• Title/Summary/Keyword: Retrieval Algorithm

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The Study of Sensor Network for Information Retrieval and Communication Protocol High Performance Algorithm (센서 네트워크의 정보검색 및 통신프로토콜 성능향상 알고리즘에 관한 연구)

  • Kang, Jeong-Yong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.5B
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    • pp.816-823
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    • 2010
  • Recently research efforts for ubiquitous technology that includes RFID(Radio Frequency Deification and sensor networks are conducted very actively The architectural framework of the USN sensor network discovery service. The survey of the USN technology is conducted on four technological visions that contain USN system technology USN networking technology and USN middleware along with the service platform, With respect to each technological division domestic and worldwide leading research projects are primarily explored with their technical features and research projects are primarily explored with their technical features and research outputs. Boasted on the result of the survey we establish a USN software model that includes data sensing, sensor data storage sensor data storage sensor data naming and sensor feed name service. This main objective of this model is to provide a reference model for the facilitation of USN application developments.

A Study on the Law2Vec Model for Searching Related Law (연관법령 검색을 위한 워드 임베딩 기반 Law2Vec 모형 연구)

  • Kim, Nari;Kim, Hyoung Joong
    • Journal of Digital Contents Society
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    • v.18 no.7
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    • pp.1419-1425
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    • 2017
  • The ultimate goal of legal knowledge search is to obtain optimal legal information based on laws and precedent. Text mining research is actively being undertaken to meet the needs of efficient retrieval from large scale data. A typical method is to use a word embedding algorithm based on Neural Net. This paper demonstrates how to search relevant information, applying Korean law information to word embedding. First, we extracts reference laws from precedents in order and takes reference laws as input of Law2Vec. The model learns a law by predicting its surrounding context law. The algorithm then moves over each law in the corpus and repeats the training step. After the training finished, we could infer the relationship between the laws via the embedding method. The search performance was evaluated based on precision and the recall rate which are computed from how closely the results are associated to the search terms. The test result proved that what this paper proposes is much more useful compared to existing systems utilizing only keyword search when it comes to extracting related laws.

A Study on the Secure Database Controlled Under Cloud Environment (클라우드 환경하에서의 안전한 데이터베이스 구축에 관한 연구)

  • Kim, SungYong;Kim, Ji-Hong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.23 no.6
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    • pp.1259-1266
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    • 2013
  • Nowadays, the databases are getting larger and larger. As the company has difficulty in managing the database, they want to outsource the database to the cloud system. In this case the database security is more important because their database is managed by the cloud service provider. Among database security techniques, the encryption method is a well-certified and established technology for protecting sensitive data. However, once encrypted, the data can no longer be easily queried. The performance of the database depends on how to encrypt the sensitive data, and on the approach for searching, and the retrieval efficiency that is implemented. In this paper we propose the new suitable mechanism to encrypt the database and lookup process on the encrypted database under control of the cloud service provider. This database encryption algorithm uses the bloom filter with the variable keyword based index. Finally, we demonstrate that the proposed algorithm should be useful for database encryption related research and application activities.

Design of Query Processing System to Retrieve Information from Social Network using NLP

  • Virmani, Charu;Juneja, Dimple;Pillai, Anuradha
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.3
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    • pp.1168-1188
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    • 2018
  • Social Network Aggregators are used to maintain and manage manifold accounts over multiple online social networks. Displaying the Activity feed for each social network on a common dashboard has been the status quo of social aggregators for long, however retrieving the desired data from various social networks is a major concern. A user inputs the query desiring the specific outcome from the social networks. Since the intention of the query is solely known by user, therefore the output of the query may not be as per user's expectation unless the system considers 'user-centric' factors. Moreover, the quality of solution depends on these user-centric factors, the user inclination and the nature of the network as well. Thus, there is a need for a system that understands the user's intent serving structured objects. Further, choosing the best execution and optimal ranking functions is also a high priority concern. The current work finds motivation from the above requirements and thus proposes the design of a query processing system to retrieve information from social network that extracts user's intent from various social networks. For further improvements in the research the machine learning techniques are incorporated such as Latent Dirichlet Algorithm (LDA) and Ranking Algorithm to improve the query results and fetch the information using data mining techniques.The proposed framework uniquely contributes a user-centric query retrieval model based on natural language and it is worth mentioning that the proposed framework is efficient when compared on temporal metrics. The proposed Query Processing System to Retrieve Information from Social Network (QPSSN) will increase the discoverability of the user, helps the businesses to collaboratively execute promotions, determine new networks and people. It is an innovative approach to investigate the new aspects of social network. The proposed model offers a significant breakthrough scoring up to precision and recall respectively.

Closest Pairs and e-distance Join Query Processing Algorithms using a POI-based Materialization Technique in Spatial Network Databases (공간 네트워크 데이터베이스에서 POI 기반 실체화 기법을 이용한 Closest Pairs 및 e-distance 조인 질의처리 알고리즘)

  • Kim, Yong-Ki;Chang, Jae-Woo
    • Journal of Korea Spatial Information System Society
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    • v.9 no.3
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    • pp.67-80
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    • 2007
  • Recently, many studies on query processing algorithms has been done for spatial networks, such as roads and railways, instead of Euclidean spaces, in order to efficiently support LBS(location-based service) and Telematics applications. However, both a closest pairs query and an e-distance join query require a very high cost in query processing because they can be answered by processing a set of POIs, instead of a single POI. Nevertheless, the query processing cost for closest pairs and e-distance join queries is rapidly increased as the number of k (or the length of radius) is increased. Therefore, we propose both a closest pairs query processing algorithm and an e-distance join query processing algorithm using a POI-based materialization technique so that we can process closest pairs and e-distance join queries in an efficient way. In addition, we show the retrieval efficiency of the proposed algorithms by making a performance comparison of the conventional algorithms.

