• Title/Summary/Keyword: Recommending system

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Semantic Fuzzy Implication Operator for Semantic Implication Relationship of Knowledge Descriptions in Question Answering System (질의 응답 시스템에서 지식 설명의 의미적 포함 관계를 고려한 의미적 퍼지 함의 연산자)

  • Ahn, Chan-Min;Lee, Ju-Hong;Choi, Bum-Ghi;Park, Sun
    • The Journal of the Korea Contents Association
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    • v.11 no.3
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    • pp.73-83
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    • 2011
  • The question answering system shows the answers that are input by other users for user's question. In spite of many researches to try to enhance the satisfaction level of answers for user question, there is a essential limitation. So, the question answering system provides users with the method of recommendation of another questions that can satisfy user's intention with high probability as an auxiliary function. The method using the fuzzy relational product operator was proposed for recommending the questions that can includes largely the contents of the user's question. The fuzzy relational product operator is composed of the Kleene-Dienes operator to measure the implication degree by contents between two questions. However, Kleene-Dienes operator is not fit to be the right operator for finding a question answers pair that semantically includes a user question, because it was not designed for the purpose of finding the degree of semantic inclusion between two documents. We present a novel fuzzy implication operator that is designed for the purpose of finding question answer pairs by considering implication relation. The new operator calculates a degree that the question semantically implies the other question. We show the experimental results that the probability that users are satisfied with the searched results is increased when the proposed operator is used for recommending of question answering system.

Analysis of the Requirements and Design of KASS Measuring Equipment (KASS 탑재측정장비 요구사항 및 설계방안 분석)

  • Kim, Woo-Ri-Ul;Hong, Gyo-Young;Kang, Hee Won;Choi, Kwang-Sik
    • Journal of Advanced Navigation Technology
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    • v.21 no.6
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    • pp.544-548
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    • 2017
  • The International Civil Aviation Organization is recommending the use of SBAS on all aircraft by 2025 to urge PBN implementation around the world. As part of this, Korea is also developing KASS, a Korean SBAS. ICAO grants authority to the host nation aviation authority in the certification and operation of SBAS. The KASS system will be verified after detailed system design, fabrication and installation. In this paper, flight test parameters are derived from the flight inspection regulations and the configuration of the on - board measurement equipment for measuring the parameters has been proposed.

A Study on the Strategy of Smart Charging System to Charge the PHEV in the House Which has a 1 kW Fuel Cell Cogeneration System (1 kW 급 가정용 연료전지 코제너레이션 시스템이 설치된 주택 내 플러그인 하이브리드 자동차의 스마트 충전전략 연구)

  • Roh, Chul-Woo;Kim, Min-Soo
    • Proceedings of the SAREK Conference
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    • 2008.06a
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    • pp.838-843
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    • 2008
  • Cause of struggling to escape from dependency of fossil fuels, the fuel cell and the Plug-in Hybrid Electric Vehicle (PHEV) draw attention in the all of the world. Especially, the Polymer Electrolyte Membrane Fuel Cell (PEMFC) systems have been anticipated for next generation's energy supplying system, and we can predict the PHEV will enlarge the market share in the next few years to reduce not only the air pollution in the metropolis but the fuel-expenses of commuters. This paper presents simulation results about the strategy of smart charging system for PHEV in the residential house which has 1 kW PEMFC cogeneration system. The smart charging system has a function of recommending the best time to charge the battery of PHEV by the lowest energy cost. The simulated energy cost for charging the battery based on the electricity demand data pattern in the house. The house which floor area is $132\;m^2$ (40 pyeong.). In these conditions, the annual gasoline, electricity, and total energy cost to fuel the PHEV versus Conventional Vehicle (CV) have been simulated in terms of cars' average life span in Korea.

