infusing gallnut, Chinese matrimony vine, lotus root is based upon such functions as hematosis, astriction, antibacterial, and antiphlogistic, Alum, eggplant and licorice are said to be effective, but their pharmacological effects have no grounds. 5) When one has conjunctivitis such herb remedies are commonly applied as irrigation with brine and dropping breast milk in eyes. Moreover, such other drugs are used as plantain. shepherd's purse, and purslane, etc. The use of brine, breast milk, plantain, shepherd's purse and purslane is based upon such functions as sterilization, antiphlogistic, disinfection and pain relieving. Eriocaulon sieboldianum, bean stem, bean pod and narcissus leaves are said to be effective, but their pharmacological action have no basis. When one has a stye, such herb remedies are applied as extracting eyelashes, stimulating by a massage of middle finger, third finger or big toe, as well as sear ing with a heated bamboo comb that is fine-toothed. Other than these, plantain and nightshade's nuts are used as drugs for it. Extracting eyelashes corresponds with exclusing suppurative node and draining the stye of pus ; and the use of plantain is based upon disinfection: and nightshade's nuts are said to be effective, however, their pharmacological action has no grounds. 6) For a treatment of toothache, such herb remedies are commonly employed as rinsing mouth with brine and holding cold water or gasoline in the mouth ; and as the drugs that are believed to be effective have been Welsh onion, ginger and castor-oil, plant, etc. The use of Welsh onion is based upon pain killing, antiinflammatory actions, and the use of ginger is based upon detoxication and disinfection ; and seeds of castor-oil plants are said to be effective, but they have no pharmacological basis. 7) When one has hives, such herb remedies are commonly applied as rubbing burned straw in affected parts, exposing to its smoke, rubbing with salt, sweeping down with a broom, and spreading and drinking boiled water of trifoliate orange. The use of cassia tora seeds, walnut, aloe and radish is said to be effective. The use of cassia tor a seeds has the functions of intestinal order, anti-paralysis, etc. The use of walnut has resulted in an increase of blood by invigorating spirits ; and the use of aloe is based upon disinfection, antibiotic, anti-salt, antihistamine and detoxication action. But, the effects of radish juice and straw's smoke have no pharmacological grounds. 8) When one gets a boil, such herb remedies are commonly used as applying a plaster, paste of flour mixed with yolk, soy sauce or honey, as well as spreading pounded elm tree. Other remedies that have been said to be effective are ; heating with mugwort, brine, wild rocambole, aloe, onion, squid's bone, etc. The use of mugwort is based upon pain killing, astringent antiinflammatory and tranquility. Wild rocambole is based upon the generation and maintenance functions of cell-joining textures ; elm tree upon antiphlogistic ; aloe upon fever removal and antiphlogistic ; onion on pain killing, fever removal, antiphlogistic and tranquility ; squid's bone on astriction: and brine or vinegar on sterilization. Pine resin and gardenia seed are said to be effective, but they have no pharmacological basis. 9) When one cuts his skin, such herb remedies are commonly employed as spreading mugwort's juice or squid's bone powder, or pressing the wounds. In addition, kalopanax, onion and fine soil are employed. The use of mugwort, kalopanax and squid's bone is based upon such functions as hemostasis, sedation, pain killing, antibacterial ; and fine soil is said to be effective, but it has no pharmacological basis. 10) When one suffers from whitlow, such herb remedies are commonly utilized as heating with boiled soy sauce, spreading soybean paste, or dipping into eggs, etc. Other drugs that have been employed are onion root, brine, eggplant, potato, loach, etc. The use of onion is based upon pain killing and antiphlogistic functions ; and that of brine upon antiphlogistic function. The use of soy sauce or soybean paste, fomentation, eggplant, potato and loach is said to be effective, but it has no pharmacblogic ground. 11) For the treatment of frostbite, such herb remedies are commonly used as dipping the affected part into frozen soybean sack, using boiled water of eggplant stem, garlic caulis, onion, hot pepper, caulis. Onion is based upon antiphlogistic and tranquility actions garlic upon disintection, metabolic exacerbation, tonic and aphrodisiac actions and the use of eggplant and hot pepper is based upon help blood circulation, dissolution and excretion of waste matters in vein. 12) For the treatment of burn, such herb remedies or drugs are commonly used as cleansing with Korean gin, spreading eggs, cleansing with cold water and soap water ; and as brine, cactus, moss, soybean paste, oil, etc. The cleansing with Korean gin, cold water, soap water, brine, vinegar is based upon cleaning and sterilizing functions ; and the use of cucumber is based upon nu. trition provision, and strengthening of resisting power by adjustment of metabolism. The use of potato, cactus, moss, oil and eggs is said to be effective, but their phamacological functions are not clarified. In view of the above results, we can realize that the drugs that have been employed in herb remedies are quite diverse. However, in regard to majority of herb remedies that have been employed by symptoms, the pharmacological functions of their drugs have not been clarified, and they are merely known as effective. Furthermore, they have not been recorded in the literature as yet ; and we confirm that there have been many herb remedies that were executed without the proper knowlege of their effects. It is now our view that the results of this survey may be utilized for consulting data in regard to the use of herb remedies.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.111-125
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• 2011

