• 한국지구물리탐사학회:학술대회논문집
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• 2002.09a
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• pp.139-162
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• 2002

Since weak zones or geological lineaments are likely to be eroded, weak zones may develop beneath rivers, and a careful evaluation of ground condition is important to construct structures passing through a river. Dc resistivity surveys, however, have seldomly applied to the investigation of water-covered area, possibly because of difficulties in data aquisition and interpretation. The data aquisition having high quality may be the most important factor, and is more difficult than that in land survey, due to the water layer overlying the underground structure to be imaged. Through the numerical modeling and the analysis of case histories, we studied the method of resistivity survey at the water-covered area, starting from the characteristics of measured data, via data acquisition method, to the interpretation method. We unfolded our discussion according to the installed locations of electrodes, ie., floating them on the water surface, and installing at the water bottom, since the methods of data acquisition and interpretation vary depending on the electrode location. Through this study, we could confirm that the dc resistivity method can provide the fairly reasonable subsurface images. It was also shown that installing electrodes at the water bottom can give the subsurface image with much higher resolution than floating them on the water surface. Since the data acquired at the water-covered area have much lower sensitivity to the underground structure than those at the land, and can be contaminated by the higher noise, such as streaming potential, it would be very important to select the acquisition method and electrode array being able to provide the higher signal-to-noise ratio data as well as the high resolving power. The method installing electrodes at the water bottom is suitable to the detailed survey because of much higher resolving power, whereas the method floating them, especially streamer dc resistivity survey, is to the reconnaissance survey owing of very high speed of field work.

• Journal of Korean Society of Forest Science
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• v.98 no.1
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• pp.66-81
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• 2009

From a new perspective of "humans and the culture of forming and conserving the environment", the sustainable forest management can be reformulated under the concept of "cultural sustainability". Cultural sustainability is based on the emphasis of the high contribution to sustainability of the culture of forming and conserving the environment. This study extracts the implications to cultural sustainability for the modern world by investigating a historical case of the culturo-social pine forestry in the Joseon period of Korea. In the legendary and recorded acts by the first king Taejo, Seonggye Yi, Korean red pine (Pinus densiflora) was the "Royal tree" of Joseon and also the "Sajik tree" related intimately with the Great Sajik Ritual valued as the top rank within the national ritual regime that sustained the Royal Virtue Politics in Confucian political ideology. Into the Neo-Confucian faith and royal rituals of Joseon, elements of geomancy (Feng shui), folk religion, and Buddhism had been amalgamated. The deities worshipped or revered at the Sajik shrine were Earth-god (Sa) and crop-god (Jik). And it is the Earth god and the concrete entity, Sajik tree, that contains the legacy of sylvan religion descended from the ancient times and had been incorporated into the Confucian faith and ritual regime. Korean red pine as the Royal-Sajik tree played a critical role of sustaining the religio-political justification for the rule of the Joseon's Royalty. The religio-political symbolism of Korean red pine was represented in diverse ways. The same pine was used as the timber material of shrine buildings established for the national rituals under Neo-Confucian faith by the royal court of Joseon kingdom before the modern Korea. The symbolic role of pine had also been expressed in the forms of royal tomb forests, the Imposition Forest (Bongsan) for royal coffin timber (Whangjangmok), and the creation, protection, conservation and bureaucratic management of the pine forests in the Inner-four and Outer-four mountains for the capital fortress at Seoul, where the king and his family inhabit. The religio-political management system of pine forests parallels well with the kingdom's economic forest management system, called "Pine Policy", with an array of pine cultivation forests and Prohibition Forests (Geumsan) in the earlier period, and that of Imposition Forests in the later period. The royal pine culture with the economic forest management system had influenced on the public consciousness and the common people seem to have coined Malrimgat, a pure Korean word that is interchangeable with the Chinesecharacter words of prohibition-cultivation land or forest (禁養地, 禁養林) practiced in the royal tomb forests, and Prohibition and Imposition Forests, which contained prohibition landmarks (Geumpyo) made of stone and rock on the boundaries. A culturo-social forestry, in which Sajik altar, royal tomb forests, Whangjang pine Prohibition and Imposition forests and the capital Inner-four and Outer-four mountain forests consist, was being put into practice in Joseon. In Joseon dynastry, the Neo-Confucian faith and royal rituals with geomancy, folk religion, and Buddhism incorporated has also played a critical humanistic role for the culturo-social pine forestry, the one higher in values than that of the economic pine forestry. The implications have been extracted from the historical case study on the Royal-Sajik tree and culturo-social forestry of Joseon : Cultural sustainability, in which the interaction between humans and environment maintains a long-term culturo-natural equilibrium or balance for many generations, emphasizes the importance that the modern humans who form and conserve environment need to rediscover and transform their culturo-natural legacy into conservation for many generations and produce knowledge of sustainability science, the transdisciplinary knowledge for the interaction between environment and humans, which fulfills the cultural, social and spiritual needs.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.151-171
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• 2014

