• Annual Conference of KIPS
• /
• 2023.11a
• /
• pp.319-320
• /
• 2023

일반적인 여행 커뮤니티는 사진과 텍스트 기반의 사용자 리뷰를 바탕으로 정보 공유를 한다. 본 연구에서는 관광지에서 수행한 활동을 한 문장의 형태로 공유하는 애플리케이션을 제안한다. ChatGPT를 활용하여 활동을 산책, 사진, 음식 등 9가지 태그로 분류하여 관광지가 가지는 특징을 용이하게 파악한다. 또한, 사용자가 작성한 활동을 임베딩하고 관광지 소개 글 벡터와 유사도를 비교하여 관광지를 추천한다. 본 애플리케이션을 통해 사용자가 긴 설명이나 사진 없이 관광지가 가지는 정보를 쉽게 공유하고 관광지 추천을 하는 새로운 여행 커뮤니티를 제공할 수 있을 것으로 기대한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.75-77
• /
• 2021

A variety of search engines are currently in use. The search engine supports the retrieval of data required by users through three stages: crawling, index generation, and output of search results based on meta-tag information. However, a large number of documents obtained by searching for keywords are often unrelated or scarce. Because of these problems, it takes time and effort to grasp the content from the search results and classify the accuracy. The index of search engines is updated periodically, but the criteria for weighted values and update periods are different from one search engine to another. Therefore, this paper uses the LSTM model, which extracts the relationship between keywords entered by the user and documents instead of the existing search engine, and improves the relationship between keywords and documents by entering keywords that the user wants to find.

• Journal of Advanced Navigation Technology
• /
• v.27 no.6
• /
• pp.835-840
• /
• 2023

RFID(Radio Frequency Identification) systems are attracting attention as a key component of Internet of Things technology due to the cost and energy efficiency of application services. In order to use RFID technology in the IoT application service field, it is necessary to be able to store and manage various information for a long period of time as well as simple recognition between the reader and tag of the RFID system. And in order to read and write information to tags, a performance improvement technology that is strong and reliable in poor wireless channels is needed. In particular, in the UHF(Ultra High Frequency) RFID system, since multiple tags communicate passively in a crowded environment, it is essential to improve the recognition rate and transmission speed of individual tags. In this paper, Middleton's Class A impulsive noise model was selected to analyze the performance of the RFID system in an impulsive noise environment, and FM0 encoding and Miller encoding were applied to the tag to analyze the error rate performance of the RFID system. As a result of analyzing the performance of the RFID system in Middleton's Class A impulsive noise channel, it was found that the larger the Gaussian noise to impulsive noise power ratio and the impulsive noise index, the more similar the characteristics to the Gaussian noise channel.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.5A
• /
• pp.517-525
• /
• 2006

In this paper, we present a high-speed RFID data filtering engine designed to carry out filtering under the conditions of massive data and massive filters. We discovered that the high-speed RFID data filtering technique is very similar to the high-speed packet classification technique which is used in high-speed routers and firewall systems. Actually, our filtering engine is designed based on existing packet classification algorithms, Bit Parallelism and Aggregated Bit Vector(ABV). In addition, we also discovered that there are strong temporal relations and redundancy in the RFID data filtering operations. We incorporated two kinds of caches, tag and filter caches, to make use of this characteristic to improve the efficiency of the filtering engine. The performance of the proposed engine has been examined by implementing a prototype system and testing it. Compared to the basic sequential filter comparison approach, our engine shows much better performance, and it gets better as the number of filters increases.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38C no.10
• /
• pp.841-851
• /
• 2013

Mobile RFID/NFC linkage technology means a provision of integrated 2 existing mobile RFID services by developing the 900MHz mobile RFID reader and the NFC reader/tag into one SoC to be put on a USIM card. In this paper, the mobile RFID related technologies that offer similar services as NFC were also analyzed to understand the potential linkage to NFC and the requirements for the linkage. In addition, the introduction of dual tag and the code system linkage suggested a linking method to maximally use the existing infrastructure and the requirement satisfaction was analyzed. Lastly, based on the analysis, the future direction for the new standard design was suggested.

