• The Korean Journal of Air & Space Law and Policy
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• v.29 no.1
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• pp.67-95
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• 2014

Some Contracting States of the Chicago Convention issue FAOC(Foreign Air Operator Certificate) and conduct various safety assessments for the safety of the foreign operators which operate to their state. These FAOC and safety audits on the foreign operators are being expanded to other parts of the world. While this trend is the strengthening measure of aviation safety resulting in the reduction of aircraft accident. FAOC also burdens the other contracting States to the Chicago Convention due to additional requirements and late permission. EASA(European Aviation Safety Agency) is a body governed by European Basic Regulation. EASA was set up in 2003 and conduct specific regulatory and executive tasks in the field of civil aviation safety and environmental protection. EASA's mission is to promote the highest common standards of safety and environmental protection in civil aviation. The task of the EASA has been expanded from airworthiness to air operations and currently includes the rulemaking and standardization of airworthiness, air crew, air operations, TCO, ATM/ANS safety oversight, aerodromes, etc. According to Implementing Rule, Commission Regulation(EU) No 452/2014, EASA has the mandate to issue safety authorizations to commercial air carriers from outside the EU as from 26 May 2014. Third country operators (TCO) flying to any of the 28 EU Member States and/or to 4 EFTA States (Iceland, Norway, Liechtenstein, Switzerland) must apply to EASA for a so called TCO authorization. EASA will only take over the safety-related part of foreign operator assessment. Operating permits will continue to be issued by the national authorities. A 30-month transition period ensures smooth implementation without interrupting international air operations of foreign air carriers to the EU/EASA. Operators who are currently flying to Europe can continue to do so, but must submit an application for a TCO authorization before 26 November 2014. After the transition period, which lasts until 26 November 2016, a valid TCO authorization will be a mandatory prerequisite, in the absence of which an operating permit cannot be issued by a Member State. The European TCO authorization regime does not differentiate between scheduled and non-scheduled commercial air transport operations in principle. All TCO with commercial air transport need to apply for a TCO authorization. Operators with a potential need of operating to the EU at some time in the near future are advised to apply for a TCO authorization in due course, even when the date of operations is unknown. For all the issue mentioned above, I have studied the function of EASA and EU Regulation including TCO Implementing Rule newly introduced, and suggested some proposals. I hope that this paper is 1) to help preparation of TCO authorization, 2) to help understanding about the international issue, 3) to help the improvement of korean aviation regulations and government organizations, 4) to help compliance with international standards and to contribute to the promotion of aviation safety, in addition.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.26 no.1
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• pp.69-89
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• 1981