Firms today have sought management effectiveness and efficiency utilizing information technologies (IT). Numerous firms are outsourcing specific information systems functions to cope with their short of information resources or IT experts, or to reduce their capital cost. Recently, Software-as-a-Service (SaaS) as a new type of information system has become one of the powerful outsourcing alternatives. SaaS is software deployed as a hosted and accessed over the internet. It is regarded as the idea of on-demand, pay-per-use, and utility computing and is now being applied to support the core competencies of clients in areas ranging from the individual productivity area to the vertical industry and e-commerce area. In this study, therefore, we seek to quantify the value that SaaS has on business performance by examining the relationships among firm strategies, SaaS technology maturity, and business performance of SaaS providers. We begin by drawing from prior literature on SaaS, technology maturity and firm strategy. SaaS technology maturity is classified into three different phases such as application service providing (ASP), Web-native application, and Web-service application. Firm strategies are manipulated by the low-cost strategy and differentiation strategy. Finally, we considered customer acquisition as a business performance. In this sense, specific objectives of this study are as follows. First, we examine the relationships between customer acquisition performance and both low-cost strategy and differentiation strategy of SaaS providers. Secondly, we investigate the mediating and moderating effects of SaaS technology maturity on those relationships. For this purpose, study collects data from the SaaS providers, and their line of applications registered in the database in CNK (Commerce net Korea) in Korea using a questionnaire method by the professional research institution. The unit of analysis in this study is the SBUs (strategic business unit) in the software provider. A total of 199 SBUs is used for analyzing and testing our hypotheses. With regards to the measurement of firm strategy, we take three measurement items for differentiation strategy such as the application uniqueness (referring an application aims to differentiate within just one or a small number of target industry), supply channel diversification (regarding whether SaaS vendor had diversified supply chain) as well as the number of specialized expertise and take two items for low cost strategy like subscription fee and initial set-up fee. We employ a hierarchical regression analysis technique for testing moderation effects of SaaS technology maturity and follow the Baron and Kenny's procedure for determining if firm strategies affect customer acquisition through technology maturity. Empirical results revealed that, firstly, when differentiation strategy is applied to attain business performance like customer acquisition, the effects of the strategy is moderated by the technology maturity level of SaaS providers. In other words, securing higher level of SaaS technology maturity is essential for higher business performance. For instance, given that firms implement application uniqueness or a distribution channel diversification as a differentiation strategy, they can acquire more customers when their level of SaaS technology maturity is higher rather than lower. Secondly, results indicate that pursuing differentiation strategy or low cost strategy effectively works for SaaS providers' obtaining customer, which means that continuously differentiating their service from others or making their service fee (subscription fee or initial set-up fee) lower are helpful for their business success in terms of acquiring their customers. Lastly, results show that the level of SaaS technology maturity mediates the relationships between low cost strategy and customer acquisition. That is, based on our research design, customers usually perceive the real value of the low subscription fee or initial set-up fee only through the SaaS service provide by vender and, in turn, this will affect their decision making whether subscribe or not.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.29-44
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• 2017

