• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• Journal of Distribution Science
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• v.10 no.2
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• pp.29-41
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• 2012

This paper undertakes a conceptual review of transaction cost to broaden the understanding of the transaction cost analysis (TCA) approach. More than 40 years have passed since Coase's fundamental insight that transaction, coordination, and contracting costs must be considered explicitly in explaining the extent of vertical integration. Coase (1937) forced economists to identify previously neglected constraints on the trading process to foster efficient intrafirm, rather than interfirm, transactions. The transaction cost approach to economic organization study regards transactions as the basic units of analysis and holds that understanding transaction cost economy is central to organizational study. The approach applies to determining efficient boundaries, as between firms and markets, and to internal transaction organization, including employment relations design. TCA, developed principally by Oliver Williamson (1975,1979,1981a) blends institutional economics, organizational theory, and contract law. Further progress in transaction costs research awaits the identification of critical dimensions in which transaction costs differ and an examination of the economizing properties of alternative institutional modes for organizing transactions. The crucial investment distinction is: To what degree are transaction-specific (non-marketable) expenses incurred? Unspecialized items pose few hazards, since buyers can turn toalternative sources, and suppliers can sell output intended for one order to other buyers. Non-marketability problems arise when specific parties' identities have important cost-bearing consequences. Transactions of this kind are labeled idiosyncratic. The summarized results of the review are as follows. First, firms' distribution decisions often prompt examination of the make-or-buy question: Should a marketing activity be performed within the organization by company employees or contracted to an external agent? Second, manufacturers introducing an industrial product to a foreign market face a difficult decision. Should the product be marketed primarily by captive agents (the company sales force and distribution division) or independent intermediaries (outside sales agents and distribution)? Third, the authors develop a theoretical extension to the basic transaction cost model by combining insights from various theories with the TCA approach. Fourth, other such extensions are likely required for the general model to be applied to different channel situations. It is naive to assume the basic model appliesacross markedly different channel contexts without modifications and extensions. Although this study contributes to scholastic research, it is limited by several factors. First, the theoretical perspective of TCA has attracted considerable recent interest in the area of marketing channels. The analysis aims to match the properties of efficient governance structures with the attributes of the transaction. Second, empirical evidence about TCA's basic propositions is sketchy. Apart from Anderson's (1985) study of the vertical integration of the selling function and John's (1984) study of opportunism by franchised dealers, virtually no marketing studies involving the constructs implicated in the analysis have been reported. We hope, therefore, that further research will clarify distinctions between the different aspects of specific assets. Another important line of future research is the integration of efficiency-oriented TCA with organizational approaches that emphasize specific assets' conceptual definition and industry structure. Finally, research of transaction costs, uncertainty, opportunism, and switching costs is critical to future study.