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Exploring the Potentialities of Automatic Extraction of University Webometric Information

Journal of Data and Information Science 2020年第4期5卷 43-55页

作者： Gianpiero Bianchi Renato Bruni Cinzia Daraio Antonio Laureti Palma Giulio Perani Francesco Scalfati ISTAT Italian National Institute of StatisticsVia Cesare Balbo 16Rome 00184Italy DIAG Sapienza University of RomeVia Ariosto 25Rome 00185Italy

Purpose:The main objective of this work is to show the potentialities of recently developed approaches for automatic knowledge extraction directly from the universities’*** information automatically extracted can be potentially updated with a frequency higher than once per year,and be safe from manipulations or ***,this approach allows us flexibility in collecting indicators about the efficiency of universities’websites and their effectiveness in disseminating key *** new indicators can complement traditional indicators of scientific research(*** of articles and number of citations)and teaching(*** of students and graduates)by introducing further dimensions to allow new insights for“profiling”the analyzed ***/methodology/approach:webometrics relies on web mining methods and techniques to perform quantitative analyses of the *** study implements an advanced application of the webometric approach,exploiting all the three categories of web mining:web content mining;web structure mining;web usage *** information to compute our indicators has been extracted from the universities’websites by using web scraping and text mining *** scraped information has been stored in a NoSQL DB according to a semistructured form to allow for retrieving information efficiently by text mining *** provides increased flexibility in the design of new indicators,opening the door to new types of *** data have also been collected by means of batch interrogations of search engines(Bing,***)or from a leading provider of Web analytics(SimilarWeb,http://***).The information extracted from the Web has been combined with the University structural information taken from the European Tertiary Education Register(https://***/#/home),a database collecting information on Higher Education Institutions(HEIs)at European *** the above was used to perfo

关键词： Development of data and information services webometrics indicators Higher education institutions Automatic extraction Machine learning Optimization

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