In Internet commerce, consumers are heavily influenced by product reviews written by other users who have already purchased the product. However, as the product reviews accumulate, it takes a lot of time and effort for consumers to individually check the massive number of product reviews. Moreover, product reviews that are written carelessly actually inconvenience consumers. Thus many online vendors provide mechanisms to identify reviews that customers perceive as most helpful (Cao et al. 2011; Mudambi and Schuff 2010). For example, some online retailers, such as Amazon.com and TripAdvisor, allow users to rate the helpfulness of each review, and use this feedback information to rank and re-order them. However, many reviews have only a few feedbacks or no feedback at all, thus making it hard to identify their helpfulness. Also, it takes time to accumulate feedbacks, thus the newly authored reviews do not have enough ones. For example, only 20% of the reviews in Amazon Review Dataset (Mcauley and Leskovec, 2013) have more than 5 reviews (Yan et al, 2014). The purpose of this study is to analyze the factors affecting the usefulness of online product reviews and to derive a forecasting model that selectively provides product reviews that can be helpful to consumers. In order to do this, we extracted the various linguistic, psychological, and perceptual elements included in product reviews by using text-mining techniques and identifying the determinants among these elements that affect the usability of product reviews. In particular, considering that the characteristics of the product reviews and determinants of usability for apparel products (which are experiential products) and electronic products (which are search goods) can differ, the characteristics of the product reviews were compared within each product group and the determinants were established for each. This study used 7,498 apparel product reviews and 106,962 electronic product reviews from Amazon.com. In order to understand a review text, we first extract linguistic and psychological characteristics from review texts such as a word count, the level of emotional tone and analytical thinking embedded in review text using widely adopted text analysis software LIWC (Linguistic Inquiry and Word Count). After then, we explore the descriptive statistics of review text for each category and statistically compare their differences using t-test. Lastly, we regression analysis using the data mining software RapidMiner to find out determinant factors. As a result of comparing and analyzing product review characteristics of electronic products and apparel products, it was found that reviewers used more words as well as longer sentences when writing product reviews for electronic products. As for the content characteristics of the product reviews, it was found that these reviews included many analytic words, carried more clout, and related to the cognitive processes (CogProc) more so than the apparel product reviews, in addition to including many words expressing negative emotions (NegEmo). On the other hand, the apparel product reviews included more personal, authentic, positive emotions (PosEmo) and perceptual processes (Percept) compared to the electronic product reviews. Next, we analyzed the determinants toward the usefulness of the product reviews between the two product groups. As a result, it was found that product reviews with high product ratings from reviewers in both product groups that were perceived as being useful contained a larger number of total words, many expressions involving perceptual processes, and fewer negative emotions. In addition, apparel product reviews with a large number of comparative expressions, a low expertise index, and concise content with fewer words in each sentence were perceived to be useful. In the case of electronic product reviews, those that were analytical with a high expertise index, along with containing many authentic expressions, cognitive processes, and positive emotions (PosEmo) were perceived to be useful. These findings are expected to help consumers effectively identify useful product reviews in the future.

• Journal of the Korean Geographical Society
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• v.38 no.2
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• pp.312-323
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• 2003

