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SwCS: Section-Wise content similarity Approach to Exploit Scientific Big Data

Computers, Materials & Continua 2021年第4期67卷 877-894页

作者： Kashif Irshad Muhammad Tanvir Afzal Sanam Shahla Rizvi Abdul Shahid Rabia Riaz Tae-Sun Chung Department of Computer Science Capital University of Science and TechnologyIslamabadPakistan Department of Computer Science NAMAL InstituteMianwali42250Pakistan Raptor Interactive(Pty)Ltd. Eco BoulevardWitch Hazel AveCenturion0157South Africa Institute of Computing Kohat University of Science and TechnologyPakistan Department of CS&IT University of Azad Jammu and KashmirMuzaffarabad13100Pakistan Department of Artificial Intelligence Ajou UniversityKorea

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 *** 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 ***,the content of the papers are compared to list the relevant papers from a *** conventional method results in a long list of papers that is often impossible to interpret ***,the need for a novel approach that intelligently utilizes the available data is ***,the primary element of the scientific knowledge base is a research article,which consists of various logical sections such as the Abstract,Introduction,Related Work,Methodology,Results,and ***,this study utilizes these logical sections of research articles,because they hold significant potential in finding relevant *** this study,comprehensive experiments were performed to determine the role of the logical sections-based terms indexing method in improving the quality of results(i.e.,retrieving relevant papers).Therefore,we proposed,implemented,and evaluated the logical sections-based content comparisons method to address the research objective with a standard method of indexing *** section-based approach outperformed the standard content-based approach in identifying relevant documents from all classified topics of computer ***,the proposed approach extracted 14%more relevant results from the entire *** the experimental results suggested that employing a finer content similarity technique improved the quality of results,the proposed approach has led the foundation of knowledge-based startups.

关键词： Scientific big data ACM classification term indexing content similarity cosine similarity

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A Knowledge Graph-Based Deep Learning Framework for Efficient content similarity Search of Sustainable Development Goals Data

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Data Intelligence 2023年第3期5卷 663-684页

作者： Irene Kilanioti George A.Papadopoulos School of Electrical and Computer Engineering National Technical University of Athens9 Heroon Polytechneiou St.Zografou Campus Athens15780Greece Department of Computer Science University of Cyprus1 University AvenueAglantziaCY-2109NicosiaCyprus

Sustainable development denotes the enhancement ofliving standards in the present without compromising future generations'*** Development Goals(SDGs)quantify the accomplishment of sustainable development and pave the way for a world worth living in for future *** can contribute to the achievement of the SDGs by guiding the actions of practitioners based on the analysis of SDG data,as intended by this *** propose a framework of algorithms based on dimensionality reduction methods with the use of Hilbert Space Filling Curves(HSFCs)in order to semantically cluster new uncategorised SDG data and novel indicators,and efficiently place them in the environment of a distributed knowledge graph ***,a framework of algorithms for insertion of new indicators and projection on the HSFC curve based on their transformer-based similarity assessment,for retrieval of indicators and loadbalancing along with an approach for data classification of entrant-indicators is ***,a thorough case study in a distributed knowledge graph environment experimentally evaluates our *** results are presented and discussed in light of theory along with the actual impact that can have for practitioners analysing SDG data,including intergovernmental organizations,government agencies and social welfare *** approach empowers SDG knowledge graphs for causal analysis,inference,and manifold interpretations of the societal implications of SDG-related actions,as data are accessed in reduced retrieval *** facilitates quicker measurement of influence of users and communities on specific goals and serves for faster distributed knowledge matching,as semantic cohesion of data is preserved.

关键词： content similarity Distributed knowledge graphs Sustainable Development Goals Hilbert space filling curves Deep learning

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Exploiting Structural Similarities to Classify Citations

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Computers, Materials & Continua 2021年第2期66卷 1195-1214页

作者： Muhammad Saboor Ahmed Muhammad Tanvir Afzal Capital University of Science and Technology IslamabadPakistan

Citations play an important role in the scientific community by assisting in measuring multifarious policies like the impact of journals,researchers,institutions,and *** cite papers for different reasons,such as extending previous work,comparing their study with the state-of-the-art,providing background of the field,*** recent years,researchers have tried to conceptualize all citations into two broad categories,important and *** 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(2)Enhancing the impact factor calculation mechanism by more strongly weighting important citations,and(3)Improving researcher,institutional,and university rankings by only considering important *** of these uses depend upon correctly identifying the important citations from the list of all citations in a *** date,researchers have utilized many features to classify citations into these broad categories:cue phrases,in-text citation counts,and metadata features,***,contemporary approaches are based on identification of in-text citation counts,mapping sections onto the Introduction,Methods,Results,and Discussion(IMRAD)structure,identifying cue phrases,*** such features accurately is a challenging task and is normally conducted manually,with the accuracy of citation classification demonstrated in terms of these manually extracted *** research proposes to examine the content of the cited and citing pair to identify important citing papers for each cited *** content similarity approach was adopted from research paper recommendation ***,a novel section-based content similarity approach is also *** results show that solely using the abstract of the cited and citing papers can achieve similar accuracy as the stateof-the-art *** makes the propose

关键词： Section-wise similarity citation classification content similarity important citation

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Hierarchical Stream Clustering Based NEWS Summarization System

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Computers, Materials & Continua 2022年第1期70卷 1263-1280页

作者： M.Arun Manicka Raja S.Swamynathan Department of Computer Science and Engineering RMKCollege of Engineering and TechnologyChennai602106India Department of Information Science and Technology College of Engineering GuindyAnna UniversityChennai600025India

News feed is one of the potential information providing sources which give updates on various topics of different *** 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 *** this paper,the news summarization system is proposed for the news data streams from RSS feeds and Google *** news stream analysis requires live content,the news data are continuously collected for our *** contributions of thiswork involve domain corpus based news collection,news content extraction,hierarchical clustering of the news and summarization of *** of the existing news summarization systems lack in providing dynamic content with domain wise *** is alleviated in our proposed systemby tagging the news feed with domain corpuses and organizing the news streams with the hierarchical structure with topic wise ***,the news streams are summarized for the users with a novel summarization *** proposed summarization system generates topic wise summaries effectively for the user and no system in the literature has handled the news summarization by collecting the data dynamically and organizing the content *** proposed system is compared with existing systems and achieves better results in generating news *** Online news content editors are highly benefitted by this system for instantly getting the news summaries of their domain interest.

关键词： News feed content similarity parallel crawler collaborative filtering hierarchical clustering news summarization

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Dynamic Trust Model Based on Service Recommendation in Big Data

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Computers, Materials & Continua 2019年第3期58卷 845-857页

作者： Gang Wang Mengjuan Liu Xi’an University of Finance and Economics Xi’an710100China Shaanxi Radio and Television University Xi’an710068China.

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 *** management is an effective solution to deal with these malicious *** paper gave a trust computing model based on service-recommendation in big *** model takes into account difference of recommendation trust between familiar node and stranger ***,to ensure accuracy of recommending trust computing,paper proposed a fine-granularity similarity computing method based on the similarity of service concept domain *** model is more accurate in computing trust value of cyber service nodes and prevents better cheating and attacking of malicious service *** results illustrated our model is effective.

关键词： Trust model recommendation trust content similarity ontology big data.

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