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A Study on Design and Implementation of Personalized Information Recommendation System based on Apriori Algorithm (Apriori 알고리즘 기반의 개인화 정보 추천시스템 설계 및 구현에 관한 연구)

  • Kim, Yong
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.23 no.4
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    • pp.283-308
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    • 2012
  • With explosive growth of information by recent advancements in information technology and the Internet, users need a method to acquire appropriate information. To solve this problem, an information retrieval and filtering system was developed as an important tool for users. Also, users and service providers are growing more and more interested in personalized information recommendation. This study designed and implemented personalized information recommendation system based on AR as a method to provide positive information service for information users as a method to provide positive information service. To achieve the goal, the proposed method overcomes the weaknesses of existing systems, by providing a personalized recommendation method for contents that works in a large-scaled data and user environment. This study based on the proposed method to extract rules from log files showing users' behavior provides an effective framework to extract Association Rule.

Motion vector-tracing algorithms of video sequence (비디오 시퀀스의 움직임 추적 알고리즘)

  • 이재현
    • Journal of the Korea Computer Industry Society
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    • v.3 no.7
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    • pp.927-936
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    • 2002
  • This paper presents the extraction of a feature by motion vector for efficient content-based retrieval for digital video. in this paper, divided by general size block for the current frame by video, using BMA(block matching algorithm) for an estimate by block move based on a time frame. but in case BMA appeared on a different pattern fact of motion in the vector obtain for the BMA. solve in this a problem to application for full search method this method is detected by of on many calculations. I propose an alternative plan in this paper Limit the search region to $\pm$15 and search is a limit integer pixel. a result, in this paper is make an estimate motion vector in more accurately using motion vector in adjoin in blocks. however, refer to the block vector because occurrence synchronism. Such addition information is get hold burden receive to transmit therefore, forecasted that motion feature each block and consider for problems for establish search region. in this paper Algorithm based to an examination Motion Estimation method by for motion Compensation is proposed.

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An Efficient Object Extraction Scheme for Low Depth-of-Field Images (낮은 피사계 심도 영상에서 관심 물체의 효율적인 추출 방법)

  • Park Jung-Woo;Lee Jae-Ho;Kim Chang-Ick
    • Journal of Korea Multimedia Society
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    • v.9 no.9
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    • pp.1139-1149
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    • 2006
  • This paper describes a novel and efficient algorithm, which extracts focused objects from still images with low depth-of-field (DOF). The algorithm unfolds into four modules. In the first module, a HOS map, in which the spatial distribution of the high-frequency components is represented, is obtained from an input low DOF image [1]. The second module finds OOI candidate by using characteristics of the HOS. Since it is possible to contain some holes in the region, the third module detects and fills them. In order to obtain an OOI, the last module gets rid of background pixels in the OOI candidate. The experimental results show that the proposed method is highly useful in various applications, such as image indexing for content-based retrieval from huge amounts of image database, image analysis for digital cameras, and video analysis for virtual reality, immersive video system, photo-realistic video scene generation and video indexing system.

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Two Version Latch Technique for Metadata Management of Documents in Digital Library (전자 도서관에서 문서의 메타데이타 관리를 위한 2 버전 래치 기법)

  • Jwa, Eun-Hee;Park, Seog
    • Journal of KIISE:Databases
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    • v.29 no.3
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    • pp.159-167
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    • 2002
  • Recently, a major issue in the research of metadata is the standardization of metadata format. The new extension capability of metadata in the standardization requires some changes - storing and managing dynamic data consistently. In this paper, we define the characteristics of new metadata and propose a concurrency control called Two Version Latch (2VL). 2VL uses a latch and maintains two versions. Maintaining two versions using latch minimizes conflicts between read operation and write operation. The removal of unnecessary lock holding minimizes refresh latency. Therefore, this algorithm presents fast response time and recent data retrieval in read operation execution. As a result of the performance evaluation, the 2VL algorithm is shown to be better than other algorithms in metadata management system.

Comparison of Algorithms for Sea Surface Current Retrieval using Himawari-8/AHI Data (Himawari-8/AHI 자료를 활용한 표층 해류 산출 알고리즘 비교)

  • Kim, Hee-Ae;Park, Kyung-Ae;Park, Ji-Eun
    • Korean Journal of Remote Sensing
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    • v.32 no.6
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    • pp.589-601
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    • 2016
  • Sea surface currents were estimated by applying the Maximum Cross Correlation (MCC), Zero-mean Sum of Absolute Distances (ZSAD), and Zero-mean Sum of Squared Distances (ZSSD) algorithms to Himawari-8/Advanced Himawari Imager (AHI) thermal infrared channel data, and the comparative analysis was performed between the results of these algorithms. The sea surface currents of the Kuroshio Current region that were retrieved using each algorithm showed similar results. The ratio of errors to the total number of estimated surface current vectors had little difference according to the algorithms, and the time required for sea surface current calculation was reduced by 24% and 18%, relative to the MCC algorithm, for the ZSAD and ZSSD algorithms, respectively. The estimated surface currents were validated against those from satellite-tracked surface drifter and altimeter data, and the accuracy evaluation of these algorithms showed results within similar ranges. In addition, the accuracy was affected by the magnitude of brightness temperature gradients and the time interval between satellite image data.