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  • Open Access

    ARTICLE

    Construction of Intelligent Recommendation Retrieval Model of FuJian Intangible Cultural Heritage Digital Archives Resources

    Xueqing Liao*

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 677-690, 2023, DOI:10.32604/iasc.2023.037219 - 29 April 2023

    Abstract In order to improve the consistency between the recommended retrieval results and user needs, improve the recommendation efficiency, and reduce the average absolute deviation of resource retrieval, a design method of intelligent recommendation retrieval model for Fujian intangible cultural heritage digital archive resources based on knowledge atlas is proposed. The TG-LDA (Tag-granularity LDA) model is proposed on the basis of the standard LDA (Linear Discriminant Analysis) model. The model is used to mine archive resource topics. The Pearson correlation coefficient is used to measure the relevance between topics. Based on the measurement results, the FastText… More >

  • Open Access

    ARTICLE

    An Intelligent Recommendation System for Real Estate Commodity

    Tsung-Yin Ou1, Guan-Yu Lin2, Hsin-Pin Fu1, Shih-Chia Wei1, Wen-Lung Tsai3,*

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 881-897, 2022, DOI:10.32604/csse.2022.022637 - 08 February 2022

    Abstract Most real estate agents develop new objects by visiting unfamiliar clients, distributing leaflets, or browsing other real estate trading website platforms, whereas consumers often rely on websites to search and compare prices when purchasing real property. In addition to being time consuming, this search process renders it difficult for agents and consumers to understand the status changes of objects. In this study, Python is used to write web crawler and image recognition programs to capture object information from the web pages of real estate agents; perform data screening, arranging, and cleaning; compare the text of… 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

    A New Time-Aware Collaborative Filtering Intelligent Recommendation System

    Weijin Jiang1,2,3, Jiahui Chen1,*, Yirong Jiang4,*, Yuhui Xu1, Yang Wang1, Lina Tan1, Guo Liang5

    CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 849-859, 2019, DOI:10.32604/cmc.2019.05932

    Abstract Aiming at the problem that the traditional collaborative filtering recommendation algorithm does not fully consider the influence of correlation between projects on recommendation accuracy, this paper introduces project attribute fuzzy matrix, measures the project relevance through fuzzy clustering method, and classifies all project attributes. Then, the weight of the project relevance is introduced in the user similarity calculation, so that the nearest neighbor search is more accurate. In the prediction scoring section, considering the change of user interest with time, it is proposed to use the time weighting function to improve the influence of the More >

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