Entwicklungstrends im Web Information Retrieval: Neue Potentiale für die Webrecherche durch Personalisierung & Web 2.0-Technologien [Trends in web information retrieval: New possibilities for internet research through personalization, social search and Web 2.0 technologies.]

New developments in the fields of social search and personalization as well as the spreading use of Web 2.0 technologies and services impact the possibilities and constraints of internet research. The first part of the paper gives an overview of new research options in blog search engines and social bookmark communities. The second part of the text discusses new social search and personalization services at Google, Yahoo and MSN. The article finishes with the introduction of a project that strives to build up an information science community in the field web information retrieval for German-speaking countries

Pre-service teachers’ search strategies when sourcing educational information on the Internet

Teachers need to be able to inform and justify their teaching practice based on available research knowledge. When searching for research knowledge, the Internet plays a crucial role as it allows teachers to search for and access evidence long after their own education at university. On the Internet, however, educational information can have varying levels of scientific groundedness (e.g., science articles or blogs from colleagues), and research indicates that (pre-service) teachers struggle to find, select, and evaluate online educational information. It is precisely for this reason that it is important to educate (pre-service) teachers on how to competently source online information. This study describes pre-service teachers’ search strategies when sourcing online educational information about the topic “students’ use of mobile phones in class.” It sheds light on their use of (1) basic or advanced search strategies and (2) the role of Internet-specific epistemological beliefs (ISEBs). N = 77 pre-service teachers conducted a realistic search on the Internet and selected those web items (WI) that they perceived relevant for justifying whether mobile phones should be used in class. Their sourcing behavior was screen-recorded and analyzed. Most selected WI were found via search engines of Google LLC (91.4%). Advanced search strategies were defined as (1) using two or more search engines (performed by 62.3% of participants), (2) adapting search terms and/or formulating new search terms (90.9%), (3) selecting at least one WI that was not listed among the first four ranks on the first search engine results page (54.7%), and (4) checking for the trustworthiness of the author/source (14.3%) or the quality of the content (13%). Binary logistic regressions were used to analyze the relationship between ISEBs and (1) search strategies and (2) science-relatedness of WI as dependent variables. The predictor ISEB did not contribute to the models, meaning that differences in participants’ ISEBs did not significantly relate to their search strategies nor to the science-relatedness of WI, all β ≤ |0.36|, Wald ≤ 0.64, p ≥ 0.43. The role of pre-service teachers’ search strategies is discussed with respect to teachers’ evidence-informed reasoning and its implications for teacher education.Peer Reviewe

Influence of language and file type on the web visibility of top European universities