Clustering is a process of grouping similar or relevant documents into a cluster and assigning a meaningful concept to the cluster. By this process, clustering facilitates fast and correct search for the relevant documents by narrowing down the range of searching only to the collection of documents belonging to related clusters. For effective clustering, techniques are required for identifying similar documents and grouping them into a cluster, and discovering a concept that is most relevant to the cluster. One of the problems often appearing in this context is the detection of a complex concept that overlaps with several simple concepts at the same hierarchical level. Previous clustering methods were unable to identify and represent a complex concept that belongs to several different clusters at the same level in the concept hierarchy, and also could not validate the semantic hierarchical relationship between a complex concept and each of simple concepts. In order to solve these problems, this paper proposes a new clustering method that identifies and represents complex concepts efficiently. We developed the Hierarchical Overlapping Clustering (HOC) algorithm that modified the traditional Agglomerative Hierarchical Clustering algorithm to allow overlapped clusters at the same level in the concept hierarchy. The HOC algorithm represents the clustering result not by a tree but by a lattice to detect complex concepts. We developed a system that employs the HOC algorithm to carry out the goal of complex concept detection. This system operates in three phases; 1) the preprocessing of documents, 2) the clustering using the HOC algorithm, and 3) the validation of semantic hierarchical relationships among the concepts in the lattice obtained as a result of clustering. The preprocessing phase represents the documents as x-y coordinate values in a 2-dimensional space by considering the weights of terms appearing in the documents. First, it goes through some refinement process by applying stopwords removal and stemming to extract index terms. Then, each index term is assigned a TF-IDF weight value and the x-y coordinate value for each document is determined by combining the TF-IDF values of the terms in it. The clustering phase uses the HOC algorithm in which the similarity between the documents is calculated by applying the Euclidean distance method. Initially, a cluster is generated for each document by grouping those documents that are closest to it. Then, the distance between any two clusters is measured, grouping the closest clusters as a new cluster. This process is repeated until the root cluster is generated. In the validation phase, the feature selection method is applied to validate the appropriateness of the cluster concepts built by the HOC algorithm to see if they have meaningful hierarchical relationships. Feature selection is a method of extracting key features from a document by identifying and assigning weight values to important and representative terms in the document. In order to correctly select key features, a method is needed to determine how each term contributes to the class of the document. Among several methods achieving this goal, this paper adopted the $x^2$�� statistics, which measures the dependency degree of a term t to a class c, and represents the relationship between t and c by a numerical value. To demonstrate the effectiveness of the HOC algorithm, a series of performance evaluation is carried out by using a well-known Reuter-21578 news collection. The result of performance evaluation showed that the HOC algorithm greatly contributes to detecting and producing complex concepts by generating the concept hierarchy in a lattice structure.

