• Title/Summary/Keyword: 제목 생성

Search Result 42, Processing Time 0.023 seconds

Ontology-based Machine Translation Mashup System for Public Information (온톨로지 기반 공공정보 번역 매쉬업 시스템)

  • Oh, Kyeong-Jin;Kwon, Kee-Young;Hong, Myung-Duk;Jo, Geun-Sik
    • Journal of the Korea Society of Computer and Information
    • /
    • v.17 no.8
    • /
    • pp.21-29
    • /
    • 2012
  • We have proposed an ontology-based translation mashup system for foreigner to enjoy Korean cultural information without any language barrier(linguistic problem). In order to utilize public information, we use a mobile public information open API of Seoul metropolitan city. Google AJAX language API is used for translations of public information. We apply an ontology to minimize errors caused by the translations. For ontology modeling, we analyze the public information domain and define classes, relations and properties of cultural vocabulary ontology. We generate ontology instances for titles, places and sponsors which are the most frequently occurring translation errors. We compare the accuracy of translations through our experiment. Through the experimental results using the proposed ontology-based translation mashup system, we verify the validity of the system.

Topic Analysis of the National Petition Site and Prediction of Answerable Petitions Based on Deep Learning (국민청원 주제 분석 및 딥러닝 기반 답변 가능 청원 예측)

  • Woo, Yun Hui;Kim, Hyon Hee
    • KIPS Transactions on Software and Data Engineering
    • /
    • v.9 no.2
    • /
    • pp.45-52
    • /
    • 2020
  • Since the opening of the national petition site, it has attracted much attention. In this paper, we perform topic analysis of the national petition site and propose a prediction model for answerable petitions based on deep learning. First, 1,500 petitions are collected, topics are extracted based on the petitions' contents. Main subjects are defined using K-means clustering algorithm, and detailed subjects are defined using topic modeling of petitions belonging to the main subjects. Also, long short-term memory (LSTM) is used for prediction of answerable petitions. Not only title and contents but also categories, length of text, and ratio of part of speech such as noun, adjective, adverb, verb are also used for the proposed model. Our experimental results show that the type 2 model using other features such as ratio of part of speech, length of text, and categories outperforms the type 1 model without other features.

Post Clustering Method using Tag Hierarchy for Blog Search (블로그 검색에서의 태그 계층구조를 이용한 포스트 군집화)

  • Lee, Ki-Jun;Kim, Kyung-Min;Lee, Myung-Jin;Kim, Woo-Ju;Hong, June-S.
    • The Journal of Society for e-Business Studies
    • /
    • v.16 no.4
    • /
    • pp.301-319
    • /
    • 2011
  • Blog plays an important role as new type of knowledge base distinguishing from traditional web resource. While information resources in their existing website dealt with a wide range of topics, information resources of the blog are concentrated in specific units of information depending on the user's interests and have the criteria of classification forresources published by tagging. In this research, we build a tag hierarchy utilizing title keywords and tags of the blog, and propose apost clustering methodology applying the tag hierarchy. We then generate the tag hierarchy reflected the relationship between tags and develop the tag clustering methodology according to tag similarity. In this paper, we analyze the possibility of applying the proposed methodology with real-world examples and evaluate its performances through developed prototype system.

A Study on the Analysis of Intellectual Structure of Korean Veterinary Sciences (국내 수의과학 분야의 지적 구조 분석에 관한 연구)

  • Cho, Hyun-Yang
    • Journal of Information Management
    • /
    • v.43 no.2
    • /
    • pp.43-66
    • /
    • 2012
  • The purpose of this study is to see the intellectual structure in the field of veterinary sciences in Korea, using author profiling analysis(APA), a bibliometric approach. Three journals are selected on the basis of citation data, exchanging most citations with Korean Journal of Veterinary. And then, 50 authors who published most articles at selected journals during the given period of time were chosen. The analysis of similarity and dissimilarity among authors by comparing co-word appearance patterns from article title, abstracts, and keywords was made. Authors can be grouped 11 minor clusters under 4 major clusters, depending on their interests in the area of veterinary sciences in Korea. The subjects for each cluster at the veterinary sciences are decided by the matching the keyword, representing author's research interest. As a result, it is possible to figure out the current research trends and the researcher network in the field of veterinary sciences.