Purpose The purpose of this paper is to detect whether both file type (a set of rich and web files) and language (English, Spanish, German, French and Italian) influence the web visibility of European universities. Design/methodology/approach A webometrics analysis of the top 200 European universities (as ranked in the Ranking web of World Universities) was carried out by a manual query for each official URL identified by using the Google search engine (April 2012). A correlation analysis between visibility and file format page count is offered according to language. Finally, a prediction of visibility is shown by using the SMOreg function. Findings The results indicate that Spanish and English are the languages that correlate most highly with web visibility. This correlation becomes greater though moderate when considering only PDF files. Research limitations/implications The results are limited due to the low correlation between overall page count and visibility. The lack of an accurate search engine that would assist in link counting procedures makes this process difficult. Originality/value An observed increase in correlation although moderate while analysing PDF files (in English and Spanish) is considered to be meaningful. This may indirectly confirm that specific file formats and languages generate different web visibility behaviour on European university web sites.Orduña Malea, E.; Ortega, JL.; Aguillo, IF. (2014). Influence of language and file type on the web visibility of top European universities. Aslib Journal of Information Management. 66(1):96-116. doi:10.1108/AJIM-02-2013-0018S96116661Aguillo, I.F. and Granadino, B. (2006), “Indicadores web para medir la presencia de las universidades en la Red”, Revista de universidad y Sociedad del Conocimiento, Vol. 3 No. 1, pp. 68-75.Aguillo, I.F. , Granadino, B. , Ortega, J.L. and Prieto, J.A. (2006), “Scientific research activity and communication measured with cybermetrics indicators”, Journal of the American Society for Information Science and Tecnology, Vol. 57 No. 10, pp. 1296-1302.Aguillo, I.F. , Ortega, J.L. and Fernández, M. (2008), “Webometric ranking of World universities: introduction, methodology, and future developments”, Higher Education in Europe, Vol. 33 Nos 2-3, pp. 233-244.Angus, E., Thelwall, M., & Stuart, D. (2008). General patterns of tag usage among university groups in Flickr. Online Information Review, 32(1), 89-101. doi:10.1108/14684520810866001Araujo Serna, L. and Martínez Romo, J. (2009), “Detección de Web Spam basada en la recuperación automática de enlaces”, Procesamiento del lenguaje natural, No. 42, pp. 39-46.Bar-Ilan, J. (2002), “Methods for measuring search engine performance over time”, Journal of the American Society for Information Science and Technology, Vol. 53 No. 4, pp. 308-319.Bar-Ilan, J. (2005), “What do we know about links and linking? A framework for studying links in academic environments”, Information Processing & Management, Vol. 41 No. 3, pp. 973-986.Cho, Y. and García-Molina, H. (2000), “The evolution of the web and implications for an incremental crawler”, Proceedings of the 26th International Conference on Very Large Data Bases, pp. 200-209.Fetterly, D. , Manasse, M. , Najork, M. and Wiener, J. (2003), “A large scale study of the evolution of web pages”, Proceedings of the Twelfth International Conference on World Wide Web, pp. 669-678.Garfield, E. (1967), “English – An international language for science?”, Current Contents, pp. 19-20.Gerrand, P. (2007), “Estimating linguistic diversity on the internet: a taxonomy to avoid pitfalls and paradoxes”, Journal of Computer-Mediated Communication, Vol. 12 No. 4, pp. 1298-1321.Ingwersen, P. (1998). The calculation of web impact factors. Journal of Documentation, 54(2), 236-243. doi:10.1108/eum0000000007167Koehler, W. (2004), “A longitudinal study of web pages continued: a consideration of document persistence”, Information Research, Vol. 9 No. 2.Kousha, K. , Thelwall, M. and Abdoli, M. (2012), “The role of online videos in research communication: a content analysis of YouTube videos cited in academic publications”, Journal of the American Society for Information Science and Technology, Vol. 63 No. 9, pp. 1710-1727.Kousha, K. , Thelwall, M. and Rezaie, S. (2010), “Using the web for research evaluation: the integrated online impact indicator”, Journal of Informetrics, Vol. 4 No. 1, pp. 124-135.Lawrence, S. and Giles, L. (1999), “Accessibility of information on the web”, Nature, Vol. 400, pp. 107-109.Lazarinis, F. (2007), “Web retrieval systems and the Greek language: do they have an understanding?”, Journal of information science, Vol. 33 No. 5, pp. 622-636.Lewandowski, D. (2008). Problems with the use of web search engines to find results in foreign languages. Online Information Review, 32(5), 668-672. doi:10.1108/14684520810914034Martins, B. and Silva, M.J. (2005), “Language identification in web pages”, Proceedings of the ACM Symposium of Applied Computing, Santa Fe, NM, ACM, New York, NY, pp. 764-768.Moukdad, H. and Cui, H. (2005), “How do search engines handle Chinese queries?”, Webology, Vol. 2 No. 3, p.Ntoulas, A. , Najork, M. , Manasse, M. and Fetterly, D. (2006), “Detecting spam web pages through content analysis”, Proceedings of the 15th International Conference on World Wide Web, AMA, New York, NY, pp. 83-92.O'Neill, E.T. , Lavoie, B.F. and Bennett, R. (2003), “Trends in the evolution of the public Web: 1998-2002”, D-Lib Magazine, Vol. 9 No. 4, available at: www.dlib.org/dlib/april03/lavoie/04lavoie.html (accessed 11 February 2013).Orduña-Malea, E. (2012), “Graphic, multimedia, and blog-content presence in the Spanish academic web-space”, Cybermetrics, Vol. 15, available at: http://cybermetrics.cindoc.csic.es/articles/v16i1p3.pdf (accessed 11 February 2013).Orduña-Malea, E. and Ontalba-Ruipérez, J-A. (2013), “Proposal for a multilevel university cybermetric analysis model”, Scientometrics, Vol. 95 No. 3, pp. 863-884.Orduña-Malea, E. , Serrano-Cobos, J. , Ontalba-Ruipérez, J-A. and Lloret-Romero, N. (2010), “Presencia y visibilidad web de las universidades públicas españolas”, Revista española de documentación científica, Vol. 33 No. 2, pp. 246-278.Payne, N. and Thelwall, M. (2007), “A longitudinal study of academic webs: growth and stabilization”, Scientometrics, Vol. 71 No. 3, pp. 523-539.Seeber, M. , Lepori, B. , Lomi, A. , Aguillo, I. and Barberio, V. (2012), “Factors affecting web links between European higher education institutions”, Journal of Informetrics, Vol. 6, pp. 435-447.Thelwall, M. (2008a), “Bibliometrics to webometrics”, Journal of Information Science, Vol. 34 No. 4, pp. 605-621.Thelwall, M. (2008b), “Quantitative comparisons of search engine results”, Journal of the American Society for Information Science and Technology, Vol. 59 No. 11, pp. 1702-1710.Thelwall, M. and Tang, R. (2003), “Disciplinary and linguistic considerations for academic web linking: an exploratory hyperlink mediated study with Mainland China and Taiwan”, Scientometrics, Vol. 58 No. 1, pp. 155-181.Thelwall, M. , Tang, R. and Price, L. (2003), “Linguistic patterns of academic web use in Western Europe”, Scientometrics, Vol. 56 No. 3, pp. 417-432.Vaughan, L. (2006), “Visualizing linguistic and cultural differences using web co-link data”, Journal of the American Society for Information Science and Technology, Vol. 57 No. 9, pp. 1178-1193.Vaughan, L. and Thelwall, M. (2004), “Search engine coverage bias: evidence and possible causes”, Information Processing & Management, Vol. 40 No. 4, pp. 693-707.Vaughan, L. and Zhang, Y. (2007), “Equal representation by search engines? A comparison of Web sites across countries and domains”, Journal of Computer-Mediated Communication, Vol. 12 No. 3, pp. 888-909.Wilkinson, D. , Harries, G. , Thelwall, M. and Price, L. (2003), “Motivations for academic web site interlinking: evidence for the web as a novel source of information on informal scholarly communication”, Journal of information science, Vol. 29 No. 1, pp. 49-56