• The Korean Journal of Nuclear Medicine
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• v.33 no.3
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• pp.316-326
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• 1999

Purpose: We evaluated the feasibility of extracting pure left ventricular blood pool and myocardial time-activity curves (TACs) and of generating factor images from human dynamic N-13 ammonia PET using factor analysis. The myocardial blood flow (MBF) estimates obtained with factor analysis were compared with those obtained with the user drawn region-of-interest (ROI) method. Materials and Methods: Stress and rest N-13 ammonia cardiac PET imaging was acquired for 23 min in 5 patients with coronary artery disease using GE Advance tomograph. Factor analysis generated physiological TACs and factor images using the normalized TACs from each dixel. Four steps were involved in this algorithm: (a) data preprocessing; (b) principal component analysis; (c) oblique rotation with positivity constraints; (d) factor image computation. Area under curves and MBF estimated using the two compartment N-13 ammonia model were used to validate the accuracy of the factor analysis generated physiological TACs. The MBF estimated by factor analysis was compared to the values estimated by using the ROI method. Results: MBF values obtained by factor analysis were linearly correlated with MBF obtained by the ROI method (slope = 0.84, r = 0.91), Left ventricular blood pool TACs obtained by the two methods agreed well (Area under curve ratio: 1.02 ($0{\sim}1min$), 0.98 ($0{\sim}2min$), 0.86 ($1{\sim}2min$)). Conclusion: The results of this study demonstrates that MBF can be measured accurately and noninvasively with dynamic N-13 ammonia PET imaging and factor analysis. This method is simple and accurate, and can measure MBF without blood sampling, ROI definition or spillover correction.

• Journal of the Korean Applied Science and Technology
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• v.34 no.3
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• pp.666-672
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• 2017

Hemp [Cannabis sativa L.] has been cultivated as a fiber crop for long history, but it was a good oil crop because its seed contain plenty of lipid which is high ratio of unsaturated fatty acid. Hemp seed oil was extracted with a extruding method in many countries including Europe. The color of oil extracted with extruding method is dark green which could be difficult to attract consumer's interest in Korea because of insufficient information about hemp seed oil. This study was conducted to know correct information about hemp seed oils which were extracted with pressuring and extruding methods. In extruding method, seeds were crushed during the extracting process and discharged oil cake in shape of thin ribbon, but maintained seed shape although the seed were slightly flatted in pressuring method. Oil yield were higher in the extruding method in comparison with pressuring method. The oil have lower degree of lightness but higher degree of greenness and yellowness in the extruding method in comparison with pressuring method because of higher content of chlorophyll A, B and carotenoid. In fatty acid composition, the ratio of palmitic acid, stearic acid, oleic acid and ${\gamma}$-linolenic acid were higher but linoleic acid and ${\alpha}$-linolenic acid were lower in the extruding method in comparison with pressuring method. The content of total tocopherol and ${\gamma}$-tocopherol were lower in the extruding method in comparison with pressuring method.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.113-129
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• 2015