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Cody Recommendation System Using Deep Learning and User Preferences

  • Kwak, Naejoung;Kim, Doyun;kim, Minho;kim, Jongseo;Myung, Sangha;Yoon, Youngbin;Choi, Jihye
    • International Journal of Advanced Culture Technology
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    • v.7 no.4
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    • pp.321-326
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    • 2019
  • As AI technology is recently introduced into various fields, it is being applied to the fashion field. This paper proposes a system for recommending cody clothes suitable for a user's selected clothes. The proposed system consists of user app, cody recommendation module, and server interworking of each module and managing database data. Cody recommendation system classifies clothing images into 80 categories composed of feature combinations, selects multiple representative reference images for each category, and selects 3 full body cordy images for each representative reference image. Cody images of the representative reference image were determined by analyzing the user's preference using Google survey app. The proposed algorithm classifies categories the clothing image selected by the user into a category, recognizes the most similar image among the classification category reference images, and transmits the linked cody images to the user's app. The proposed system uses the ResNet-50 model to categorize the input image and measures similarity using ORB and HOG features to select a reference image in the category. We test the proposed algorithm in the Android app, and the result shows that the recommended system runs well.

Development of the Recommender System of Arabic Books Based on the Content Similarity

  • Alotaibi, Shaykhah Hajed;Khan, Muhammad Badruddin
    • International Journal of Computer Science & Network Security
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    • v.22 no.8
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    • pp.175-186
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    • 2022
  • This research article develops an Arabic books' recommendation system, which is based on the content similarity that assists users to search for the right book and predict the appropriate and suitable books pertaining to their literary style. In fact, the system directs its users toward books, which can meet their needs from a large dataset of Information. Further, this system makes its predictions based on a set of data that is gathered from different books and converts it to vectors by using the TF-IDF system. After that, the recommendation algorithms such as the cosine similarity, the sequence matcher similarity, and the semantic similarity aggregate data to produce an efficient and effective recommendation. This approach is advantageous in recommending previously unrated books to users with unique interests. It is found to be proven from the obtained results that the results of the cosine similarity of the full content of books, the results of the sequence matcher similarity of Arabic titles of the books, and the results of the semantic similarity of English titles of the books are the best obtained results, and extremely close to the average of the result related to the human assigned/annotated similarity. Flask web application is developed with a simple interface to show the recommended Arabic books by using cosine similarity, sequence matcher similarity, and semantic similarity algorithms with all experiments that are conducted.

A Method of Fashion Recommender in Coordination with Individual Physical Features (개인의 신체적 특성에 맞춘 의류 추천 방법)

  • Kim, Jung-In
    • Journal of Korea Multimedia Society
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    • v.14 no.8
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    • pp.1061-1069
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    • 2011
  • With the development of information technology, online commercial transactions have been steadily increasing. However it is not easy to recommend the clothes in coordination with individual physical features. This paper presents a fashion coordination recommender system for women's clothes. The system includes the functionality of recommending clothes best-suited for customers in consideration of their individual physical features. It has also been designed to recommend clothes in vogue for those who are fashion-sensitive by considering the fashion trend of the times. Operated in an optional or coupling way, these functionalities of our system result in an intelligent fashion coordination system which recommends dress items to customers in various ways.

Development of User-dependent Mid-point Navigation System (사용자 중심의 중간지점 탐색 시스템의 설계 및 구현)

  • Ahn, Jonghee;Kang, Inhyeok;Seo, Seyeong;Kim, Taewoo;Heo, Yusung;Ahn, Yonghak
    • Convergence Security Journal
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    • v.19 no.2
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    • pp.73-81
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    • 2019
  • In this paper, we propose a user-dependent mid-point navigation system using a time weighted mid-point navigation algorithm and a user preference based mid-point neighborhood recommendation system. The proposed system consists of a mid-point navigation module for calculating an mid-point by applying a time weight of each user based on a departure point between users, and a search module for providing a search for a route to the calculated mid-point. In addition, based on the mid-point search result, it is possible to increase the utilization rate of users by including a place recommending function based on user's preference. Experimental results show that the proposed system can increase the efficiency of using by the user-dependent mid-point navigation and place recommendation function.

