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An Empirical Assessment of Competency Requirements for Logistics Managers of Freight Forwarding Companies (복합운송주선업 물류관리자의 자격요건에 관한 연구)

  • Kim, Jin-Su;Hong, Eui
    • International Commerce and Information Review
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    • v.14 no.2
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    • pp.147-172
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    • 2012
  • The aim of this research is to identify the competencies required by freight forwarding company logistics managers or supply chain managers. And this research also attempts to show their relative importance and key knowledge areas that require improvement. Using a survey questionnaire, data was collected against forty three logistics and supply chain management skills or competencies, which were then grouped into four categories and analysed. The Analysis revealed that supply chain awareness, ability to make decisions, analytical skill, communication skill, supply chain cost, people skill, and integration of internal or external information flow which belong to logistics planning group are considered the most important competencies for effective and efficient logistics functioning. On the other hand, reverse logistics and IATA regulations from environmental awareness group show little influence on logistics managers for improving their logistics performances. The results have implications for a variety of parties including prospective logisticians, students, teachers and companies considering expanding their business to Chinese market. For example, the results permit companies to employ appropriate logistics managers who are qualified with sufficient skills and competencies suggested in this research. In the case of practitioners, the results provide a benchmark for comparison with their current level of abilities and suggested competencies.

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The Generic Terms and the Standards of a Delimitation for Oceans and Seas based on S-23(Names and Limits of Oceans and Seas) (S-23(Names and Limits of Oceans and Seas)을 기초로 한 바다의 속성지명과 바다경계의 획정 근거 분석)

  • Sung, Hyo Hyun;Kang, Jihyun
    • Journal of the Korean Geographical Society
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    • v.48 no.6
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    • pp.914-928
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    • 2013
  • Establishment of limits and names for oceans and seas is necessary for a safety of navigation. Even if there are no national and international standard for the delimitation of sea boundaries, we can take guidelines for the delimitation of sea boundaries through the analysis of IHO official publications, Limits and Names for Oceans and Sea; S-23. This paper shows the changes of the spatial limit of seas since first edition publication, and the standards for a delimitation of oceans and seas were analyzed using S-23 4th edition draft(2002) in terms of physical geographic features. The generic terms of S-23 include Ocean, Sea, Channel, Passage, Strait, Sound, Gulf, Bay and Bight, and each generic term shows hierarchical structures. Several seas show different characteristics compared with definitions of IHO dictionary. Sea boundaries are delimited by longitude and latitude, cape, river mouth, sandbar, and so on. Undersea features such as a shelf, trench, trough, rise, bank and reef are also important features for delimitation of sea boundary. Especially, seas that are delimited by undersea feature are mainly located Arctic and Southern ocean area in S-23 4th edition. Advanced knowledge of marine science with a technical advance might affect to delimit for sea boundary.

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The Historical Understanding of the U. S. Secret Records Management (미국의 비밀기록관리체제에 대한 역사적 이해)

  • Lee, Kyong-Rae
    • The Korean Journal of Archival Studies
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    • no.23
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    • pp.257-297
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    • 2010
  • The U. S. government has a long history to classify and manage governmental records which are created, collected, and preserved for itself. During the colonial period before the independence, the U. S. mostly practiced the maintenances of secret records and restrictions of access to the records following a long convention without any specific legal authority. Since establishment of the U. S. Constitution, the government had kept secret records on the basis of constitutional authority. However, the U. S. government began to take shape the secret records management system when it participated in the World War I, which required the system to reflect the needs in reality to manage drastic increases in important military and foreign relation documents. The World War II made the U. S. government strengthen its secret records management system, and its conception of secret records management system at that time has sustained until now. It can be said that the current secret records management system of the U. S. government continues to be managed by constitutional authorities and the executive orders which are opt to change. This article intends to review the secret records management system of the U. S. from the initial history of the U. S. to the Cold War. To understand its system of secret management, the paper investigates the U. S. secret records management history by dividing into three periods: the period of establishment of its tradition(the Colonial era~just before the WWI); the period of taking shape of its system (the WWI~the WWII); and the period of current conception of its system. The criteria of these divisions are created based on the differences of the laws relevant to the secret records and the application methods of secret management system in reality.

