• Journal of Technology Innovation
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• v.26 no.4
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• pp.199-232
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• 2018

There are increasing needs for understanding and fathoming of business management environment through big data analysis at industrial and corporative level. The research using the company disclosure information, which is comprehensively covering the business performance and the future plan of the company, is getting attention. However, there is limited research on developing applicable analytical models leveraging such corporate disclosure data due to its unstructured nature. This study proposes a text-mining-based analytical model for industrial and firm level analyses using publicly available company disclousre data. Specifically, we apply LDA topic model and word2vec word embedding model on the U.S. SEC data from the publicly listed firms and analyze the trends of business topics at the industrial and corporate levels. Using LDA topic modeling based on SEC EDGAR 10-K document, whole industrial management topics are figured out. For comparison of different pattern of industries' topic trend, software and hardware industries are compared in recent 20 years. Also, the changes of management subject at firm level are observed with comparison of two companies in software industry. The changes of topic trends provides lens for identifying decreasing and growing management subjects at industrial and firm level. Mapping companies and products(or services) based on dimension reduction after using word2vec word embedding model and principal component analysis of 10-K document at firm level in software industry, companies and products(services) that have similar management subjects are identified and also their changes in decades. For suggesting methodology to develop analysis model based on public management data at industrial and corporate level, there may be contributions in terms of making ground of practical methodology to identifying changes of managements subjects. However, there are required further researches to provide microscopic analytical model with regard to relation of technology management strategy between management performance in case of related to various pattern of management topics as of frequent changes of management subject or their momentum. Also more studies are needed for developing competitive context analysis model with product(service)-portfolios between firms.

• 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 the Speleological Society of Korea
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• no.68
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• pp.23-73
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• 2005

Purpose of study; The purpose of this study is specifically classified as two parts. The one is to attempt the chronological annals of Quaternary topographic surface through the study over the formation process of alluvial surfaces in our country, setting forth the alluvial surfaces lower-parts of Han River area, as the basic deposit, and comparing it to the marginal landform surfaces. The other is to attempt the classification of micro morphology based on the and condition premising the land use as a link for the regional development in the lower-parts of Han river area. Reasons why selected the Lower-parts of Han river area as study objects: 1. The change of river course in this area is very serve both in vertical and horizontal sides. With a situation it is very easy to know about the old geography related to the formation process of topography. 2. The component materials of gravel, sand, silt and clay are deposited in this area. Making it the available data, it is possible to consider about not oかy the formation process of topography but alsoon the development history to some extent. 3. The earthen vessel, a fossil shell fish, bone, cnarcoal and sea-weed are included in the alluvial deposition in this area. These can be also valuable data related to the chronological annals. 4. The bottom set conglometate beds is also included in the alluvial deposits. This can be also valuable data related to the research of geomorphological development. 5. Around of this area the medium landform surface, lower landform surface, pediment and basin, are existed, and these enable the comparison between the erosion surfaces and the alluvial surfaces. Approach : 1. Referring to the change of river beds, I have calculated the vertical and horizontal differences comparing the topographic map published in 1916 with that published in 1966 and through the field work 2. In classifying the landform, I have applied the method of micro morphological classification in accordance with the synthetic index based upon the land conditions, and furthermore used the classification method comparing the topographic map published in 1916 and in that of 1966. 3. I have accorded this classification with the classification by mapping through appliying the method of classification in the development history for the field work making the component materials as the available data. 4. I have used the component materials, which were picked up form the outcrop of 10 places and bored at 5 places, as the available data. 5. I have referred to Hydrological survey data of the ministry of Construction (since 1916) on the overflow of Han-river, and used geologic map of Seoul metropolitan area. Survey Data, and general map published in 1916 by the Japanese Army Survbey Dept., and map published in 1966 by the Construction Research Laboratory and ROK Army Survey Dept., respectively. Conclusion: 1. Classification of Morphology: I have added the historical consideration for development, making the component materials and fossil as the data, to the typical consideration in accordance with the map of summit level, reliefe and slope distribution. In connection with the erosion surface, I have divided into three classification such as high, medium and low-,level landform surfaces which were classified as high and low level landform surfaces in past. furthermore I have divided the low level landform surface two parts, namely upper-parts(200-300m) and bellow-parts(${\pm}100m$). Accordingly, we can recognize the three-parts of erosion surface including the medium level landform surface (500-600m) in this area. (see table 22). In condition with the alluvial surfaces I have classified as two landform surfaces (old and new) which was regarded as one face in past. Meamwhile, under the premise of land use, the synthetic, micro morphological classification based upon the land condition is as per the draw No. 19-1. This is the quite new method of classification which was at first attempted in this country. 2. I have learned that the change of river was most severe at seeing the river meandering rate from Dangjung-ni to Nanjido. As you seee the table and the vertical and horizontal change of river beds is justly proportionable to the river meandering rate. 3. It can be learned at seeing the analysis of component materials of alluvial deposits that the component from each other by areas, however, in the deposits relationship upper stream, and between upper parts and below parts I couldn't always find out the regular ones. 4. Having earthern vessel, shell bone, fossil charcoal and and seaweeds includen in the component materials such as gravel, clay, sand and silt in Dukso and Songpa deposits area. I have become to attempt the compilation of chronicle as yon see in the table 22. 5. In according to hearing of basemen excavation, the bottom set conglomerate beds of Dukso beds of Dukso-beds is 7m and Songpa-beds is 10m. In according to information of dredger it is approx. 20m in the down stream. 6. Making these two beds as the standard beds, I have compared it to other beds. 7 The coarse sand beds which is covering the clay-beds of Dukso-beds and Nanjidobeds is shown the existence of so-called erosion period which formed the gap among the alluvial deposits of stratum. The former has been proved by the sorting, bedding and roundness which was supplied by the main stream and later by the branch stream, respectively. 8. If the clay-beds of Dukeo-bed and Songpa-bed is called as being transgressive overlap, by the Eustatic movement after glacial age, the bottom set conglomerate beds shall be called as being regressive overlap at the holocene. This has the closest relationship with the basin formation movement of Seoul besides the Eustatic movement. 9. The silt-beds which is the main component of deposits of flood plain, is regarded as being deposited at the Holocene in the comb ceramic and plain pottery ages. This has the closest relationship with the change of river course and river beds.