A Study on the Development of Korean Defense Standards through Text Mining-Based Trend Analysis of United States Defense Standards (텍스트 마이닝 기반의 미국 국방 표준 동향 분석을 통한 한국 국방 표준의 발전 방안 연구)

  • Chae, Soohwan;Shim, Bohyun;Yeom, Seulki;Hong, Seongdon
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.22 no.3
    • /
    • pp.651-660
    • /
    • 2021
  • This study examined the trend of standards established in the United States and to find points that can be applied to Korean defense standards. The titles of various United States defense standard documents registered on the web were selected for this research. The wordcloud was created after analyzing the frequency of words appearing in the title using text mining. The trend of words appearing in MIL-STD by era was obtained. This study identified words that appear often due to the format of the document itself, words that appear regularly throughout the era, words that are used frequently in the past but are not used much in the present, and words that did not receive attention in the past but appeared recurrently in the present. In addition, the characteristics of each document were derived through the wordcloud produced for various defense documents. In conclusion, Korean defense standards also require a consideration of safe and efficient management, transport, and load design of hazardous materials. Furthermore, the quality of defense standards can be expected to improve if the defense standard document system can be established, focusing on efficient management.

Ontology Modeling and Rule-based Reasoning for Automatic Classification of Personal Media (미디어 영상 자동 분류를 위한 온톨로지 모델링 및 규칙 기반 추론)

  • Park, Hyun-Kyu;So, Chi-Seung;Park, Young-Tack
    • Journal of KIISE
    • /
    • v.43 no.3
    • /
    • pp.370-379
    • /
    • 2016
  • Recently personal media were produced in a variety of ways as a lot of smart devices have been spread and services using these data have been desired. Therefore, research has been actively conducted for the media analysis and recognition technology and we can recognize the meaningful object from the media. The system using the media ontology has the disadvantage that can't classify the media appearing in the video because of the use of a video title, tags, and script information. In this paper, we propose a system to automatically classify video using the objects shown in the media data. To do this, we use a description logic-based reasoning and a rule-based inference for event processing which may vary in order. Description logic-based reasoning system proposed in this paper represents the relation of the objects in the media as activity ontology. We describe how to another rule-based reasoning system defines an event according to the order of the inference activity and order based reasoning system automatically classify the appropriate event to the category. To evaluate the efficiency of the proposed approach, we conducted an experiment using the media data classified as a valid category by the analysis of the Youtube video.

Building Korean Science Textbook Corpus (K-STeC) for research of Scientific Language in Education (교육용 과학언어 연구를 위한 범용 자료로서 과학교과서 말뭉치 K-STeC(Korean Science Textbook Corpus) 구축)

  • Yun, Eunjeong;Kim, Jinho;Nam, Kilim;Song, Hyunju;Ok, Cheolyoung;Choi, Jun;Park, Yunebae
    • Journal of The Korean Association For Science Education
    • /
    • v.38 no.4
    • /
    • pp.575-585
    • /
    • 2018
  • In this study, the texts of science textbooks of the past 20 years were collected in order to systematically carry out researches on scientific languages and scientific terms that have not been noticed in science education. We have collected all the science textbooks from elementary school to high school in the 6th curriculum, the 7th curriculum, and the 2009 revised curriculum, and constructed a corpus comprising of 132 textbooks in total. Sequentially, a raw corpus, a morphological annotated corpus, and a semantic annotated corpus of science terms, were constructed. The final constructed science textbook corpus was named K-STeC (Korean Science Textbook Corpus). K-STeC is a semantic annotated corpus with semantic classification and classification of scientific terms, together with meta information of bibliographic information such as curriculum, subject, grade, and publisher, location information such as chapter, section, lesson, page, and sentence, and structure information such as main, inquiry activities, reference materials, and titles. Throughout the three-year study period, a new research method was created by integrating the know-how of the three fields of linguistic informatics, computer science and science education, and a large number of experts were put in to produce labor-intensive results. This paper introduces new research methodologies and outcomes by looking at the whole research process and methods, and discusses the possibility of future development of scientific language research and how to use the results.