Stevia (Stevia rebaudiana Bertoni) is a perennial herb widely distributed in the mountainous area of Paraguay. It belongs to the family Compositae and contains 6 to 12 percent stevioside in the leaves. Stevioside is a glucoside having similar sweetening character to surgar and the degree of sweetness is approximately 300 times of sugar. Since Korea does not produce any sugar crops, and the synthetic sweetenings are potentially hazardous for health, it is rather urgent to develop an economical new sweetener. Consequently, the current experiments are conducted to establish cultural practices of stevia, a new sweetening herbs, introduced into Korea in 1973 and the results are summarized as followings: 1. Days from transplanting of cuttings to the flower bud formation of 6 stevia lines were similar among daylengths of 8, 10 and 12 hours, but it was much greater at daylengths of 14 or 24 hour and varietal differences were noticable. All lines were photosensitive, but a line, 77013, was the most sensitive and 77067 and Suweon 2 were less sensitive to daylength. 2. Critical daylength of all lines seemed to be approximately 12 hours. Growth of plants was severely retarded at daylengths less than 12 hours. 3. Cutting were responded to short daylength before rooting. Number of days from transplanting to flower bud formation of 40-day old cuttings in the nursery bed was 20 days and it was delayed as duration of nursery were shorter. 4. Number of days from emergence to flower bud formation was shortest at short day treatment from 20 days after emergence. It was became longer as initiation of short day treatment was earlier or later than 20 days. 5. Plant height, number of branches, and top dry weight of stevia were reduced as cutting date was delayed from March 20 to May 20. The highest yield of dry leaf was obtained at nursery duration of 40-50 days in march 20 cutting, 30-40 days in April 20 cutting, and 30 days in May 20 cutting. 6. An asymptotic relationship was observed between plant population and leaf dry weight. Yield of dry leaf increased rapidly as plant population increased from 5,000 to 10,000 plants/10a with a reduced increasing rate from 10,000 to 20,000 plants/l0a, and levelled off at the plant population higher than 20,000 plants/l0a. 7. Stevia was adaptable in Suweon, Chengju, Mokpo and Jeju and drought was one of the main factors reducing yield of dry leaf. Yield of dry leaf was reduced significantly (approximately 30%) at June 20 transplanting compared to optimum transplanting. 8. Yield of dry leaf was higher in a vinyl house compared to unprotected control at long daylength or natural daylength except at short day treatment at March 20. Higher temperature ill a vinyl house does not have benefital effects at April 20 transplanting. 9. The highest content of stevioside was noted at the upper leaves of the plant but the lowest was measured at the plant parts of 20cm above ground. Leaf dry weight and stevioside yield was mainly contributed by the plant parts of 60 to 120cm above ground but the varietal differences were also significant. 10. Delayed harvest by the time of flower bud formation increased leaf dry weight remarkably. However, there were insignificant changes of yield as harvests were made at any time after flower bud formation. Content of stevioside was highest at the time of flower bud formation and earlier or later harvest than this time was low in its content. The optimum harvesting time determined by leaf dry weight and stevioside content was the periods from flower bud formation to right before flowering that would be the period from September 10 to September 15 in Suweon area. 11. Stevioside and rebaudioside content in the leaves of Stevia varieties were ranged from 5.4% to 14.3% and 1.5% to 8.3% respectively. However, no definit relationships between stevioside and rebaudioside were observed in these particular experiments.

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

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

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Journal of The Korean Society of Grassland and Forage Science
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• v.18 no.2
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• pp.79-88
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• 1998

This experiment was conducted from May to August in 1997 to selected the wrn hybrids being suitable for silage at farm in the Kongju National University through the comparison of growth characteristics, forage yield and growth analysis about native and imported corn hybrids for silage production. In this experiment, trial design was a randomized block design with three replication, testing varieties were 4 hybrids (Suwon 19, Kwanganok, Whengsungok, Suwonok ) of native corn hybrids and 13 hybrids (P 3156, P 3352, P 3144w, DK 501, DK 689, DK 713, DK 729, H 643.99, H 545.64, H 645.12, HC 7466, H 644.18, H ALISEO) of imported corn hybrids. The results obtained are summarized as follows; 1. The emergence rate of H643.99 was the highest with 97.0%. In rice black streaked dwarf virus(RBSOV), the hybrid of HC 7466 was lower infected with 1.6% than other hybrids. The plant hight of P 3144w was the highest with 339 cm and the stem length of P 3156 was the highest with 261 cm. In native com hybrids, the plant height and stem length of Kwanganok were recorded with 306 cm and 235 cm, respectively. 2. Leaf number and leaf area of Kwanganok were the greatest with 16 sheet per plant and $5,180\;{\textrm{m}^2}/l0a$, respectively. H 645.12 and H 545.64 had the greatest in ear to total dry matter ratio with 49.5% and 49.4%, respectively. 3. The fresh matter yield was significantly difference between growth stage, So Suwon 19 had the most level at 15 days before silking, P 3352 had the most level at silking date, Kwananok had the most level at 35 days a after silking. The fresh matter yield of native com hybrids such as Suwon 19 and Kwanganok was not apparent diffreences as compared with imported corn hybrids. 4. As the results of survey with dry weight, the quantity of dry matter accumulation were increase after silking. The varieties of P 3352, P 3156, Kwanganok, OK 713 were more quantity of dry matter production than DK 501, HC 7466. The Kwanganok of native com hybrid and Pioneer strain with high percentage of dry matter were higher dry weight than Limagrain strain. 5. HC 7466 had the largest LAR with $6.53\;{\textrm{cm}^2}/g$, H545.12 had the lowest LAR with $3.30\;{\textrm{cm}^2/g}$. P 3144 had the largest LAI, DeKalb strain including DK 713 were larger apparently than Limagrain strain including HC 7466 with 3.15. 6. The RGR of testing varieties was little difference of statistical significantly, but DK 501, and HC 7466 were lower than other corn hybrids. The CGR of native and American varieties was no apparent differences, but that of Limagrain strains were a large variation. According to the results obtained by this experiment, the eary growth such as emergence rate and RBSDV infection rate of Limagrain strains was more excellent than other strains. P 3156, P 3352, P 3144w, DK 713 and HC 7466 were suitable for silage condition such as dry matter yield, percentage of dry matter and % ear to total dry matter. The fresh and dry matter yield of native corn hybrids such as Suwon 19 and Kwanganok were not apparent differences as compared with imported corn hybrids, but percentage of dry matter was lower than other imported corn hybrids.