A Study on the Elaboration of Request for Proposal of Localization Parts using AHP method (AHP 기법을 적용한 부품국산화 제안요청서 정교화 연구)

  • Song, Hyeong-Min
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.1
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    • pp.35-44
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    • 2020
  • The purpose of this study is to elaborate the request for proposal (RFP) for the localization parts development support project of core parts carried out by the Defense Agency for Technology and Quality. The RFP is the most important document throughout the localization parts project, including project announcement and developer selection, design and test of the development product, final evaluation, and standardization of the project. However, if the RFP is not established at the beginning of the project, there is an increased risk of business failure due to frequent changes by various reasons. In this study, we recognized the necessity of elaboration of RFP and applied the AHP method for quantitative elaboration. Eight requirements of the RFP related to the mechanical/electrical performance of localized development products and three elaboration methods for each requirement were designed in a hierarchical structure, and each weight was calculated by applying the 5-point scale AHP method. The AHP survey was conducted with 20 developers participating in the localization parts project, and the consistency ratio of the AHP survey result was less than 0.1. The elaboration method with the highest value among the calculated weights is classified, and the analysis results and future research directions of the elaboration method are presented.

Design and Implementation of MongoDB-based Unstructured Log Processing System over Cloud Computing Environment (클라우드 환경에서 MongoDB 기반의 비정형 로그 처리 시스템 설계 및 구현)

  • Kim, Myoungjin;Han, Seungho;Cui, Yun;Lee, Hanku
    • 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.

Locational Analysis and Classification of the Eup-Settlements in the Joseon Dynasty Period from Feng-Shui's Point of View (조선시대 지방도시의 풍수적 입지분석과 경관유형- 경상도 71개 읍치를 대상으로 -)

  • Choi, Won-Suk
    • Journal of the Korean Geographical Society
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    • v.42 no.4
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    • pp.540-559
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    • 2007
  • The purpose of this paper is to analyse the locations and to interpret the landscapes of the local towns in Joseon Dynasty from Feng-shui's point of view. As a result of analysing the locations of towns in Gyeongsang Province, the towns which have typical Feng-shui landscapes make up to 58% of the total. Historically, the local towns that were established in the early period of the Joseon Dynasty didn't reveal Feng-shui's landscape, but those that were established in the late period of the Joseon Dynasty revealed the Feng-shui's landscape clearly. In this article, I classify the local towns of the Gyeongsang Province into 3 types: 1. Non Feng-shui type These towns are located near the seashore. The main reason that these towns were located at the seashore was defense against an enemy. 2. Semi Feng-shui type. These towns don't have natural location but have a man-made landscape, based on the principles of Feng-shui. 3. Typical Feng-shui type. These towns were typically administrational towns which were located at the center of a local region.

Term Mapping Methodology between Everyday Words and Legal Terms for Law Information Search System (법령정보 검색을 위한 생활용어와 법률용어 간의 대응관계 탐색 방법론)

  • Kim, Ji Hyun;Lee, Jong-Seo;Lee, Myungjin;Kim, Wooju;Hong, June Seok
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.137-152
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    • 2012
  • In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

Methodology for Identifying Issues of User Reviews from the Perspective of Evaluation Criteria: Focus on a Hotel Information Site (사용자 리뷰의 평가기준 별 이슈 식별 방법론: 호텔 리뷰 사이트를 중심으로)