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.123-139
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• 2019

The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.

• Journal of Hospice and Palliative Care
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• v.4 no.1
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• pp.14-25
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• 2001

Purpose : To determine whether there exist gender differences in pain in Korean cancer patients and whether the depression and performance that are often expressed differently between men and women with cancer interact with pain. Method : The results of survey were collected from 140 in- and out-patients (78 male and 62 female) who had cancer treatment at one of the university hospital in Seoul for four months from February of 1999. The severity and interference of pain were examined with the self-reported survey based on Korean version of Brief Pain Inventory (BPI-K). Demographic and clinical information for all patient were compiled by reviewing their medical records, and the level of depression was examined with the Korean version of Beck Depression Inventory (BDI-K). Usual statistical methods, e.g., frequences, means and SDs were used to characterize the sample. The chi-square tests for categorical data and t-test for numerical data were used for group comparison. And the correlation between variables were performed using Pearson correlation coefficient. Resuts : 1) The mean scores of the worst pain for last 24-hours measured with the pain severity of BPI-K were 5.77 in male and 6.45 in female. The pain interference of BPI-K in men was in the order of mood (5.49), enjoy (5.36), and work (5.00), and in women were work (7.48), enjoy (7.16), and mood (6.53). 2) In pain severity, significant difference was found between men and women in the average pain for last 24-hours (t=-2.130, P=.035). In pain interference, significant difference was found between men and women in activity (t=-2.450, P=.015), mood (t=-2,321, P=.022), walk (t=-2.762, P=.007), work (t=-4.946, P=.000), relate (t=-2.595, P=.010), sleep (t=-2.071, P=.040), enjoy (t=-3.198, P=.001). 3) It was found that the items of pain and depression are significantly correlated in men but not in women. Men also exhibited higher correlation in the items of pain and performance status than women. Conclusions : Women report significantly greater average pain for last 24-hours and for all items of pain interference than men. Pain and depression are significantly correlated in men. The results of this study suggest that gender differences in pain should be considered for planning effective pain management program.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.1-10
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• 2013

