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  • Open Access

    ARTICLE

    Ontology-Based Semantic Search Framework for Disparate Datasets

    Paramjeet Kaur1, Parma Nand1, Salman Naseer2, Akber Abid Gardezi3, Fawaz Alassery4, Habib Hamam5, Omar Cheikhrouhou6, Muhammad Shafiq7,*

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1717-1728, 2022, DOI:10.32604/iasc.2022.023063

    Abstract The public sector provides open data to create new opportunities, stimulate innovation, and implement new solutions that benefit academia and society. However, open data is usually available in large quantities and often lacks quality, accuracy, and completeness. It may be difficult to find the right data to analyze a target. There are many rich open data repositories, but they are difficult to understand and use because these data can only be used with a complex set of keyword search options, and even then, irrelevant or insufficient data may eventually be retrieved. To alleviate this situation, ontology-based semantic search has been… 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

    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 applied to various systems, the… More >

  • Open Access

    ARTICLE

    Privacy-Preserving Content-Aware Search Based on Two-Level Index

    Zhangjie Fu1,*, Lili Xia1, Yuling Liu2, Zuwei Tian3

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 473-491, 2019, DOI:10.32604/cmc.2019.03785

    Abstract Nowadays, cloud computing is used more and more widely, more and more people prefer to using cloud server to store data. So, how to encrypt the data efficiently is an important problem. The search efficiency of existed search schemes decreases as the index increases. For solving this problem, we build the two-level index. Simultaneously, for improving the semantic information, the central word expansion is combined. The purpose of privacy-preserving content-aware search by using the two-level index (CKESS) is that the first matching is performed by using the extended central words, then calculate the similarity between the trapdoor and the secondary… More >

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