Location branding is a very important income making activity, by giving special meanings to a specific location while producing identity and communal value which are based around the understanding of a place's location branding concept methodology. Many other areas, such as marketing, architecture, and city construction, exert an influence creating an impressive brand image. A place brand which shows great recognition to both native people of S. Korea and foreigners creates significant economic effects. There has been research on creating a strategically and detailed place brand image, and the representative research has been carried out by Anholt who surveyed two million people from 50 different countries. However, the investigation, including survey research, required a great deal of effort from the workforce and required significant expense. As a result, there is a need to make more affordable, objective and effective research methods. The purpose of this paper is to find a way to measure the intensity of the image of the brand objective and at a low cost through text mining purposes. The proposed method extracts the keyword and the factors constructing the location brand image from the related web documents. In this way, we can measure the brand image intensity of the specific location. The performance of the proposed methodology was verified through comparison with Anholt's 50 city image consistency index ranking around the world. Four methods are applied to the test. First, RNADOM method artificially ranks the cities included in the experiment. HUMAN method firstly makes a questionnaire and selects 9 volunteers who are well acquainted with brand management and at the same time cities to evaluate. Then they are requested to rank the cities and compared with the Anholt's evaluation results. TM method applies the proposed method to evaluate the cities with all evaluation criteria. TM-LEARN, which is the extended method of TM, selects significant evaluation items from the items in every criterion. Then the method evaluates the cities with all selected evaluation criteria. RMSE is used to as a metric to compare the evaluation results. Experimental results suggested by this paper's methodology are as follows: Firstly, compared to the evaluation method that targets ordinary people, this method appeared to be more accurate. Secondly, compared to the traditional survey method, the time and the cost are much less because in this research we used automated means. Thirdly, this proposed methodology is very timely because it can be evaluated from time to time. Fourthly, compared to Anholt's method which evaluated only for an already specified city, this proposed methodology is applicable to any location. Finally, this proposed methodology has a relatively high objectivity because our research was conducted based on open source data. As a result, our city image evaluation text mining approach has found validity in terms of accuracy, cost-effectiveness, timeliness, scalability, and reliability. The proposed method provides managers with clear guidelines regarding brand management in public and private sectors. As public sectors such as local officers, the proposed method could be used to formulate strategies and enhance the image of their places in an efficient manner. Rather than conducting heavy questionnaires, the local officers could monitor the current place image very shortly a priori, than may make decisions to go over the formal place image test only if the evaluation results from the proposed method are not ordinary no matter what the results indicate opportunity or threat to the place. Moreover, with co-using the morphological analysis, extracting meaningful facets of place brand from text, sentiment analysis and more with the proposed method, marketing strategy planners or civil engineering professionals may obtain deeper and more abundant insights for better place rand images. In the future, a prototype system will be implemented to show the feasibility of the idea proposed in this paper.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.77-83
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• 2015

Frequent pattern mining, which is one of the major areas actively studied in data mining, is a method for extracting useful pattern information hidden from large data sets or databases. Moreover, frequent pattern mining approaches have been actively employed in a variety of application fields because the results obtained from them can allow us to analyze various, important characteristics within databases more easily and automatically. However, traditional frequent pattern mining methods, which simply extract all of the possible frequent patterns such that each of their support values is not smaller than a user-given minimum support threshold, have the following problems. First, traditional approaches have to generate a numerous number of patterns according to the features of a given database and the degree of threshold settings, and the number can also increase in geometrical progression. In addition, such works also cause waste of runtime and memory resources. Furthermore, the pattern results excessively generated from the methods also lead to troubles of pattern analysis for the mining results. In order to solve such issues of previous traditional frequent pattern mining approaches, the concept of representative pattern mining and its various related works have been proposed. In contrast to the traditional ones that find all the possible frequent patterns from databases, representative pattern mining approaches selectively extract a smaller number of patterns that represent general frequent patterns. In this paper, we describe details and characteristics of pattern condensing techniques that consider the maximality or closure property of generated frequent patterns, and conduct comparison and analysis for the techniques. Given a frequent pattern, satisfying the maximality for the pattern signifies that all of the possible super sets of the pattern must have smaller support values than a user-specific minimum support threshold; meanwhile, satisfying the closure property for the pattern means that there is no superset of which the support is equal to that of the pattern with respect to all the possible super sets. By mining maximal frequent patterns or closed frequent ones, we can achieve effective pattern compression and also perform mining operations with much smaller time and space resources. In addition, compressed patterns can be converted into the original frequent pattern forms again if necessary; especially, the closed frequent pattern notation has the ability to convert representative patterns into the original ones again without any information loss. That is, we can obtain a complete set of original frequent patterns from closed frequent ones. Although the maximal frequent pattern notation does not guarantee a complete recovery rate in the process of pattern conversion, it has an advantage that can extract a smaller number of representative patterns more quickly compared to the closed frequent pattern notation. In this paper, we show the performance results and characteristics of the aforementioned techniques in terms of pattern generation, runtime, and memory usage by conducting performance evaluation with respect to various real data sets collected from the real world. For more exact comparison, we also employ the algorithms implementing these techniques on the same platform and Implementation level.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.149-162
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• 2014

Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.