• Korean Journal of Breeding Science
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• v.41 no.4
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• pp.654-659
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• 2009

"Cheongcheongjinmi" is a new japonica rice variety developed from a cross between Iri401 and Ilpumbyeo by the rice breeding team of National Institute of Crop Science, RDA. This variety is suitable for ordinary season culture of low level nitrogen application. Heading date of "Cheongcheongjinmi" is August 17, 4 days later than that of Sobibyeo in plain areas. It has culm length of 82 cm, and relatively semi-erect pubescent leaf blade and slightly tough culm tolerant to lodging with good canopy architecture. This variety has 13 tillers per hill, 126 spikelets per panicle and 90.2% of ripened grains. "Cheongcheongjinmi" showed lower spikelet fertility than Sobibyeo when exposed to cold stress. This variety showed slower leaf senescence and lower viviparous germination compared to Sobibyeo during the ripening stage. "Cheongcheongjinmi" is susceptible to blast disease, bacterial blight, virus diseases and planthoppers. The dried plant weight, total nitrogen and RuBisCO activity of "Cheongcheongjinmi" were higher than those of Sobibyeo in low level nitrogen application. The milled rice of "Cheongcheongjinmi" exhibits translucent, clear non-glutinous endosperm and medium short grain. It shows lower protein and amylose contents than those of Sobibyeo, and better palatability of cooked rice compared to Hwaseongbyeo. The milled rice yield of this cultivar is about 5.10 MT/ha at low level nitrogen application of ordinary season culture in local adaptability test for three years. Especially, "Cheongcheongjinmi" has better milling properties such as the percentage of whole grain in milled rice and milling recovery of whole grain, respectively than those of Sobibyeo. "Cheongcheongjinmi" would be adaptable to middle plain areas and middle-western coastal areas of Korea.

• Korean Journal of Heritage: History & Science
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• v.52 no.2
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• pp.196-219
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• 2019

According to the Samguk Yusa, the nine-story wooden pagoda at Hwangnyongsa Temple was built by a Baekje artisan named Abiji in 645. Until the temple was burnt down completely during the Mongol invasion of Korea in 1238, it was the greatest symbol of the spiritual culture of the Korean people at that time and played an important role in the development of Buddhist thought in the country for about 700 years. At present, the only remaining features of Hwangnyongsa Temple, which is now in ruins, are the pagoda's stylobate and several foundation stones. In the past, many researchers made diverse inferences concerning the restoration of the original structure and the overall architecture of the wooden pagoda at Hwangnyongsa Temple, based on written records and excavation data. However, this information, together with the remaining external structure of the pagoda site and the assumption that it was a simple wooden structure, actually suggest that it was a rectangular-shaped nine-story pagoda. It is assumed that such ideas were suggested at a time when there was a lack of relevant data and limited knowledge on the subject, as well as insufficient information about the technical lineage of the wooden pagoda at Hwangnyongsa Temple; therefore, these ideas should be revised in respect of the discovery of new data and an improved level of awareness about the structural features of large ancient Buddhist pagodas. This study focused on the necessity of raising awareness of the lineage and structure of the wooden pagoda at Hwangnyongsa Temple and gaining a broader understanding of the structural system of ancient Buddhist pagodas in East Asia. The study is based on a reanalysis of data about the site of the wooden pagoda obtained through research on the restoration of Hwangnyongsa Temple, which has been ongoing since 2005. It is estimated that the wooden pagoda underwent at least two large-scale repairs between the Unified Silla and Goryeo periods, during which the size of the stylobate and the floor plan were changed and, accordingly, the upper structure was modified to a significant degree. Judging by the features discovered during excavation and investigation, traces relating to the nine-story wooden pagoda built during the Three Kingdoms Period include the earth on which the stylobate was built and the central pillar's supporting stone, which had been reinstalled using the rammed earth technique, as well as other foundation stones and stylobate stone materials that most probably date back to the ninth century or earlier. It seems that the foundation stones and stylobate stone materials were new when the reliquaries were enshrined again in the pagoda after the Unified Silla period, so the first story and upper structure would have been of a markedly different size to those of the original wooden pagoda. In addition, during the Goryeo period, these foundation stones were rearranged, and the cover stone was newly installed; therefore, the pagoda would seem to have undergone significant changes in size and structure compared to previous periods. Consequently, the actual structure of the original wooden pagoda at Hwangnyongsa Temple should be understood in terms of the changes in large Buddhist pagodas built in East Asia at that time, and the technical lineage should start with the large Buddhist pagodas of the Baekje dynasty, which were influenced by the Northern dynasty of China. Furthermore, based on the archeological data obtained from the analysis of the images of the nine-story rock-carved pagoda depicted on the Rock-carved Buddhas in Tapgok Valley at Namsan Mountain in Gyeongju, and the gilt-bronze rail fragments excavated from the lecture hall at the site of Hwangnyongsa Temple, the wooden pagoda would appear to have originally been an octagonal nine-story pagoda with a dual structure, rather than a simple rectangular wooden structure.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.141-166
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• 2019