A Large Visual, Qualitative, and Quantitative Dataset for Web Intelligence Applications

The Web is the communication platform and source of information par excellence. The volume and complexity of its content have grown enormously, with organizing, retrieving, and cleaning Web information becoming a challenge for traditional techniques. Web intelligence is a novel research area to improve Web-based services and applications using artificial intelligence and automatic learning algorithms, for which a large amount of Web-related data are essential. Current datasets are, however, limited and do not combine visual representation and attributes of Web pages. Our work provides a large dataset of 49,438 Web pages, composed of webshots, along with qualitative and quantitative attributes. This dataset covers all the countries in the world and a wide range of topics, such as art, entertainment, economics, business, education, government, news, media, science, and the environment, addressing different cultural characteristics and varied design preferences. We use this dataset to develop three Web Intelligence applications: knowledge extraction on Web design using statistical analysis, recognition of error Web pages using a customized convolutional neural network (CNN) to eliminate invalid pages, and Web categorization based solely on screenshots using a CNN with transfer learning to assist search engines, indexers, and Web directories.This work has been funded by the grant awarded by the Central University of Ecuador through budget certification No. 34 of March 25, 2022 for the development of the research project with code: DOCT-DI-2020-37

Penentuan Kerelevanan Dokumen Menggunakan Rangkaian Rambatan Balik

Information retrieval (IR) is one of the Computer Science branches that deals with accessing relevant information from a database. Several search engines have been developed to assist users in retrieving the relevant information from the Internet. However, due to information overload, some search engines are still incapable of returning only the most relevant documents to the users. Hence, this research aims to explore the use of Artificial Intelligence (AI) technique, particularly neural network (NN) in measuring the relevancy of each document compared to the users requests. Backpropagation learning algorithm has been used as a basis for learning in this study. Several phases are involved, namely as the identification of the document's atributes, implementation of NN, identification of NN parameters and development of simple search engine prototype. 53 documents have been uploaded into the database for evaluation purpose. These documents have been downloaded from the Seventh International World Wide Web Conferences. The documents are then used to test with two different queries; 'metadata' and 'multimedia'. A test for 'metadata' query achieved 100 percent recall and 50 percent precision. Whereas, the test for 'muItimedia ' query achieved 75 percent recall and 60 percent precision. The result shows that the usage of NN approaches has produced a high recall. The result is also tested using fallout and generality measurement. Fallout for both queries are 6 and 5.666 percent respectively. Whereas, the generality for both queries are 4.08 and 7.54 respectively