RFID(Radio Frequency Identification) system is non-contact identification technology. A basic RFID system consists of a reader, and a set of tags. RFID tags can be divided into active and passive tags. Active tags with power source allows their own operation execution and passive tags are small and low-cost. So passive tags are more suitable for distribution industry than active tags. A reader processes the information receiving from tags. RFID system achieves a fast identification of multiple tags using radio frequency. RFID systems has been applied into a variety of fields such as distribution, logistics, transportation, inventory management, access control, finance and etc. To encourage the introduction of RFID systems, several problems (price, size, power consumption, security) should be resolved. In this paper, we proposed an algorithm to significantly alleviate the collision problem caused by simultaneous responses of multiple tags. In the RFID systems, in anti-collision schemes, there are three methods: probabilistic, deterministic, and hybrid. In this paper, we introduce ALOHA-based protocol as a probabilistic method, and Tree-based protocol as a deterministic one. In Aloha-based protocols, time is divided into multiple slots. Tags randomly select their own IDs and transmit it. But Aloha-based protocol cannot guarantee that all tags are identified because they are probabilistic methods. In contrast, Tree-based protocols guarantee that a reader identifies all tags within the transmission range of the reader. In Tree-based protocols, a reader sends a query, and tags respond it with their own IDs. When a reader sends a query and two or more tags respond, a collision occurs. Then the reader makes and sends a new query. Frequent collisions make the identification performance degrade. Therefore, to identify tags quickly, it is necessary to reduce collisions efficiently. Each RFID tag has an ID of 96bit EPC(Electronic Product Code). The tags in a company or manufacturer have similar tag IDs with the same prefix. Unnecessary collisions occur while identifying multiple tags using Query Tree protocol. It results in growth of query-responses and idle time, which the identification time significantly increases. To solve this problem, Collision Tree protocol and M-ary Query Tree protocol have been proposed. However, in Collision Tree protocol and Query Tree protocol, only one bit is identified during one query-response. And, when similar tag IDs exist, M-ary Query Tree Protocol generates unnecessary query-responses. In this paper, we propose Adaptive M-ary Query Tree protocol that improves the identification performance using m-bit recognition, collision information of tag IDs, and prediction technique. We compare our proposed scheme with other Tree-based protocols under the same conditions. We show that our proposed scheme outperforms others in terms of identification time and identification efficiency.

• Journal of Animal Environmental Science
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• v.18 no.2
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• pp.99-110
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• 2012

The purpose of the study is to collect basis data for to establish standard administrative processes of liquid fertilizer treatment. From this survey we could make out the key point of each step through a case of effective liquid manure treatment system in pig house. It is divided into six step; 1. piggery slurry management step, 2. Solid-liquid separation step, 3. liquid fertilizer treatment (aeration) step, 4. liquid fertilizer treatment (microorganism, recirculation and internal return) step, 5. liquid fertilizer treatment (completion) step, 6. land application step. From now on, standardization process of liquid manure treatment technologies need to be develop based on the six steps process.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.175-191
