Výsledky vyhľadávania - Performance Keywords graph algorithms

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    Using the Ship-Gram Model for Japanese Keyword Extraction Based on News Reports Autor Teng, Miao

    ISSN: 1076-2787, 1099-0526
    Vydavateľské údaje: Hoboken Hindawi 2021
    Vydané v Complexity (New York, N.Y.) (2021)
    “…In this paper, we conduct an in-depth study of Japanese keyword extraction from news reports, train external computer document word sets from text preprocessing into word vectors using the Ship-gram…”
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    Keyphrase extraction using graph-based statistical approach with NLP patterns Autor Mehta, Siddhesh, Karwa, Rushikesh, Chavan, Rahul, Khatavkar, Vaibhav, Joshi, Amit

    ISSN: 0973-7677, 0256-2499, 0973-7677
    Vydavateľské údaje: New Delhi Springer India 05.05.2024
    Vydané v Sadhana (Bangalore) (05.05.2024)
    “… This research paper introduces a novel approach to extract keyphrases using a statistical approach based on graphs that incorporates degree centrality, TextRank, closeness, and betweenness measures…”
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    Predicting co-word links via heterogeneous graph convolutional networks Autor Li, Yangmin, Zhang, Xin, Bai, Xin, Bai, Sen, Jiang, Zhengang

    ISSN: 2045-2322, 2045-2322
    Vydavateľské údaje: London Nature Publishing Group UK 02.07.2025
    Vydané v Scientific reports (02.07.2025)
    “… Nevertheless, few existing methods have explored end-to-end deep models, impeded by the limitations of text graph models in learning both word co-occurrence and word-document relations implicit in co…”
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    A multi-centrality index for graph-based keyword extraction Autor Vega-Oliveros, Didier A., Gomes, Pedro Spoljaric, E. Milios, Evangelos, Berton, Lilian

    ISSN: 0306-4573, 1873-5371
    Vydavateľské údaje: Oxford Elsevier Ltd 01.11.2019
    Vydané v Information processing & management (01.11.2019)
    “…•Centrality measures are correlated and with statistical similar performance when finding keyword…”
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    Graph Matching by Simplified Convex-Concave Relaxation Procedure Autor Liu, Zhi-Yong, Qiao, Hong, Yang, Xu, Hoi, Steven C. H.

    ISSN: 0920-5691, 1573-1405
    Vydavateľské údaje: Boston Springer US 01.09.2014
    “…The convex and concave relaxation procedure (CCRP) was recently proposed and exhibited state-of-the-art performance on the graph matching problem…”
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    DKWS: A Distributed System for Keyword Search on Massive Graphs Autor Jiang, Jiaxin, Choi, Byron, Huang, Xin, Xu, Jianliang, Bhowmick, Sourav S

    ISSN: 1041-4347, 1558-2191
    Vydavateľské údaje: New York IEEE 01.05.2024
    “…Due to the unstructuredness and the lack of schemas of graphs, such as knowledge graphs, social networks, and RDF graphs, keyword search for querying such graphs has been proposed…”
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    An effective keyword search co-occurrence multi-layer graph mining approach Autor Bolorunduro, Janet Oluwasola, Zou, Zhaonian, Bah, Mohamed Jaward

    ISSN: 0885-6125, 1573-0565
    Vydavateľské údaje: New York Springer US 01.08.2024
    Vydané v Machine learning (01.08.2024)
    “… structures into embedding by utilizing specific pre-defined metrics. Co-occurrence graphs and keyword searches are the foundation of search engine optimizations for diverse real-world applications…”
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    Domain-Specific Languages for Algorithmic Graph Processing: A Systematic Literature Review Autor Boukham, Houda, Younsi Dahbi, Kawtar, Chiadmi, Dalila

    ISSN: 1999-4893, 1999-4893
    Vydavateľské údaje: Basel MDPI AG 01.07.2025
    Vydané v Algorithms (01.07.2025)
    “…) to support graph processing operations. These DSLs fall into two categories: query-based DSLs for graph-pattern matching and graph algorithm DSLs…”
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    A Graph Convolutional Network-Based Sensitive Information Detection Algorithm Autor Liu, Ying, Yang, Chao-Yu, Yang, Jie

    ISSN: 1076-2787, 1099-0526
    Vydavateľské údaje: Hoboken Hindawi 2021
    Vydané v Complexity (New York, N.Y.) (2021)
    “… For improvement purposes, this paper proposes a novel self-attention-based detection algorithm using the implementation of graph convolutional network (GCN…”
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    A semantic graph-based keyword extraction model using ranking method on big social data Autor Devika, R., Subramaniyaswamy, V.

