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  • Open Access

    ARTICLE

    Leveraging Readability and Sentiment in Spam Review Filtering Using Transformer Models

    Sujithra Kanmani*, Surendiran Balasubramanian

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1439-1454, 2023, DOI:10.32604/csse.2023.029953

    Abstract Online reviews significantly influence decision-making in many aspects of society. The integrity of internet evaluations is crucial for both consumers and vendors. This concern necessitates the development of effective fake review detection techniques. The goal of this study is to identify fraudulent text reviews. A comparison is made on shill reviews vs. genuine reviews over sentiment and readability features using semi-supervised language processing methods with a labeled and balanced Deceptive Opinion dataset. We analyze textual features accessible in internet reviews by merging sentiment mining approaches with readability. Overall, the research improves fake review screening by using various transformer models such… More >

  • Open Access

    ARTICLE

    Semantic Modeling of Events Using Linked Open Data

    Sehrish Jamil1, Salma Noor1,*, Iftikhar Ahmed2, Neelam Gohar1, Fouzia1

    Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 511-524, 2021, DOI:10.32604/iasc.2021.017770

    Abstract Significant happenings in terms of spatio-temporal factors are called events. In the digital age, these events and their associated features are scattered in various databases on the Internet. The event data are in heterogeneous formats, which are often not machine-readable. This leads to a lack of unification of event-related knowledge across different domains and results in a research gap in terms of event modeling and representation. Specialized event models are needed to overcome this gap and integrate relevant information of different similar events occurring worldwide. Our research explores the problem of heterogeneity in specialized event modeling and takes modeling for… More >

  • Open Access

    ARTICLE

    Ensuring Readability of Electronic Records Based on Virtualization Technology in Cloud Storage

    Qirun Wang1,2, Fujian Zhu3,4, Yan Leng3,4, Yongjun Ren3,4,*, Jinyue Xia5

    Journal on Internet of Things, Vol.1, No.1, pp. 33-39, 2019, DOI:10.32604/jiot.2019.05898

    Abstract With the rapid development of E-commerce and E-government, there are so many electronic records have been produced. The increasing number of electronic records brings about storage difficulties, the traditional electronic records center is difficult to cope with the current fast growth requirements of electronic records storage and management. Therefore, it is imperative to use cloud storage technology to build electronic record centers. However, electronic records also have weaknesses in the cloud storage environment, and one of them is that once electronic record owners or managers lose physical control of them, the electronic records are more likely to be tampered with… More >

  • Open Access

    ARTICLE

    Readability Assessment of Textbooks in Low Resource Languages

    Zhijuan Wang1,2, Xiaobin Zhao1,2, Wei Song1,*, Antai Wang3

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 213-225, 2019, DOI:10.32604/cmc.2019.05690

    Abstract Readability is a fundamental problem in textbooks assessment. For low re-sources languages (LRL), however, little investigation has been done on the readability of textbook. In this paper, we proposed a readability assessment method for Tibetan textbook (a low resource language). We extract features based on the information that are gotten by Tibetan segmentation and named entity recognition. Then, we calculate the correlation of different features using Pearson Correlation Coefficient and select some feature sets to design the readability formula. Fit detection, F test and T test are applied on these selected features to generate a new readability assessment formula. Experiment… More >

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