• Title/Summary/Keyword: Internet application classification

Search Result 142, Processing Time 0.027 seconds

A Research on how to turn informationization Database of construction materials to practical use (건설 자재정보 DataBase의 실용화 방안 연구)

  • Kwon, Oh-Yong;Han, Chung-Han;Lee, Hwa-Young
    • Proceedings of the Korean Institute Of Construction Engineering and Management
    • /
    • 2007.11a
    • /
    • pp.747-750
    • /
    • 2007
  • Information of construction material is served through internet to user but it is poor to use information of construction material because of lack of information which is accumulated and insufficience of standardization. So informationization of civil materials are closely connected with works and then it is promoted to be used through works like design, construction etc. Informationization for management of information of construction material which reflects questionnaires about opinion of workers presents promotion by stage considering first, continuous renewal of information of construction material and increase in quantity, second classification system and standardization of terms in order to share and connect information of construction material third, developing inquiry method of material information needed in construction stage fourth, connecting material information DB and application through design and construction.

  • PDF

A Study on Detection of Small Size Malicious Code using Data Mining Method (데이터 마이닝 기법을 이용한 소규모 악성코드 탐지에 관한 연구)

  • Lee, Taek-Hyun;Kook, Kwang-Ho
    • Convergence Security Journal
    • /
    • v.19 no.1
    • /
    • pp.11-17
    • /
    • 2019
  • Recently, the abuse of Internet technology has caused economic and mental harm to society as a whole. Especially, malicious code that is newly created or modified is used as a basic means of various application hacking and cyber security threats by bypassing the existing information protection system. However, research on small-capacity executable files that occupy a large portion of actual malicious code is rather limited. In this paper, we propose a model that can analyze the characteristics of known small capacity executable files by using data mining techniques and to use them for detecting unknown malicious codes. Data mining analysis techniques were performed in various ways such as Naive Bayesian, SVM, decision tree, random forest, artificial neural network, and the accuracy was compared according to the detection level of virustotal. As a result, more than 80% classification accuracy was verified for 34,646 analysis files.

Custom Metadata Storage Method Using XMP (XMP를 이용한 커스텀 메타데이터 저장 방법)

  • Hyun, Chang-Jong;Kim, Dong-Ho
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.14 no.2
    • /
    • pp.323-330
    • /
    • 2019
  • Recently, as the growth of the Internet has led to a rapid increase in the consumption of multimedia such as photographs and moving images, the importance of metadata has been emphasized. In the case of existing metadata, only limited information such as GPS value or focal length according to the format is stored. However, with the development of mobile devices and multimedia acquisition devices, various sensors can be used in the devices. Therefore, this paper describes a method that can store not only the existing metadata format information at the time of multimedia acquisition but also another existing format of metadata such as information of various sensors which is the gyroscope and acceleration sensor of the device. We propose an application program that provides moving location information. The proposed method is expected to provide various applications such as image matching and effective image classification.

Construction of Onion Sentiment Dictionary using Cluster Analysis (군집분석을 이용한 양파 감성사전 구축)

  • Oh, Seungwon;Kim, Min Soo
    • Journal of the Korean Data Analysis Society
    • /
    • v.20 no.6
    • /
    • pp.2917-2932
    • /
    • 2018
  • Many researches are accomplished as a result of the efforts of developing the production predicting model to solve the supply imbalance of onions which are vegetables very closely related to Korean food. But considering the possibility of storing onions, it is very difficult to solve the supply imbalance of onions only with predicting the production. So, this paper's purpose is trying to build a sentiment dictionary to predict the price of onions by using the internet articles which include the informations about the production of onions and various factors of the price, and these articles are very easy to access on our daily lives. Articles about onions are from 2012 to 2016, using TF-IDF for comparing with four kinds of TF-IDFs through the documents classification of wholesale prices of onions. As a result of classifying the positive/negative words for price by k-means clustering, DBSCAN (density based spatial cluster application with noise) clustering, GMM (Gaussian mixture model) clustering which are partitional clustering, GMM clustering is composed with three meaningful dictionaries. To compare the reasonability of these built dictionary, applying classified articles about the rise and drop of the price on logistic regression, and it shows 85.7% accuracy.