    ISSN: 1022-0038, 1572-8196
    Vydavateľské údaje: New York Springer US 01.11.2021
    Vydané v Wireless networks (01.11.2021)
    “… Existing graph-based methods consider only numeric measures such as centrality, degree, and betweenness for keyword extraction…”
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    Optimizing document management and retrieval with multimodal transformers and knowledge graphs Autor Chen, Yali, Hu, Bin, Liu, Yajuan

    ISSN: 1932-6203, 1932-6203
    Vydavateľské údaje: United States Public Library of Science 11.06.2025
    Vydané v PloS one (11.06.2025)
    “… To address this issue, this paper proposes the MDKG-RL model, which organically integrates knowledge graph reasoning, deep reinforcement learning dynamic optimization, and multimodal Transformer…”
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    A Generic Ontology Framework for Indexing Keyword Search on Massive Graphs Autor Jiang, Jiaxin, Choi, Byron, Xu, Jianliang, Bhowmick, Sourav S

    ISSN: 1041-4347, 1558-2191
    Vydavateľské údaje: New York IEEE 01.06.2021
    “…Due to the unstructuredness and the lack of schema information of knowledge graphs, social networks and RDF graphs, keyword search has been proposed for querying such graphs/networks…”
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    Understanding the domain of driving distraction with knowledge graphs Autor Xu, Wenxia, Feng, Lei, Ma, Jun

    ISSN: 1932-6203, 1932-6203
    Vydavateľské údaje: United States Public Library of Science 09.12.2022
    Vydané v PloS one (09.12.2022)
    “…This paper aims to provide insight into the driving distraction domain systematically on the basis of scientific knowledge graphs…”
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    Efficient keyword search on graph data for finding diverse and relevant answers Autor Park, Chang-Sup

    ISSN: 1744-0084, 1744-0092, 1744-0084
    Vydavateľské údaje: Bingley Emerald Publishing Limited 12.07.2023
    “… This study aims to propose an efficient keyword search algorithm on graph data to find top-k answers that are most relevant to the query and have diverse content nodes for the input keyword…”
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    Path Planning Under Kinematic Constraints by Rapidly Exploring Manifolds Autor Jaillet, L., Porta, J. M.

    ISSN: 1552-3098, 1941-0468
    Vydavateľské údaje: New York IEEE 01.02.2013
    Vydané v IEEE transactions on robotics (01.02.2013)
    “… This paper presents the AtlasRRT algorithm, which is a planner especially tailored for such constrained systems that builds on recently developed tools for higher-dimensional continuation…”
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    An efficient approach for searching optimal multi-keywords coverage routes Autor Yang, Rong, Niu, Baoning, Jin, Pengfei

    ISSN: 1382-6905, 1573-2886
    Vydavateľské údaje: New York Springer US 01.09.2022
    Vydané v Journal of combinatorial optimization (01.09.2022)
    “… Motivated by this, we propose an algorithm called Keyword-aware Skyline Route Generating (KSRG*). KSRG* consists of a preprocessing stage, in which KSRG…”
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    Keyword-based Socially Tenuous Group Queries Autor Zhu, Huaijie, Liu, Wei, Yin, Jian, Cui, Ningning, Xu, Jianliang, Huang, Xin, Lee, Wang-Chien

    ISSN: 2375-026X
    Vydavateľské údaje: IEEE 01.04.2023
    Vydané v Data engineering (01.04.2023)
    “…s. To address the KTG problem, we first propose two exact algorithms, namely KTG-VKC and KTG-VKC-DEG, which give priority to the valid keyword coverage and the combination…”
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    A survey study on task scheduling schemes for workflow executions in cloud computing environment: classification and challenges Autor Hosseini Shirvani, Mirsaeid

    ISSN: 0920-8542, 1573-0484
    Vydavateľské údaje: New York Springer US 01.05.2024
    Vydané v The Journal of supercomputing (01.05.2024)
    “… Since task scheduling algorithms for workflow executions determine which task should be possibly executed on what resources, they have a drastic impact on both the…”
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    Name Disambiguation Based on Graph Convolutional Network Autor Chen, Ya, Yuan, Hongliang, Liu, Tingting, Ding, Nan

    ISSN: 1058-9244, 1875-919X
    Vydavateľské údaje: New York Hindawi 2021
    Vydané v Scientific programming (2021)
    “…: clustering based on attribute features and clustering based on linkage information. They cannot however get high performance…”
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