Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (4)
  • Open Access

    ARTICLE

    Hierarchical Stream Clustering Based NEWS Summarization System

    M. Arun Manicka Raja1,*, S. Swamynathan2

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1263-1280, 2022, DOI:10.32604/cmc.2022.019451 - 07 September 2021

    Abstract News feed is one of the potential information providing sources which give updates on various topics of different domains. These updates on various topics need to be collected since the domain specific interested users are in need of important updates in their domains with organized data from various sources. In this paper, the news summarization system is proposed for the news data streams from RSS feeds and Google news. Since news stream analysis requires live content, the news data are continuously collected for our experimentation. The major contributions of this work involve domain corpus based… More >

  • Open Access

    ARTICLE

    SwCS: Section-Wise Content Similarity Approach to Exploit Scientific Big Data

    Kashif Irshad1, Muhammad Tanvir Afzal2, Sanam Shahla Rizvi3, Abdul Shahid4, Rabia Riaz5, Tae-Sun Chung6,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 877-894, 2021, DOI:10.32604/cmc.2021.014156 - 12 January 2021

    Abstract The growing collection of scientific data in various web repositories is referred to as Scientific Big Data, as it fulfills the four “V’s” of Big Data–-volume, variety, velocity, and veracity. This phenomenon has created new opportunities for startups; for instance, the extraction of pertinent research papers from enormous knowledge repositories using certain innovative methods has become an important task for researchers and entrepreneurs. Traditionally, the content of the papers are compared to list the relevant papers from a repository. The conventional method results in a long list of papers that is often impossible to interpret… More >

  • Open Access

    ARTICLE

    Exploiting Structural Similarities to Classify Citations

    Muhammad Saboor Ahmed*, Muhammad Tanvir Afzal

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1195-1214, 2021, DOI:10.32604/cmc.2020.012619 - 26 November 2020

    Abstract Citations play an important role in the scientific community by assisting in measuring multifarious policies like the impact of journals, researchers, institutions, and countries. Authors cite papers for different reasons, such as extending previous work, comparing their study with the state-of-the-art, providing background of the field, etc. In recent years, researchers have tried to conceptualize all citations into two broad categories, important and incidental. Such a categorization is very important to enhance scientific output in multiple ways, for instance, (1) Helping a researcher in identifying meaningful citations from a list of 100 to 1000 citations… More >

  • Open Access

    ARTICLE

    Dynamic Trust Model Based on Service Recommendation in Big Data

    Gang Wang1,*, Mengjuan Liu2

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 845-857, 2019, DOI:10.32604/cmc.2019.03678

    Abstract In big data of business service or transaction, it is impossible to provide entire information to both of services from cyber system, so some service providers made use of maliciously services to get more interests. Trust management is an effective solution to deal with these malicious actions. This paper gave a trust computing model based on service-recommendation in big data. This model takes into account difference of recommendation trust between familiar node and stranger node. Thus, to ensure accuracy of recommending trust computing, paper proposed a fine-granularity similarity computing method based on the similarity of More >

Displaying 1-10 on page 1 of 4. Per Page