This writer absolutely agrees with the government that regional disequilibrium is severe enough to consider moving the administrative capital. Pursuing this course solely to establish a balanced development, however, is not a convincing enough reason. The capital city is directly related to not only the social and economic situation but, much more importantly, to the domestic political situation as well. In the mid-1970s, the proposal by the Third Republic to move the capital city temporarily was based completely on security reasons. At e time, the then opposition leader Kim, Dae-jung said that establishing a safe distance from the demilitarized zone(DMZ) reflected a typically military decision. His view was that retaining the capital city close to the DMZ would show more consideration for the will of the people to defend their own country. In fact, independent Pakistan moved its capital city from Karachi to Islamabad, situated dose to Kashmir the subject of hot territorial dispute with India. It is regrettable that no consideration has been given to the urgent political situation in the Korean peninsula, which is presently enveloped in a dense nuclear fog. As a person requires health to pursue his/her dream, a country must have security to implement a balanced territorial development. According to current urban theories, the fate of a country depends on its major cities. A negligently guarded capital city runs the risk of becoming hostage and bringing ruin to the whole country. In this vein, North Koreas undoubted main target of attack in the armed communist reunification of Korea is Seoul. For the preservation of our state, therefore, it is only right that Seoul must be shielded to prevent becoming hostage to North Korea. The location of the US Armed Forces to the north of the capital city is based on the judgment that defense of Seoul is of absolute importance. At the same time, regardless of their different standpoints, South and North Korea agree that division of the Korean people into two separate countries is abnormal. Reunification, which so far has defied all predictions, may be realized earlier than anyone expects. The day of reunification seems to be the best day for the relocation of the capital city. Building a proper capital city would take at least twenty years, and a capital city cannot be dragged from one place to another. On the day of a free and democratic reunification, a national agreement will be reached naturally to find a nationally symbolic city as in Brazil or Australia. Even if security does not pose a problem, the governments way of thinking would not greatly contribute to the balanced development of the country. The Chungcheon region, which is earmarked as the new location of the capital city, has been the greatest beneficiary of its proximity to the capital region. Not being a disadvantaged region, locating the capital city there would not help alleviate regional disparity. If it is absolutely necessary to find a candidate region at present, considering security, balanced regional development and post-reunification scenario of the future, Cheolwon area located in the middle of the Korean peninsula may be a plausible choice. Even if the transfer of capital is delayed in consideration of the present political conflict between the South and the North Koreas, there is a definite shortcut to realizing a balanced regional development. It can be found not in the geographical dispersal of the central government, but in the decentralization of power to the provinces. If the government has surplus money to build a new symbolic capital city, it is only right that it should improve, for instance, the quality of drinking water which now everyone eschews, and to help the regional subway authority whose chronic deficit state resoled in a recent disastrous accident. And it is proper to time the transfer of capital city to coincide with that of the reunification of Korea whenever Providence intends.

• Communications of Mathematical Education
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• v.24 no.1
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• pp.235-257
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• 2010