Curriculum of IoT by IPC Code Analysis of Patents (특허문헌의 IPC 코드 분석에 의한 사물인터넷 분야 교육과정에 관한 연구)

  • Shim, Jaeruen;Choi, Jin-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.25 no.11
    • /
    • pp.1642-1648
    • /
    • 2021
  • We analyzes representative technologies of IoT patents and reflects these results in the curriculum of IoT. In order to identify the representative technologies, the IPC codes of the patents were analyzed. Among the main category IPC codes, the most used IPC codes were H04L in Single IPC Patent with 974 cases(32.0%) and G06Q in Multiple IPC Patent with 710 cases(29.2%). As a result of classifying the IPC code into the WIPO technology classification system, the most emphasized technologies are Digital Communication, accounting for about 60.5% in the Single IPC Patent and IT Methods for Management(710 cases, 29.2%) in Multiple IPC Patent. The main points to be considered when organizing the curriculum of IoT are: ∇Emphasis on Digital Communication, ∇Expansion of Education related to IT Methods for Management(Including entrepreneurship and patent application), and ∇Consideration of subjects related to the Convergence of IoT. This research can contribute to the curriculum design of new industrial technologies such as AI and Fintech.

Study on Basic Elements for Smart Content through the Market Status-quo (스마트콘텐츠 현황분석을 통한 기본요소 추출)

  • Kim, Gyoung Sun;Park, Joo Young;Kim, Yi Yeon
    • Korea Science and Art Forum
    • /
    • v.21
    • /
    • pp.31-43
    • /
    • 2015
  • Information and Communications Technology (ICT) is one of the technologies which represent the core value of the creative economy. It has served as a vehicle connecting the existing industry and corporate infrastructure, developing existing products and services and creating new products and services. In addition to the ICT, new devices including big data, mobile gadgets and wearable products are gaining a great attention sending an expectation for a new market-pioneering. Further, Internet of Things (IoT) is helping solidify the ICT-based social development connecting human-to-human, human-to-things and things-to-things. This means that the manufacturing-based hardware development needs to be achieved simultaneously with software development through convergence. The essential element the convergence between hardware and software is OS, for which world's leading companies such as Google and Apple have launched an intense development recognizing the importance of software. Against this backdrop, the status-quo of the software market has been examined for the study of the present report (Korea Evaluation Institute of Industrial Technology: Professional Design Technology Development Project). As a result, the software platform-based Google's android and Apple's iOS are dominant in the global market and late comers are trying to enter the market through various pathways by releasing web-based OS and similar OS to provide a new paradigm to the market. The present study is aimed at finding the way to utilize a smart content by which anyone can be a developer based on OS responding to such as social change, newly defining a smart content to be universally utilized and analyzing the market to deal with a rapid market change. The study method, scope and details are as follows: Literature investigation, Analysis on the app market according to a smart classification system, Trend analysis on the current content market, Identification of five common trends through comparison among the universal definition of smart content, the status-quo of application represented in the app market and content market situation. In conclusion, the smart content market is independent but is expected to develop in the form of a single organic body being connected each other. Therefore, the further classification system and development focus should be made in a way to see the area from multiple perspectives including a social point of view in terms of the existing technology, culture, business and consumers.

Chatbot Design Method Using Hybrid Word Vector Expression Model Based on Real Telemarketing Data

  • Zhang, Jie;Zhang, Jianing;Ma, Shuhao;Yang, Jie;Gui, Guan
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.14 no.4
    • /
    • pp.1400-1418
    • /
    • 2020
  • In the development of commercial promotion, chatbot is known as one of significant skill by application of natural language processing (NLP). Conventional design methods are using bag-of-words model (BOW) alone based on Google database and other online corpus. For one thing, in the bag-of-words model, the vectors are Irrelevant to one another. Even though this method is friendly to discrete features, it is not conducive to the machine to understand continuous statements due to the loss of the connection between words in the encoded word vector. For other thing, existing methods are used to test in state-of-the-art online corpus but it is hard to apply in real applications such as telemarketing data. In this paper, we propose an improved chatbot design way using hybrid bag-of-words model and skip-gram model based on the real telemarketing data. Specifically, we first collect the real data in the telemarketing field and perform data cleaning and data classification on the constructed corpus. Second, the word representation is adopted hybrid bag-of-words model and skip-gram model. The skip-gram model maps synonyms in the vicinity of vector space. The correlation between words is expressed, so the amount of information contained in the word vector is increased, making up for the shortcomings caused by using bag-of-words model alone. Third, we use the term frequency-inverse document frequency (TF-IDF) weighting method to improve the weight of key words, then output the final word expression. At last, the answer is produced using hybrid retrieval model and generate model. The retrieval model can accurately answer questions in the field. The generate model can supplement the question of answering the open domain, in which the answer to the final reply is completed by long-short term memory (LSTM) training and prediction. Experimental results show which the hybrid word vector expression model can improve the accuracy of the response and the whole system can communicate with humans.