  • Byun, Sungho;Lee, Donghoon;Kim, Namgyu
    • Journal of Intelligence and Information Systems
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    • v.22 no.3
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    • pp.23-43
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    • 2016
  • As a result of the growth of Internet data and the rapid development of Internet technology, "big data" analysis has gained prominence as a major approach for evaluating and mining enormous data for various purposes. Especially, in recent years, people tend to share their experiences related to their leisure activities while also reviewing others' inputs concerning their activities. Therefore, by referring to others' leisure activity-related experiences, they are able to gather information that might guarantee them better leisure activities in the future. This phenomenon has appeared throughout many aspects of leisure activities such as movies, traveling, accommodation, and dining. Apart from blogs and social networking sites, many other websites provide a wealth of information related to leisure activities. Most of these websites provide information of each product in various formats depending on different purposes and perspectives. Generally, most of the websites provide the average ratings and detailed reviews of users who actually used products/services, and these ratings and reviews can actually support the decision of potential customers in purchasing the same products/services. However, the existing websites offering information on leisure activities only provide the rating and review based on one stage of a set of evaluation criteria. Therefore, to identify the main issue for each evaluation criterion as well as the characteristics of specific elements comprising each criterion, users have to read a large number of reviews. In particular, as most of the users search for the characteristics of the detailed elements for one or more specific evaluation criteria based on their priorities, they must spend a great deal of time and effort to obtain the desired information by reading more reviews and understanding the contents of such reviews. Although some websites break down the evaluation criteria and direct the user to input their reviews according to different levels of criteria, there exist excessive amounts of input sections that make the whole process inconvenient for the users. Further, problems may arise if a user does not follow the instructions for the input sections or fill in the wrong input sections. Finally, treating the evaluation criteria breakdown as a realistic alternative is difficult, because identifying all the detailed criteria for each evaluation criterion is a challenging task. For example, if a review about a certain hotel has been written, people tend to only write one-stage reviews for various components such as accessibility, rooms, services, or food. These might be the reviews for most frequently asked questions, such as distance between the nearest subway station or condition of the bathroom, but they still lack detailed information for these questions. In addition, in case a breakdown of the evaluation criteria was provided along with various input sections, the user might only fill in the evaluation criterion for accessibility or fill in the wrong information such as information regarding rooms in the evaluation criteria for accessibility. Thus, the reliability of the segmented review will be greatly reduced. In this study, we propose an approach to overcome the limitations of the existing leisure activity information websites, namely, (1) the reliability of reviews for each evaluation criteria and (2) the difficulty of identifying the detailed contents that make up the evaluation criteria. In our proposed methodology, we first identify the review content and construct the lexicon for each evaluation criterion by using the terms that are frequently used for each criterion. Next, the sentences in the review documents containing the terms in the constructed lexicon are decomposed into review units, which are then reconstructed by using the evaluation criteria. Finally, the issues of the constructed review units by evaluation criteria are derived and the summary results are provided. Apart from the derived issues, the review units are also provided. Therefore, this approach aims to help users save on time and effort, because they will only be reading the relevant information they need for each evaluation criterion rather than go through the entire text of review. Our proposed methodology is based on the topic modeling, which is being actively used in text analysis. The review is decomposed into sentence units rather than considering the whole review as a document unit. After being decomposed into individual review units, the review units are reorganized according to each evaluation criterion and then used in the subsequent analysis. This work largely differs from the existing topic modeling-based studies. In this paper, we collected 423 reviews from hotel information websites and decomposed these reviews into 4,860 review units. We then reorganized the review units according to six different evaluation criteria. By applying these review units in our methodology, the analysis results can be introduced, and the utility of proposed methodology can be demonstrated.

Discovering Promising Convergence Technologies Using Network Analysis of Maturity and Dependency of Technology (기술 성숙도 및 의존도의 네트워크 분석을 통한 유망 융합 기술 발굴 방법론)

  • Choi, Hochang;Kwahk, Kee-Young;Kim, Namgyu
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.101-124
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    • 2018
  • Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

Development of Topic Trend Analysis Model for Industrial Intelligence using Public Data (텍스트마이닝을 활용한 공개데이터 기반 기업 및 산업 토픽추이분석 모델 제안)

  • Park, Sunyoung;Lee, Gene Moo;Kim, You-Eil;Seo, Jinny
    • 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.