Recently, channels like social media and SNS create enormous amount of data. In all kinds of data, portions of unstructured data which represented as text data has increased geometrically. But there are some difficulties to check all text data, so it is important to access those data rapidly and grasp key points of text. Due to needs of efficient understanding, many studies about text summarization for handling and using tremendous amounts of text data have been proposed. Especially, a lot of summarization methods using machine learning and artificial intelligence algorithms have been proposed lately to generate summary objectively and effectively which called "automatic summarization". However almost text summarization methods proposed up to date construct summary focused on frequency of contents in original documents. Those summaries have a limitation for contain small-weight subjects that mentioned less in original text. If summaries include contents with only major subject, bias occurs and it causes loss of information so that it is hard to ascertain every subject documents have. To avoid those bias, it is possible to summarize in point of balance between topics document have so all subject in document can be ascertained, but still unbalance of distribution between those subjects remains. To retain balance of subjects in summary, it is necessary to consider proportion of every subject documents originally have and also allocate the portion of subjects equally so that even sentences of minor subjects can be included in summary sufficiently. In this study, we propose "subject-balanced" text summarization method that procure balance between all subjects and minimize omission of low-frequency subjects. For subject-balanced summary, we use two concept of summary evaluation metrics "completeness" and "succinctness". Completeness is the feature that summary should include contents of original documents fully and succinctness means summary has minimum duplication with contents in itself. Proposed method has 3-phases for summarization. First phase is constructing subject term dictionaries. Topic modeling is used for calculating topic-term weight which indicates degrees that each terms are related to each topic. From derived weight, it is possible to figure out highly related terms for every topic and subjects of documents can be found from various topic composed similar meaning terms. And then, few terms are selected which represent subject well. In this method, it is called "seed terms". However, those terms are too small to explain each subject enough, so sufficient similar terms with seed terms are needed for well-constructed subject dictionary. Word2Vec is used for word expansion, finds similar terms with seed terms. Word vectors are created after Word2Vec modeling, and from those vectors, similarity between all terms can be derived by using cosine-similarity. Higher cosine similarity between two terms calculated, higher relationship between two terms defined. So terms that have high similarity values with seed terms for each subjects are selected and filtering those expanded terms subject dictionary is finally constructed. Next phase is allocating subjects to every sentences which original documents have. To grasp contents of all sentences first, frequency analysis is conducted with specific terms that subject dictionaries compose. TF-IDF weight of each subjects are calculated after frequency analysis, and it is possible to figure out how much sentences are explaining about each subjects. However, TF-IDF weight has limitation that the weight can be increased infinitely, so by normalizing TF-IDF weights for every subject sentences have, all values are changed to 0 to 1 values. Then allocating subject for every sentences with maximum TF-IDF weight between all subjects, sentence group are constructed for each subjects finally. Last phase is summary generation parts. Sen2Vec is used to figure out similarity between subject-sentences, and similarity matrix can be formed. By repetitive sentences selecting, it is possible to generate summary that include contents of original documents fully and minimize duplication in summary itself. For evaluation of proposed method, 50,000 reviews of TripAdvisor are used for constructing subject dictionaries and 23,087 reviews are used for generating summary. Also comparison between proposed method summary and frequency-based summary is performed and as a result, it is verified that summary from proposed method can retain balance of all subject more which documents originally have.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.167-194
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• 2019