Application of Advertisement Filtering Model and Method for its Performance Improvement (광고 글 필터링 모델 적용 및 성능 향상 방안)

  • Park, Raegeun;Yun, Hyeok-Jin;Shin, Ui-Cheol;Ahn, Young-Jin;Jeong, Seungdo
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.21 no.11
    • /
    • pp.1-8
    • /
    • 2020
  • In recent years, due to the exponential increase in internet data, many fields such as deep learning have developed, but side effects generated as commercial advertisements, such as viral marketing, have been discovered. This not only damages the essence of the internet for sharing high-quality information, but also causes problems that increase users' search times to acquire high-quality information. In this study, we define advertisement as "a text that obscures the essence of information transmission" and we propose a model for filtering information according to that definition. The proposed model consists of advertisement filtering and advertisement filtering performance improvement and is designed to continuously improve performance. We collected data for filtering advertisements and learned document classification using KorBERT. Experiments were conducted to verify the performance of this model. For data combining five topics, accuracy and precision were 89.2% and 84.3%, respectively. High performance was confirmed, even if atypical characteristics of advertisements are considered. This approach is expected to reduce wasted time and fatigue in searching for information, because our model effectively delivers high-quality information to users through a process of determining and filtering advertisement paragraphs.

A Study on Efficient AI Model Drift Detection Methods for MLOps (MLOps를 위한 효율적인 AI 모델 드리프트 탐지방안 연구)

  • Ye-eun Lee;Tae-jin Lee
    • Journal of Internet Computing and Services
    • /
    • v.24 no.5
    • /
    • pp.17-27
    • /
    • 2023
  • Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.

A Study on the Transformation of Traditional Laboratories into Instructional Media Centers for Education of Library and Information Science (문헌정보학 실습실의 교수매체 센터화에 관한 연구)

  • Lee, Man-Soo
    • Journal of the Korean Society for Library and Information Science
    • /
    • v.34 no.1
    • /
    • pp.265-295
    • /
    • 2000
  • Education of library and information science must focus on practical education acted upon as a laboratory room in the characteristics of learning, because it cultivates a librarian as an information expert who can conduct professional affairs and services, applying traditional theory to the practical business of library and information. This dissertation suggested a new paradigm of an instructional media center as an advanced laboratory room which faithfully can run the curriculum of a library and information science for cultivating librarians, information experts who can satisfy the 21C information society. To carry out this purpose, I considered the various opinions of professors and librarians, after investigating and analyzing facilities and furnishings of laboratory rooms and teaching and learning data related to departments of library and information science in 32 universities. These contents can be summarized as follows : 1) Constructional media centers connected to education of library and information science sets laboratory rooms for practical classification and cataloging classes; laboratory rooms for film media which can utilize advanced media, listening tools, and practical materials; information management laboratory rooms which can experience the various information research methods through the Internet, cultivate the ability of information application, and teach the curriculum of library and information science related to computers. 2) Arrangement plans linked to laboratory rooms for classification and cataloging, one for film media, and one for information proceedings are as follows: , , and . 3) The size of each room is $162m^2$ (49.1pying); the number of persons to be admitted is about 40 to 50; each room has one media expert and one assistant as operating manager of exclusive responsibility. 4) Instructional & learning data which must be contained as instructional media of library and information science include computers, marginal tools related to it, listening materials, supplies for ordering books, teaching aids containing various equipment and tools, textbooks for practice, books connected to classification and cataloging for practice, and textbooks related to practical subjects and reference books. 5) Industrial media centers belonging to library and information science require for practice, general furnishings like bookshelves, and various material depository boxes.

  • PDF