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• 2011

With the MICE(Meeting, Incentive travel, Convention, Exhibition) industry coming into the spotlight, there has been a growing interest in the domestic exhibition industry. Accordingly, in Korea, various studies of the industry are being conducted to enhance exhibition performance as in the United States or Europe. Some studies are focusing particularly on analyzing visiting patterns of exhibition visitors using intelligent information technology in consideration of the variations in effects of watching exhibitions according to the exhibitory environment or technique, thereby understanding visitors and, furthermore, drawing the correlations between exhibiting businesses and improving exhibition performance. However, previous studies related to booth recommendation systems only discussed the accuracy of recommendation in the aspect of a system rather than determining changes in visitors' behavior or perception by recommendation. A booth recommendation system enables visitors to visit unplanned exhibition booths by recommending visitors suitable ones based on information about visitors' visits. Meanwhile, some visitors may be satisfied with their unplanned visits, while others may consider the recommending process to be cumbersome or obstructive to their free observation. In the latter case, the exhibition is likely to produce worse results compared to when visitors are allowed to freely observe the exhibition. Thus, in order to apply a booth recommendation system to exhibition halls, the factors affecting the performance of the system should be generally examined, and the effects of the system on visitors' unplanned visiting behavior should be carefully studied. As such, this study aims to determine the factors that affect the performance of a booth recommendation system by reviewing theories and literature and to examine the effects of visitors' perceived performance of the system on their satisfaction of unplanned behavior and intention to reuse the system. Toward this end, the unplanned behavior theory was adopted as the theoretical framework. Unplanned behavior can be defined as "behavior that is done by consumers without any prearranged plan". Thus far, consumers' unplanned behavior has been studied in various fields. The field of marketing, in particular, has focused on unplanned purchasing among various types of unplanned behavior, which has been often confused with impulsive purchasing. Nevertheless, the two are different from each other; while impulsive purchasing means strong, continuous urges to purchase things, unplanned purchasing is behavior with purchasing decisions that are made inside a store, not before going into one. In other words, all impulsive purchases are unplanned, but not all unplanned purchases are impulsive. Then why do consumers engage in unplanned behavior? Regarding this question, many scholars have made many suggestions, but there has been a consensus that it is because consumers have enough flexibility to change their plans in the middle instead of developing plans thoroughly. In other words, if unplanned behavior costs much, it