This research starts from the four basic concepts of incentive incompatibility, limited information, myopia and decision variable which are confronted when making decisions in keyword bidding. In order to make these concept concrete, four framework approaches are designed as follows; Strategic approach for the incentive incompatibility, Statistical approach for the limited information, Alternative optimization for myopia, and New model approach for decision variable. The purpose of this research is to propose the statistical optimization model in constructing the portfolio of Sponsored Search Advertising (SSA) in the Sponsor's perspective through empirical tests which can be used in portfolio decision making. Previous research up to date formulates the CTR estimation model using CPC, Rank, Impression, CVR, etc., individually or collectively as the independent variables. However, many of the variables are not controllable in keyword bidding. Only CPC and Rank can be used as decision variables in the bidding system. Classical SSA model is designed on the basic assumption that the CPC is the decision variable and CTR is the response variable. However, this classical model has so many huddles in the estimation of CTR. The main problem is the uncertainty between CPC and Rank. In keyword bid, CPC is continuously fluctuating even at the same Rank. This uncertainty usually raises questions about the credibility of CTR, along with the practical management problems. Sponsors make decisions in keyword bids under the limited information, and the strategic portfolio approach based on statistical models is necessary. In order to solve the problem in Classical SSA model, the New SSA model frame is designed on the basic assumption that Rank is the decision variable. Rank is proposed as the best decision variable in predicting the CTR in many papers. Further, most of the search engine platforms provide the options and algorithms to make it possible to bid with Rank. Sponsors can participate in the keyword bidding with Rank. Therefore, this paper tries to test the validity of this new SSA model and the applicability to construct the optimal portfolio in keyword bidding. Research process is as follows; In order to perform the optimization analysis in constructing the keyword portfolio under the New SSA model, this study proposes the criteria for categorizing the keywords, selects the representing keywords for each category, shows the non-linearity relationship, screens the scenarios for CTR and CPC estimation, selects the best fit model through Goodness-of-Fit (GOF) test, formulates the optimization models, confirms the Spillover effects, and suggests the modified optimization model reflecting Spillover and some strategic recommendations. Tests of Optimization models using these CTR/CPC estimation models are empirically performed with the objective functions of (1) maximizing CTR (CTR optimization model) and of (2) maximizing expected profit reflecting CVR (namely, CVR optimization model). Both of the CTR and CVR optimization test result show that the suggested SSA model confirms the significant improvements and this model is valid in constructing the keyword portfolio using the CTR/CPC estimation models suggested in this study. However, one critical problem is found in the CVR optimization model. Important keywords are excluded from the keyword portfolio due to the myopia of the immediate low profit at present. In order to solve this problem, Markov Chain analysis is carried out and the concept of Core Transit Keyword (CTK) and Expected Opportunity Profit (EOP) are introduced. The Revised CVR Optimization model is proposed and is tested and shows validity in constructing the portfolio. Strategic guidelines and insights are as follows; Brand keywords are usually dominant in almost every aspects of CTR, CVR, the expected profit, etc. Now, it is found that the Generic keywords are the CTK and have the spillover potentials which might increase consumers awareness and lead them to Brand keyword. That's why the Generic keyword should be focused in the keyword bidding. The contribution of the thesis is to propose the novel SSA model based on Rank as decision variable, to propose to manage the keyword portfolio by categories according to the characteristics of keywords, to propose the statistical modelling and managing based on the Rank in constructing the keyword portfolio, and to perform empirical tests and propose a new strategic guidelines to focus on the CTK and to propose the modified CVR optimization objective function reflecting the spillover effect in stead of the previous expected profit models.