• Annual Conference on Human and Language Technology
• /
• 2001.10d
• /
• pp.146-154
• /
• 2001

본 논문에서는 개념망 구축을 위해 사전 뜻풀이말에서 추출 가능한 의미속성의 분포 정보를 기반으로 어휘 연관도를 측정하고자 한다. 먼저 112,000여 개의 사전 뜻풀이말을 대상으로 품사 태그와 의미 태그가 부여된 코퍼스에서 의미속성을 추출한다. 추출 가능한 의미속성은 체언류, 부사류, 용언류 등이 있는데 본 논문에서는 일차적으로 명사류와 수식 관계에 있는 용언류 중 관형형 전성어미('ㄴ/은/는')가 부착된 것을 대상으로 한다. 추출된 공기쌍 45,000여 개를 대상으로 정제 작업을 거쳐 정보이론의 상호 정보량(MI)을 이용하여 명사류와 용언류의 연관도를 측정한다. 한편, 자료의 희귀성을 완화하기 위해 수식 관계의 명사류와 용언류는 기초어휘를 중심으로 유사어 집합으로 묶어서 작업을 하였다. 이러한 의미속성의 분포 정보를 통해 측정된 어휘 연관도는 의미속성의 공유 정도를 계산하여 개념들간에 계층구조를 구축하는 데 이용할 수 있다.

• Journal of KIISE
• /
• v.41 no.12
• /
• pp.1117-1125
• /
• 2014

Folksonomy data, which is derived from social tagging systems, is a useful source for understanding a user's intention and interest. Using the folksonomy data, it is possible to create an accurate user profile which can be utilized to build a personalized search system. However there are limitations in some of the traditional methods such as Vector Space Model(VSM) for user profiling and similarity computation. This paper suggests a novel method with graph-based user and document profile which uses the proximity information of query terms to improve personalized search. We demonstrate the performance of the suggested method by comparing its performance with several state-of-the-art VSM based personalization models in two different folksonomy datasets. The results show that the proposed model constantly outperforms the other state-of-the-art personalization models. Furthermore, the parameter sensitivity results show that the proposed model is parameter-free in that it is not affected by the idiosyncratic nature of datasets.

• Journal of the Korean Society for information Management
• /
• v.37 no.2
• /
• pp.197-223
• /
• 2020

The purpose of this study is to analyze the issues resulted from the process of grouping KORMARC records using FRBR WORK concept and to suggest a new method. The previous studies did not sufficiently address the criteria or processes for identifying representative authors of records and their derivatives. Therefore, our study focused on devising a method of identifying the representative author when there are multiple contributors in a work. The study developed a method of identifying representative authors using an author role dictionary constructed by extracting role-terms from the statement of responsibility field (245). We also designed another way to group records as a work by calculating similarity measures of authors and titles. The accuracy rate of WORK grouping was the highest when blank spaces, parentheses, and controling processes were removed from titles and the measured similarity rates of authors and titles were higher than 80 percent. This was an experiment study where we developed an author-role dictionary that can be utilized in selecting a representative author and measured the similarity rate of authors and titles in order to achieve effective WORK grouping of KORMARC records. The future study will attempt to devise a way to improve the similarity measure of titles, incorporate FRBR Group 1 entities such as expression, manifestation and item data into the algorithm, and a method of improving the algorithm by utilizing other forms of MARC data that are widely used in Korea.

• Journal of Korean Library and Information Science Society
• /
• v.38 no.4
• /
• pp.257-276
• /
• 2007

Back-of-book-style indexes have a similar function as back-of-book indexes. The best advantage o4 back-of-book-style indexes for Information access on the web is to give direct access to specific subjects of interest. Though back-of-book-style indexes are alphabetically arranged as back-of-book indexes, they have linked index entries to contents on the site by using a anchor tag of HTML. In this research, I have created back-of-book-style indexes in two separated ways, by hand-crafted and semi-automatic Indexing. We have utilized back-of-book-style indexes, that is similar to back-of-book index of traditional information organization method of library and information science, in library circumstances.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
• /
• 2006.06a
• /
• pp.497-500
• /
• 2006

신상욱 등은 JCCI 2003에서 새로운 인증-암호화 모드 NAE를 제안하였다. NAE는 CFB 모드와 CTR 모드를 결합시킨 변형된 형태로, 하나의 기반이 되는 블록 암호 키를 가지고 최소한으로 블록 암호를 호출하여 기밀성과 무결성을 모두 제공한다. 이 모드는 CBC 암호화 모드와 CBC-MAC이 결합된 CCM 인증-암호화 모드보다 효율적이며, 기제안된 다른 인증-암호화 기법들과 유사한 성능을 가진다. 그러나 본 논문에서는 단순 암호문 조작으로 유효한 암호문-태그 쌍을 생성할 수 있음을 보인다.