will be difficult for consumers to change their prearranged plans. In the case of the exhibition hall examined in this study, visitors learn the programs of the hall and plan which booth to visit in advance. This is because it is practically impossible for visitors to visit all of the various booths that an exhibition operates due to their limited time. Therefore, if the booth recommendation system proposed in this study recommends visitors booths that they may like, they can change their plans and visit the recommended booths. Such visiting behavior can be regarded similarly to consumers' visit to a store or tourists' unplanned behavior in a tourist spot and can be understand in the same context as the recent increase in tourism consumers' unplanned behavior influenced by information devices. Thus, the following research model was established. This research model uses visitors' perceived performance of a booth recommendation system as the parameter, and the factors affecting the performance include trust in the system, exhibition visitors' knowledge levels, expected personalization of the system, and the system's threat to freedom. In addition, the causal relation between visitors' satisfaction of their perceived performance of the system and unplanned behavior and their intention to reuse the system was determined. While doing so, trust in the booth recommendation system consisted of 2nd order factors such as competence, benevolence, and integrity, while the other factors consisted of 1st order factors. In order to verify this model, a booth recommendation system was developed to be tested in 2011 DMC Culture Open, and 101 visitors were empirically studied and analyzed. The results are as follows. First, visitors' trust was the most important factor in the booth recommendation system, and the visitors who used the system perceived its performance as a success based on their trust. Second, visitors' knowledge levels also had significant effects on the performance of the system, which indicates that the performance of a recommendation system requires an advance understanding. In other words, visitors with higher levels of understanding of the exhibition hall learned better the usefulness of the booth recommendation system. Third, expected personalization did not have significant effects, which is a different result from previous studies' results. This is presumably because the booth recommendation system used in this study did not provide enough personalized services. Fourth, the recommendation information provided by the booth recommendation system was not considered to threaten or restrict one's freedom, which means it is valuable in terms of usefulness. Lastly, high performance of the booth recommendation system led to visitors' high satisfaction levels of unplanned behavior and intention to reuse the system. To sum up, in order to analyze the effects of a booth recommendation system on visitors' unplanned visits to a booth, empirical data were examined based on the unplanned behavior theory and, accordingly, useful suggestions for the establishment and design of future booth recommendation systems were made. In the future, further examination should be conducted through elaborate survey questions and survey objects.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Journal of Information Management
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• v.6 no.5
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• pp.131-134