Contemporary belief is that the creative talented can create new knowledge and lead national development, so lots of countries in the world have interest in Gifted Education. As we well know, U.S.A., England, Russia, Germany, Australia, Israel, and Singapore enforce related laws in Gifted Education to offer Gifted Classes, and our government has also created an Improvement Act in January, 2000 and Enforcement Ordinance for Gifted Improvement Act was also announced in April, 2002. Through this initiation Gifted Education can be possible. Enforcement Ordinance was revised in October, 2008. The main purpose of this revision was to expand the opportunity of Gifted Education to students with special education needs. One of these programs is, the opportunity of Gifted Education to be offered to lots of the Gifted by establishing Special Classes at each school. Also, it is important that the quality of Gifted Education should be combined with the expansion of opportunity for the Gifted. Social opinion is that it will be reckless only to expand the opportunity for the Gifted Education, therefore, assessment on the Teaching and Learning Program for the Gifted is indispensible. In this study, 3 middle schools were selected for the Teaching and Learning Programs in mathematics. Each 1st Grade was reviewed and analyzed through comparative tables between Regular and Gifted Education Programs. Also reviewed was the content of what should be taught, and programs were evaluated on assessment standards which were revised and modified from the present teaching and learning programs in mathematics. Below, research issues were set up to assess the formation of content areas and appropriateness for Teaching and Learning Programs for the Gifted in mathematics. A. Is the formation of special class content areas complying with the 7th national curriculum? 1. Which content areas of regular curriculum is applied in this program? 2. Among Enrichment and Selection in Curriculum for the Gifted, which one is applied in this programs? 3. Are the content areas organized and performed properly? B. Are the Programs for the Gifted appropriate? 1. Are the Educational goals of the Programs aligned with that of Gifted Education in mathematics? 2. Does the content of each program reflect characteristics of mathematical Gifted students and express their mathematical talents? 3. Are Teaching and Learning models and methods diverse enough to express their talents? 4. Can the assessment on each program reflect the Learning goals and content, and enhance Gifted students' thinking ability? The conclusions are as follows: First, the best contents to be taught to the mathematical Gifted were found to be the Numeration, Arithmetic, Geometry, Measurement, Probability, Statistics, Letter and Expression. Also, Enrichment area and Selection area within the curriculum for the Gifted were offered in many ways so that their Giftedness could be fully enhanced. Second, the educational goals of Teaching and Learning Programs for the mathematical Gifted students were in accordance with the directions of mathematical education and philosophy. Also, it reflected that their research ability was successful in reaching the educational goals of improving creativity, thinking ability, problem-solving ability, all of which are required in the set curriculum. In order to accomplish the goals, visualization, symbolization, phasing and exploring strategies were used effectively. Many different of lecturing types, cooperative learning, discovery learning were applied to accomplish the Teaching and Learning model goals. For Teaching and Learning activities, various strategies and models were used to express the students' talents. These activities included experiments, exploration, application, estimation, guess, discussion (conjecture and refutation) reconsideration and so on. There were no mention to the students about evaluation and paper exams. While the program activities were being performed, educational goals and assessment methods were reflected, that is, products, performance assessment, and portfolio were mainly used rather than just paper assessment.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.10 no.3
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• pp.154-163
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• 2005

Irregular discharges of freshwater through the water gates of the Keum River Estuarine Weir, Korea, whose construction had been completed in 1998 with its water gates being operated as late as August 1994, drastically modified the estuarine environment. Sharp decrease of salinity along with the altered concentrations of inorganic nutrients are accompanied with the irregular discharges of freshwater into the estuary under the influence of regular semi-diurnal tidal effect. Field sampling was carried out on the time of high tide at 2 fixed stations(St.1 near the Estuarine Weir and St.2 off Kunsan Ferry Station) every other day for 4 months from mid-February 2004 to investigate into the semi-weekly variation of spring phytoplankton community in relation to the freshwater discharges from Keum River Estuarine Weir. CV(coefficient of variation) of salinity measurements was roughly 2 times greater in St.1 than that in St.2, reflecting extreme salinity variation in St.1 Among inorganic nutrients, concentrations of N-nutrients($NO_3^-,\;NO_2^-$ and $NH_4^+$) were clearly higher in St.1, to imply the more drastic changes of the nutrient concentrations in St.1. than St.2 following the freshwater discharges. As a component of phytoplankton community, diatoms were among the top dominants in terms of species richness as well as biomass. Solitary centric diatom, Cyclotella meneghiniana, and chain-forming centric diatom, Skeletonema costatum, dominated over the phytoplankton community in order for S-6 weeks each (Succession Interval I and II), and the latter succeeded to the former from the time of <$10^{\circ}C$ of water temperature. Cyanobacterial species, Aphanizomenon Posaquae and Phormidium sp., which might be transported into the estuary along with the discharged freshwater, occupied high portion of total biomass during Succession Interval III(mid-April to late-May). During this period, freshwater species exclusively dominated over the phytoplankton community except the low concentrations of the co-occurring 2 estuarine diatoms, Cyclotella meneghiniana and Skeletonema costatum. During the 4th Succession Interval when the water temperature was over $18^{\circ}C$, the diatom, Guinardia delicatula, was predominant for a week with the highest dominance of $75\%$ in discrete samples. To summarize, during all the Succession Intervals other than Succession Interval III characterized by the extreme variation of salinity under cooler water temperature than $18^{\circ}C$, the diatoms were the most important dominants for species succession in spring. If the scale and frequency of the freshwater discharge could have been adjusted properly even during the Succession Interval III, the dominant species would quite possibly be replaced by other estuarine diatom species rather than the two freshwater cyanobacteria, Aphanizomenon flosaquae and Phormidium sp.. The scheme of field sampling every other day for the present study was concluded to be the minimal requirement in order to adequately explore the phytoplankton succession in such estuarine environment as in Keum River Estuary: which is stressed by the unpredictable and unavoidable discharges of freshwater under the regular semi-diurnal tide.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.219-240
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• 2018