A Study on the Research Trends on Domestic Platform Government using Topic Modeling (토픽 모델링을 활용한 한국의 플랫폼정부 연구동향 분석)

  • Suh, Byung-Jo;Shin, Sun-Young
    • Informatization Policy
    • /
    • v.24 no.3
    • /
    • pp.3-26
    • /
    • 2017
  • The amount of unstructured data generated online is increasing exponentially and the analysis of text data is being done in various fields. In order to identify the research trends on the platform government, the title, year, academic society, and abstract information of the academic papers on the subject of platform government were collected from the database of the domestic papers, DBPIA(www.dbpia.co.kr). The results of the existing research on the platform government and related fields were analyzed based on each stage of the national informatization promotion. The technology, service, and governance topics were extracted from papers on platform government and the trends of core topics were analyzed by year. Entering the era of the intelligent information society, this study has significance for providing the basis for defining a new role of government - the platform government that sets the stage for the private sector to lead the innovation, and plays the role of an 'enabler' and 'facilitator' instead. The purpose of this study is to understand the platform government research through objective analysis of its trends. Looking for future directions, this study will contribute to future research by providing reference materials.

KOMUChat: Korean Online Community Dialogue Dataset for AI Learning (KOMUChat : 인공지능 학습을 위한 온라인 커뮤니티 대화 데이터셋 연구)

  • YongSang Yoo;MinHwa Jung;SeungMin Lee;Min Song
    • Journal of Intelligence and Information Systems
    • /
    • v.29 no.2
    • /
    • pp.219-240
    • /
    • 2023
  • Conversational AI which allows users to interact with satisfaction is a long-standing research topic. To develop conversational AI, it is necessary to build training data that reflects real conversations between people, but current Korean datasets are not in question-answer format or use honorifics, making it difficult for users to feel closeness. In this paper, we propose a conversation dataset (KOMUChat) consisting of 30,767 question-answer sentence pairs collected from online communities. The question-answer pairs were collected from post titles and first comments of love and relationship counsel boards used by men and women. In addition, we removed abuse records through automatic and manual cleansing to build high quality dataset. To verify the validity of KOMUChat, we compared and analyzed the result of generative language model learning KOMUChat and benchmark dataset. The results showed that our dataset outperformed the benchmark dataset in terms of answer appropriateness, user satisfaction, and fulfillment of conversational AI goals. The dataset is the largest open-source single turn text data presented so far and it has the significance of building a more friendly Korean dataset by reflecting the text styles of the online community.

A Study of the New Chinese Words Under the Influence of Culture Content (문화 콘텐츠 영향의 신조 중국어 고찰)

  • Meng, Xiang-Shan;Lee, Kwang-Ho
    • Journal of Korea Entertainment Industry Association
    • /
    • v.13 no.8
    • /
    • pp.131-142
    • /
    • 2019
  • This paper is intended to examine and analyze the new Chinese words as the result of culture content. The development of the Korean entertainment industry has created a Korean wave around the world. Through this, many Korean words, Internet vocabulary, and cultural concepts have begun to enter China. Among them, there are many new words that have appeared on the Chinese Internet due to the culture content. As the number of Korean fans and Korean learners increases, new words on the Internet are widely used. The new Chinese words, which are influenced by Korean cultural content, are considered an important part of new Chinese vocabulary. To accurately recognize and understand this, first of all six categories of the new Chinese words were analyzed, which were figurative meaning, substitution, loan of foreign words, abbreviation, compound word, derivation. This formulation also works on the Chinese words with the influence of cultural content. There are three types of the Internet new words form Korean cultural. Which were new words in Chinese characters, new words in alphabets, extended meanings. And had analyzed new words through the acquisition of new meanings. Also took specific news titles and songs according to each category. Through new Chinese words, The influence of cultural content had been confirmed. It is expected that these new Chinese words enrich Chinese vocabulary, also help to facilitate communication. And these new Chinese words are often used in public media or in everyday life. We should recognize the existence of these new Chinese words, and have an accurate perception of them.