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• 1973

본고(本稿)시리이즈의 제1보(第一報)에서 우리는 물리(物理), 사회과학(社會科學) 및 공학분야(工學分野)의 12,442명(名)의 과학자(科學者)와 기술자(技術者)에 대한 정보교환활동(情報交換活動)의 78례(例)에 있어서 일반과정(一般過程)과 몇 가지 결과(結果)를 기술(記述)한 바 있다. 4년반(年半) 이상(以上)의 기간(其間)($1966{\sim}1971$)에서 수행(遂行)된 이 연구(硏究)는 현재(現在)의 과학지식(科學知識)의 집성체(集成體)로 과학자(科學者)들이 연구(硏究)를 시작(始作)한 때부터 기록상(記錄上)으로 연구결과(硏究結果)가 취합(聚合)될 때까지 각종(各種) 정형(定形), 비정형(非定形) 매체(媒體)를 통한 유통정보(流通情報)의 전파(傳播)와 동화(同化)에 대한 포괄적(包括的)인 도식(圖式)으로 표시(表示)할 수 있도록 설정(設定)하고 또 시행(施行)되었다. 2보(二報), 3보(三報), 4보(四報)에서는 데이터 뱅크에 수집(蒐集) 및 축적(蓄積)된 데이터의 일반적(一般的)인 기술(記述)을 적시(摘示)하였다. (1) 과학(科學)과 기술(技術)의 정보유통(情報流通)에 있어서 국가적(國家的) 회합(會合)의 역할(役割)(Garvey; 4보(報)) 국가적(國家的) 회합(會合)은 투고(投稿)와 이로 인한 잡지중(雜誌中) 게재간(揭載間)의 상대적(相對的)인 오랜 기간(期間)동안 이러한 연구(硏究)가 공개매체(公開媒體)로 인하여 일시적(一時的)이나마 게재여부(揭載如否)의 불명료성(不明瞭性)을 초래(招來)하기 전(前)에 과학연구(科學硏究)의 초기전파(初期傳播)를 위하여 먼저 행한 주요(主要) 사례(事例)와 마지막의 비정형매체(非定形媒體)의 양자(兩者)를 항상 조직화(組織化)하여 주는 전체적(全體的)인 유통과정(流通過程)에 있어서 명확(明確)하고도 중요(重要)한 기능(機能)을 갖는다는 것을 알 수 있었다. (2) 잡지(雜誌)에 게재(揭載)된 정보(情報)의 생산(生産)과 관련(關聯)되는 정보(情報)의 전파과정(傳播過程)(Garvey; 1보(報)). 이 연구(硏究)를 위해서 우리는 정보유통과정(情報流通過程)을 따라 많은 노력(努力)을 하였는데, 여기서 유통과정(流通過程)의 인상적(印象的)인 면목(面目)은 특별(特別)히 연구(硏究)로부터의 정보(情報)는 잡지(雜誌)에 게재(揭載)되기까지 진정으로는 공개적(公開的)이 못된다는 것과 이러한 사실(事實)은 선진연구(先進硏究)가 자주 시대(時代)에 뒤떨어지게 된다는 것을 발견할 수 있었다. 경험(經驗)이 많은 정보(情報)의 수요자(需要者)는 이러한 폐물화(廢物化)에 매우 민감(敏感)하며 자기(自己) 연구(硏究)에 당면한, 진행중(進行中)이거나 최근(最近) 완성(完成)된 연구(硏究)에 대하여 정보(情報)를 얻기 위한 모든 수단(手段)을 발견(發見)코자 하였다. 예를 들어, 이들은 잡지(雜誌)에 보문(報文)을 발표(發表)하기 전(前)에 발생(發生)하는 정보전파과정(情報傳播過程)을 통하여 유루(遺漏)될지도 모르는 정보(情報)를 얻기 위하여 한 잡지(雜誌)나 2차자료(二次資料) 또는 전형적(典型的)으로 이용(利用)되는 다른 잡지류중(雜誌類中)에서 당해정보(當該情報)가 발견(發見)되기를 기다리지 않는다는 것이다. (3) "정보생산 과학자(情報生産 科學者)"에 의한 정보전파(情報傳播)의 계속성(繼續性)(이 연구(硏究) 시리이즈의 결과(結果)는 본고(本稿)의 주내용(主內容)으로 되어 있다.) 1968/1969년(年)부터 1970/1971년(年)의 이년기간(二年期間)동안 보문(報文)을 낸 과학자(科學者)(1968/1969년(年) 잡지중(雜誌中)에 "질이 높은" 보문(報文)을 발표(發表)한)의 약 2/3는 1968/1969의 보문(報文)과 동일(同一)한 대상영역(對象領域)의 연구(硏究)를 계속(繼續) 수행(遂行)하였다. 그래서 우리는 본연구(本硏究)에 오른 대부분(大部分)의 저자(著者)가 정상적(正常的)인 과학(科學), 즉 연구수행중(硏究遂行中) 의문(疑問)에 대한 완전(完全)한 해답(解答)을 얻게 되는 가장 중요(重要)한 추구(追求)로서 Kuhn(제5보(第5報))에 의하여 기술(技術)된 방법(방법)으로 과학(연구)(科學(硏究))을 실행(實行)하였음을 알았다. 최근(最近)에 연구(硏究)를 마치고 그 결과(結果)를 보문(報文)으로서 발표(發表)한 이들 과학자(科學者)들은 다음 단계(段階)로 해야 할 사항(事項)에 대하여 선행(先行)된 동일견해(同一見解)를 가진 다른 연구자(硏究자)들의 연구(硏究)와 대상(對象)에 밀접(密接)하게 관련(關聯)되고 있다. 이 계속성(繼續性)의 효과(效果)에 대한 지표(指標)는 보문(報文)과 동일(同一)한 영역(領域)에서 연구(硏究)를 계속(繼續)한 저자(著者)들의 약 3/4은 선행(先行) 보문(報文)에 기술(技術)된 연구결과(硏究結果)에서 직접적(直接的)으로 새로운 연구(硏究)가 유도(誘導)되었음을 보고(報告)한 사항(事項)에 반영(反映)되어 있다. 그렇지만 우리들의 데이터는 다음 영역(領域)으로 기대(期待)하지 않은 전환(轉換)을 일으킬 수도 있음을 보여주고 있다. 동일(同一) 대상(對象)에서 연구(硏究)를 속행(續行)하였던 저자(著者)들의 1/5 이상(以上)은 뒤에 새로운 영역(領域)으로 연구(硏究)를 전환(轉換)하였고 또한 이 영역(領域)에서 연구(硏究)를 계속(繼續)하였다. 연구영역(硏究領域)의 이러한 변화(變化)는 연구자(硏究者)의 일반(一般) 정보유통(情報流通) 패턴에 크게 변화(變化)를 보이지는 않는다. 즉 새로운 지적(知的) 문제(問題)에 대한 변화(變化)에서 야기(惹起)되는 패턴에 있어서 저자(著者)들은 오래된 문제(問題)의 방법(方法)과 기술(技術)을 새로운 문제(問題)로 맞추려 한다. 과학사(科學史)의 최근(最近) 해석(解釋)(Hanson: 6보(報))에서 예기(豫期)되었던 바와 같이 정상적(正常的)인 과학(科學)의 계속성(繼續性)은 항상 절대적(絶對的)이 아니며 "과학지식(科學知識)"의 첫발자욱은 예전 연구영역(硏究領域)의 대상(對象)에 관계(關係)없이 나타나는 다른 영역(領域)으로 내딛게 될지도 모른다. 우리들의 연구(硏究)에서 저자(著者)의 1/3은 동일(同一) 영역(領域)의 대상(對象)에서 속계적(續繼的)인 연구(硏究)를 수행(遂行)치 않고 새로운 영역(領域)으로 옮아갔다. 우리는 이와 같은 데이터를 (a) 저자(著者)가 각개과학자(各個科學者)의 활동(活動)을 통하여 집중적(集中的)인 과학적(科學的) 노력(努力)을 시험(試驗)할 때 각자(各自)의 연구(硏究)에 대한 많은 양(量)의 계속성(繼續性)이 어떤 진보중(進步中)의 과학분야(科學分野)에서도 나타난다는 것과 (b) 이 계속성(繼續性)은 과학(科學)에 대한 집중적(集中的) 진보(進步)의 필요적(必要的) 특질(特質)이라는 것을 의미한다. 또한 우리는 이 계속성(繼續性)과 관련(關聯)되는 유통문제(流通問題)라는 새로운 대상영역(對象領域)으로 전환(轉換)할 때 연구(硏究)의 각단계(各段階)의 진보(進步)와 새로운 목적(目的)으로 전환시(轉換時) 양자(兩者)가 다 필요(必要)로 하는 각개(各個) 과학자(科學者)의 정보수요(情報需要)를 위한 시간(時間) 소비(消費)라는 것을 탐지(探知)할 수 있다. 