Sentiment analysis, which is one of the text mining techniques, is a method for extracting subjective content embedded in text documents. Recently, the sentiment analysis methods have been widely used in many fields. As good examples, data-driven surveys are based on analyzing the subjectivity of text data posted by users and market researches are conducted by analyzing users' review posts to quantify users' reputation on a target product. The basic method of sentiment analysis is to use sentiment dictionary (or lexicon), a list of sentiment vocabularies with positive, neutral, or negative semantics. In general, the meaning of many sentiment words is likely to be different across domains. For example, a sentiment word, 'sad' indicates negative meaning in many fields but a movie. In order to perform accurate sentiment analysis, we need to build the sentiment dictionary for a given domain. However, such a method of building the sentiment lexicon is time-consuming and various sentiment vocabularies are not included without the use of general-purpose sentiment lexicon. In order to address this problem, several studies have been carried out to construct the sentiment lexicon suitable for a specific domain based on 'OPEN HANGUL' and 'SentiWordNet', which are general-purpose sentiment lexicons. However, OPEN HANGUL is no longer being serviced and SentiWordNet does not work well because of language difference in the process of converting Korean word into English word. There are restrictions on the use of such general-purpose sentiment lexicons as seed data for building the sentiment lexicon for a specific domain. In this article, we construct 'KNU Korean Sentiment Lexicon (KNU-KSL)', a new general-purpose Korean sentiment dictionary that is more advanced than existing general-purpose lexicons. The proposed dictionary, which is a list of domain-independent sentiment words such as 'thank you', 'worthy', and 'impressed', is built to quickly construct the sentiment dictionary for a target domain. Especially, it constructs sentiment vocabularies by analyzing the glosses contained in Standard Korean Language Dictionary (SKLD) by the following procedures: First, we propose a sentiment classification model based on Bidirectional Long Short-Term Memory (Bi-LSTM). Second, the proposed deep learning model automatically classifies each of glosses to either positive or negative meaning. Third, positive words and phrases are extracted from the glosses classified as positive meaning, while negative words and phrases are extracted from the glosses classified as negative meaning. Our experimental results show that the average accuracy of the proposed sentiment classification model is up to 89.45%. In addition, the sentiment dictionary is more extended using various external sources including SentiWordNet, SenticNet, Emotional Verbs, and Sentiment Lexicon 0603. Furthermore, we add sentiment information about frequently used coined words and emoticons that are used mainly on the Web. The KNU-KSL contains a total of 14,843 sentiment vocabularies, each of which is one of 1-grams, 2-grams, phrases, and sentence patterns. Unlike existing sentiment dictionaries, it is composed of words that are not affected by particular domains. The recent trend on sentiment analysis is to use deep learning technique without sentiment dictionaries. The importance of developing sentiment dictionaries is declined gradually. However, one of recent studies shows that the words in the sentiment dictionary can be used as features of deep learning models, resulting in the sentiment analysis performed with higher accuracy (Teng, Z., 2016). This result indicates that the sentiment dictionary is used not only for sentiment analysis but also as features of deep learning models for improving accuracy. The proposed dictionary can be used as a basic data for constructing the sentiment lexicon of a particular domain and as features of deep learning models. It is also useful to automatically and quickly build large training sets for deep learning models.