3D scanners in orthodontics—Current knowledge and future perspectives—A systematic review

Background: Nowadays the use of intraoral scanners has become a routine practice in orthodontics. It allows the introduction of many treatment innovations. One should consider to what extent intraoral scanners have influenced the everyday orthodontic practice and in what direction should the further research in this field be conducted. This study is aimed to systematically review and synthesize available controlled trials investigating the accuracy and efficacy of intraoral scanners for orthodontic purpose to provide clinically useful information and to direct further research in this field. Methods: A literature search of free text and MeSH terms was performed by using MedLine (PubMed), Scopus, Web of Science and Embase. The search engines were used to find studies on application of intraoral scanners in orthodontics (from 1950 to 30 September 2020). The following keywords were used: “intraoral scanners AND efficiency AND accuracy AND orthodontics”. Results: The number of potential identified articles was 71, including 61 from PubMed, two from Scopus, three from Web of Science and five from Embase. After removal of duplicates, 67 full-text articles were analyzed for inclusion criteria, 16 of them were selected and finally included in the qualitative synthesis. Conclusions: There are plenty of data available on accuracy and efficacy of different scanners. Scanners of the same generation from different manufacturers have almost identical accuracy. This is the reason why future similar research will not introduce much to the orthodontics. The challenge for the coming years is to find new applications of digital impressions in the orthodontic practice

Getting ahead of the curve: an investigation into how the Caltech Library succeeds in resource sharing (paper presented to the IFLA Interlending and Document Supply Conference (Paris, 2017)

This paper will address the challenges faced by the California Institute of Technology (Caltech) Library, its history in supplying research materials to its community, and the significant shift in its collections strategy in 2015 that directly affected how the Library would continue to provide information resources to its students, faculty, and staff through resource sharing. Prior to 2015, the Caltech Library had approached procuring information resources for its campus community in a hybrid model that married together the typical academic library process of interlibrary loan with a business or special library practice of purchasing material and charging users for the service. Based on a number of factors in 2015, this process shifted to a multi-faceted approach that utilized an increased use of consortia, mediated article purchasing, and an unmediated article acquisition process where our users can decide whether to use the normal interlibrary loan process or a “rush” alternative. This included embedding the unmediated rush option within search engines such as Web of Science and Ebsco Discovery Service (EDS). This paper will share the findings of this strategic change and the outcomes based on the data

Rodzina Google w służbie tłumacza. Wyszukiwanie terminologii z pomocą Internetu

Any specialised translation between languages requires knowledge of specific terminology. A variety of terminology sources can be found on the Internet, namely term banks, specialised dictionaries and glossaries. However, on many occasions they seem to be insufficient when it comes to the latest vocabulary related with the domains which utilize modern information technologies. The research shows that efficient use of search tools retrieves relevant equivalents of, at least, popular terms in the target language or defi nitions of concepts (when equivalents are not available) directly from the Internet viewed as an infinite term database itself. Beginning with the definition of terminology, the paper discusses the use of several Google search tools for retrieving specialised vocabulary, definitions of concepts and parallel texts. By applying examples from such fields as library and information science, it gives a detailed characteristics of various terminology search strategies with the use of a general search engine Google Web Search, a web directory Google Directory and specialised search engines Google Scholar and Book Search. Th e following methods are discussed: using a search engine as a bilingual dictionary, search operator define: phrase searches with Boolean operators or a verb, searching and browsing a web directory, advanced search for the retrieval of parallel texts and various search options. The results show that all the examined tools prove to be useful in terminology search for specialised translation.Wychodząc od definicji pojęć terminologia i termin, artykuł omawia możliwości wykorzystania różnych typów narzędzi platformy Google do przeszukiwania zasobów Internetu w celu znajdowania słownictwa specjalistycznego, definicji pojęć oraz tekstów paralelnych. Szczegółowo scharakteryzowano modele i strategie wyszukiwania terminologicznego z zastosowaniem wyszukiwarki ogólnej Google Web Search, katalogu tematycznego Google Directory oraz wyszukiwarek specjalistycznych Google Scholar i Book Search na przykładzie takich dziedzin, jak edukacja, informacja naukowa i bibliotekoznawstwo