이러한 관찰(觀察)은 정보(情報)의 선택제공(選擇提供)시스팀이 현재(現在) 필요(必要)로 하는 정보(情報)의 만족(滿足)을 위하여는 효과적(效果的)으로 매우 융통성(融通性)을 띠어야 한다는 것을 암시(暗示)하는 것이다. 본고(本稿)의 시리이즈에 기술(記述)된 전정보유통(全情報流通) 과정(過程)의 재검토(再檢討) 결과(結果)는 과학자(科學者)들이 항상 그들의 요구(要求)를 조화(調和)시키는 신축성(伸縮性)있는 유통체제(流通體制)를 발전(發展)시켜 왔다는 것을 시사(示唆)해 주고 있다. 이 시스팀은 정보전파(情報傳播) 사항(事項)을 중심(中心)으로 이루어 지며 또한 이 사항(事項)의 대부분(大部分)의 참여자(參與者)는 자기자신(自己自身)이 과학정보(科學情報) 전파자(傳播者)라는 기본적(基本的)인 정보전파체제(情報傳播體制)인 것이다. 그러나 이 과정(過程)의 유통행위(流通行爲)에서 살펴본 바와 같이 우리는 대부분(大部分)의 정보전파자(情報傳播者)가 역시 정보(情報)의 동화자(同化者)-다시 말해서 과학정보(科學情報)의 생산자(生産者)는 정보(情報)의 이용자(利用者)라는 것을 알 수 있다. 이 연구(硏究)에서 전형적(典型的)인 과학자((科學者)는 과학정보(科學情報)의 생산(生産)이나 전파(傳播)의 양자(兩者)에 연속적(連續的)으로 관계(關係)하고 있음을 보았다. 만일(萬一) 연구자(硏究者)가 한 편(編)의 연구(硏究)를 완료(完了)한다면 이 연구자(硏究者)는 다음에 무엇을 할 것이냐 하는 관념(觀念)을 갖게 되고 따라서 "완료(完了)된" 연구(硏究)에 관한 정보(情報)를 이용(利用)하여 동시(同時)에 새로운 일을 시작(始作)하게 된다. 예를 들어, 한 과학자(科學者)가 동일(同一) 영역(領域)의 다른 동료연구자(同僚硏究者)에게 완전(完全)하며 이의(異議)에 방어(防禦)할 수 있는 보고서(報告書)를 제공(提供)할 수 있는 단계(段階)에 도달(到達)하였다면 우리는 이 과학자(科學者)가 정보유통과정(情報流通過程)에서 많은 역할(役割)을 해낼 수 있다는 것을 알 것이다. 즉 이 과학자(科學者)는 다른 과학자(科學者)들에게 최신(最新)의 과학적(科學的) 결과(結果)를 제공(提供)할 때 하나의 과학정보(科學情報) 전파자(傳播者)가 되며, 이 연구(硏究)의 의의(意義)와 타당성(妥當性)에 관한 논평(論評)이나 비평(批評)을 동료(同僚)로부터 구(求)하는 관점(觀點)에서 보면 이 과학자(科學者)는 하나의 정보탐색자(情報探索者)가 된다. 또한 장래(將來)의 이용(利用)을 위하여 증정(贈呈)이나 동화(同化)한 이 정보(情報)로부터 피이드백을 받아 드렸을 때의 범주(範疇)에서 보면 (잡지(雜誌)에 투고(投稿)하기 위하여 원고(原稿)를 작성(作成)하는 경우에 있어서와 같이) 과학자(科學者)는 하나의 정보이용자(情報利用者)가 되고 이러한 모든 가능성(可能性)에서 정보생산자(情報生産者)는 다음 정보생산(情報生産)에 이미 들어가 있다고 볼 수 있다(저자(著者)들의 2/3는 보문(報文)이 게재(揭載)되기 전(前)에 이미 새로운 연구(硏究)를 시작(始作)하였다). 과학자(科學者)가 자기연구(自己硏究)를 마치고 예비보고서(豫備報告書)를 만든 후(後) 자기연구(自己硏究)에 관한 정보(情報)의 전파(傳播)를 계속하게 되는데 이와 관계(關係)되는 일반적(一般的)인 패턴을 보면 소수(少數)의 동료(同僚)그룹에 출석(出席)하는 경우 (예로 지역집담회)(地域集談會))와 대중(大衆) 앞에서 행(行)하는 경우(예로 국가적 회합(國家的 會合)) 등이 있다. 그러는 동안에 다양성(多樣性) 있는 성문보고서(成文報告書)가 이루어진다. 그러나 과학자(科學者)들이 자기연구(自己硏究)를 위한 주정보전파목표(主情報傳播目標)는 과학잡지중(科學雜誌中)에 게재(揭載)되는 보문(報文)이라는 것이 명확(明確)한 사실(事實)인 것이다. 이러한 목표(目標)에 도달(到達)할 때까지의 각(各) 정보전파단계(情報傳播段階)에서 과학자(科學者)들은 목표달성(目標達成)을 위하여 청중(聽衆), 자기동화(自己同化)된 정보(情報) 및 이미 이용(利用)된 정보(情報)로부터 피이드백을 탐색(探索)하게 된다. 우리가 본고(本稿)의 시리이즈중(中)에 표현(表現)하려 했던 바와 같이 이러한 활동(活動)은 조사수임자(調査受任者)의 의견(意見)이 원고(原稿)에 반영(反映)되고 또 그 원고(原稿)가 잡지게재(雜誌揭載)를 위해 수리(受理)될 때까지 계속적(繼續的)으로 정보(情報)를 탐색(探索)하는 과학자(科學者)나 기타(其他)사람들에게 효과적(效果的)이었다. 원고(原稿)가 수리(受理)되면 그 원고(原稿)의 저자(著者)들은 그 보문(報文)의 주내용(主內容)에 대하여 적극적(積極的)인 정보전파자(情報傳播者)로서의 역할(役割)을 종종 중지(中止)하는 일이 있는데 이때에는 저자(著者)들의 역할(役割)이 변화(變化)하는 것을 볼 수 있었다. 즉 이 저자(著者)들은 일시적(一時的)이긴 하나 새로운 일을 착수(着手)하기 위하여 정보(情報)의 동화자(同化者)를 찾게 된다. 또한 전(前)에 행한 일에 대한 의견(意見)이나 비평(批評)이 새로운 일에 영향(影響)을 끼치게 된다. 동시(同時)에 새로운 과학정보생산(科學情報生産) 과정(過程)에 들어가게 되고 현재(現在) 진행중(進行中)이거나 최근(最近) 완료(完了)한 연구(硏究)에 대한 정보(情報)를 항상 찾게 된다. 활발(活潑)한 연구(硏究)를 하는 과학자(科學者)들에게는, 동화자(同化者)로서의 역할(役割)과 전파자(傳播者)로서의 역할(役割)을 분리(分離)시킨다는 것은 실제적(實際的)은 못된다. 즉 후자(後者)를 완성(完成)하기 위해서는 전자(前者)를 이용(利用)하게 된다는 것이다. 과학자(科學者)들은 한 단계(段階)에서 한 전파자(傳播者)로서의 역할(役割)이 뚜렷하나 다른 단계(段階)에서는 정보교환(情報交換)이 기본적(基本的)으로 정보동화(情報同化)에 직결(直結)되고 있는 것이다. 정보전파자(情報傳播者)와 정보동화자간(情報同化者間)의 상호관계(相互關係)(또는 정보생산자(情報生産者)와 정보이용자간(情報利用者間))는 과학(科學)에 있어서 하나의 필수양상(必修樣相)이다. 과학(科學)의 유통구조(流通構造)가 전파자(傳播者)(이용자(利用者)로서의 역할(役割)보다는)의 필요성(必要性)에서 볼 때 복잡(複雜)하고 다이나믹한 시스팀으로 구성(構成)된다는 사실(事實)은 과학(科學)의 발전과정(發展過程)에서 필연적(必然的)으로 나타난다. 이와 같은 사실(事實)은 과학정보(科學情報)의 전파요원(傳播要員)이 국가적 회합(國家的 會合)에서 자기연구(自己硏究)에 대한 정보(情報)의 전파기회(傳播機會)를 거절(拒絶)하고 따라서 전파정보(電波情報)를 판단(判斷)하고 선별(選別)하는 것을 감소(減少)시키며 결과적(結果的)으로 잡지(雜誌)나 단행본(單行本)에서 비평(批評)을 하고 추고(推敲)하는 것이 배제(排除)될 때는 유형적(有形的) 과학(科學)은 급속(急速)히 비과학성(非科學性)을 띠게 된다는 것을 Lysenko의 생애(生涯)에 대한 Medvedev의 기술중(記述中)[7]에 지적(指摘)한 것과 관계(關係)되고 있다.