The study presents the results divided into three categories: consensus, consensus tendency and without consensus. A web information system was developed to support four rounds of the survey, which received contributions from 16 experts (first round) and 14 respondents in the next three rounds. The opinions of these experts were evaluated on the future of libraries in Brazil in 2018. It presents the main results of a Delphi study conducted with library experts, involved in providing information products and services. This survey provides a brief review of state-of-the-art, challenges and solutions towards recommending and ranking tagged web documents in Social Bookmarking Systems (SBS). A lot of research works have already been published to tickle the problem by exploiting different features of folksonomy structure. However search results associated with query-tags are randomly ordered either by popularity, interestingness or reverse chronological order with most recent bookmarks on top of search results, which limits the effectiveness of information searching in social bookmarking systems. Social tags reflect not only human cognition on contents the document contains inbut also used as index-terms in social searching.
These social toolsallow its users to associate free chosen keywords (tags) with documents for future considerations.
Social bookmarking systems facilitateusers to store, manageand share tagged web documents through folk classification system. Social web applications like Facebook, YouTube, Delicious, Twitter and so many others have gained popularity among masses due to its versatility and potential of accommodating cultural perspectives in Social web paradigm. Library users to find books in which they are interested. Integrating tagging into library OPACs would create more opportunities for Library of Congress subject headings mostly identify the basic genres that the books in the sample belonged to, but added little additional information. The most frequently used tags were those that matched the Library of Congress subject headings, but there were a significant number of non-matching tags that offered useful additional information about the books in the sample. The tags were then classified into categories created by the researcher and examined using descriptive statistics inside Excel. The researcher harvested tags from ten books in the genres of science fiction and fantasy. This study has a largely quantitative methodology with some qualitative aspects. This study examines the extent to which LibraryThing tags match their equivalent Library of Congress subject headings and looks at whether they offer any additional information about the subject matter of the books to which they are applied.