A Development of Optimal Travel Course Recommendation System based on Altered TSP and Elasticsearch Algorithm (변형된 TSP 및 엘라스틱서치 알고리즘 기반의 최적 여행지 코스 추천 시스템 개발)

  • Kim, Jun-Yeong;Jo, Kyeong-Ho;Park, Jun;Jung, Se-Hoon;Sim, Chun-Bo
    • Journal of Korea Multimedia Society
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    • v.22 no.9
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    • pp.1108-1121
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    • 2019
  • As the quality and level of life rise, many people are doing search for various pieces of information about tourism. In addition, users prefer the search methods reflecting individual opinions such as SNS and blogs to the official websites of tourist destination. Many of previous studies focused on a recommendation system for tourist courses based on the GPS information and past travel records of users, but such a system was not capable of recommending the latest tourist trends. This study thus set out to collect and analyze the latest SNS data to recommend tourist destination of high interest among users. It also aimed to propose an altered TSP algorithm to recommend the optimal routes to the recommended destination within an area and a system to recommend the optimal tourist courses by applying the Elasticsearch engine. The altered TSP algorithm proposed in the study used the location information of users instead of Dijkstra's algorithm technique used in previous studies to select a certain tourist destination and allowed users to check the recommended courses for the entire tourist destination within an area, thus offering more diverse tourist destination recommendations than previous studies.

A practical challenge-response authentication mechanism for a Programmable Logic Controller control system with one-time password in nuclear power plants

  • Son, JunYoung;Noh, Sangkyun;Choi, JongGyun;Yoon, Hyunsoo
    • Nuclear Engineering and Technology
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    • v.51 no.7
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    • pp.1791-1798
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    • 2019
  • Instrumentation and Control (I&C) systems of nuclear power plants (NPPs) have been continuously digitalized. These systems have a critical role in the operation of nuclear facilities by functioning as the brain of NPPs. In recent years, as cyber security threats to NPP systems have increased, regulatory and policy-related organizations around the world, including the International Atomic Energy Agency (IAEA), Nuclear Regulatory Commission (NRC) and Korea Institute of Nuclear Nonproliferation and Control (KINAC), have emphasized the importance of nuclear cyber security by publishing cyber security guidelines and recommending cyber security requirements for NPP facilities. As described in NRC Regulatory Guide (Reg) 5.71 and KINAC RS015, challenge response authentication should be applied to the critical digital I&C system of NPPs to satisfy the cyber security requirements. There have been no cases in which the most robust response authentication technology like challenge response has been developed and applied to nuclear I&C systems. This paper presents a challenge response authentication mechanism for a Programmable Logic Controller (PLC) system used as a control system in the safety system of the Advanced Power Reactor (APR) 1400 NPP.

CRF Based Intrusion Detection System using Genetic Search Feature Selection for NSSA

  • Azhagiri M;Rajesh A;Rajesh P;Gowtham Sethupathi M
    • International Journal of Computer Science & Network Security
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    • v.23 no.7
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    • pp.131-140
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    • 2023
  • Network security situational awareness systems helps in better managing the security concerns of a network, by monitoring for any anomalies in the network connections and recommending remedial actions upon detecting an attack. An Intrusion Detection System helps in identifying the security concerns of a network, by monitoring for any anomalies in the network connections. We have proposed a CRF based IDS system using genetic search feature selection algorithm for network security situational awareness to detect any anomalies in the network. The conditional random fields being discriminative models are capable of directly modeling the conditional probabilities rather than joint probabilities there by achieving better classification accuracy. The genetic search feature selection algorithm is capable of identifying the optimal subset among the features based on the best population of features associated with the target class. The proposed system, when trained and tested on the bench mark NSL-KDD dataset exhibited higher accuracy in identifying an attack and also classifying the attack category.