Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (47)
  • Open Access

    ARTICLE

    An Importance Assessment Model of Open-Source Community Java Projects Based on Domain Knowledge Graph

    Chengrong Yang1, Rongjing Bu2, Yan Kang2, Yachuan Zhang2, Hao Li2,*, Tao Li2, Junfeng Li2

    Journal on Big Data, Vol.2, No.4, pp. 135-144, 2020, DOI:10.32604/jbd.2020.010000 - 24 December 2020

    Abstract With the rise of open-source software, the social development paradigm occupies an indispensable position in the current software development process. This paper puts forward a variant of the PageRank algorithm to build the importance assessment model, which provides quantifiable importance assessment metrics for new Java projects based on Java open-source projects or components. The critical point of the model is to use crawlers to obtain relevant information about Java open-source projects in the GitHub open-source community to build a domain knowledge graph. According to the three dimensions of the Java opensource project’s project influence, project More >

  • Open Access

    ARTICLE

    Knowledge Graph Representation Reasoning for Recommendation System

    Tao Li, Hao Li*, Sheng Zhong, Yan Kang, Yachuan Zhang, Rongjing Bu, Yang Hu

    Journal of New Media, Vol.2, No.1, pp. 21-30, 2020, DOI:10.32604/jnm.2020.09767 - 14 August 2020

    Abstract In view of the low interpretability of existing collaborative filtering recommendation algorithms and the difficulty of extracting information from content-based recommendation algorithms, we propose an efficient KGRS model. KGRS first obtains reasoning paths of knowledge graph and embeds the entities of paths into vectors based on knowledge representation learning TransD algorithm, then uses LSTM and soft attention mechanism to capture the semantic of each path reasoning, then uses convolution operation and pooling operation to distinguish the importance of different paths reasoning. Finally, through the full connection layer and sigmoid function to get the prediction ratings, More >

  • Open Access

    ARTICLE

    Auxiliary Diagnosis Based on the Knowledge Graph of TCM Syndrome

    Yonghong Xie1, 3, Liangyuan Hu1, 3, Xingxing Chen2, 3, Jim Feng4, Dezheng Zhang1, 3, *

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 481-494, 2020, DOI:10.32604/cmc.2020.010297 - 23 July 2020

    Abstract As one of the most valuable assets in China, traditional medicine has a long history and contains pieces of knowledge. The diagnosis and treatment of Traditional Chinese Medicine (TCM) has benefited from the natural language processing technology. This paper proposes a knowledge-based syndrome reasoning method in computerassisted diagnosis. This method is based on the established knowledge graph of TCM and this paper introduces the reinforcement learning algorithm to mine the hidden relationship among the entities and obtain the reasoning path. According to this reasoning path, we could infer the path from the symptoms to the More >

  • Open Access

    ARTICLE

    Survey of Knowledge Graph Approaches and Applications

    Hangjun Zhou1, Tingting Shen1, *, Xinglian Liu1, Yurong Zhang1, Peng Guo1, 2, Jianjun Zhang3

    Journal on Artificial Intelligence, Vol.2, No.2, pp. 89-101, 2020, DOI:10.32604/jai.2020.09968 - 15 July 2020

    Abstract With the advent of the era of big data, knowledge engineering has received extensive attention. How to extract useful knowledge from massive data is the key to big data analysis. Knowledge graph technology is an important part of artificial intelligence, which provides a method to extract structured knowledge from massive texts and images, and has broad application prospects. The knowledge base with semantic processing capability and open interconnection ability can be used to generate application value in intelligent information services such as intelligent search, intelligent question answering and personalized recommendation. Although knowledge graph has been More >

  • Open Access

    ARTICLE

    Optimization of the Dynamic Measure of Spillover Effect Based on Knowledge Graph

    Rui Hua1,2, Yongwen Bao3, Shengan Chen2, Ziyin Zhuang1,*

    Computer Systems Science and Engineering, Vol.34, No.4, pp. 215-223, 2019, DOI:10.32604/csse.2019.34.215

    Abstract This paper improves the dynamic Feder model based on the characteristics of knowledge production and separates the direct effect and spillover effect of R&D in order to determine the relationship between spillover effect of R&D and economic growth, and accurately measure it by examining Chinese provincial panel data from 2008–2016. The theoretical analysis shows that the spillover effect of R&D promotes economic growth. Empirical analysis using a combination of OLS, sysGMM, 2SLS and GLS shows that basic research and application research have significant spillover effects; the marginal revenue of the basic research is lower than More >

  • Open Access

    ARTICLE

    A Longest Matching Resource Mapping Algorithm with State Compression Dynamic Programming Optimization

    Zhang Min, Teng Haibin, Jiang Ming, Wen Tao, Tang Jingfan

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 625-635, 2019, DOI:10.31209/2019.100000117

    Abstract Mapping from sentence phrases to knowledge graph resources is an important step for applications such as search engines, automatic question answering systems based on acknowledge base and knowledge graphs. The existing solution maps a simple phrase to a knowledge graph resource strictly or approximately from the text. However, it is difficult to detect phrases and map the composite semantic resource. This paper proposes a longest matching resource mapping scheme to solve this problem, namely, to find the longest substring in a sentence that can match the knowledge base resource. Based on this scheme, we propose More >

  • Open Access

    ARTICLE

    An Improved Method for Web Text Affective Cognition Computing Based on Knowledge Graph

    Bohan Niu1,*, Yongfeng Huang2

    CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 1-14, 2019, DOI:10.32604/cmc.2019.06032

    Abstract The goal of research on the topics such as sentiment analysis and cognition is to analyze the opinions, emotions, evaluations and attitudes that people hold about the entities and their attributes from the text. The word level affective cognition becomes an important topic in sentiment analysis. Extracting the (attribute, opinion word) binary relationship by word segmentation and dependency parsing, and labeling those by existing emotional dictionary combined with webpage information and manual annotation, this paper constitutes a binary relationship knowledge base. By using knowledge embedding method, embedding each element in (attribute, opinion, opinion word) as More >

Displaying 41-50 on page 5 of 47. Per Page