Heath, Tom and Motta, Enrico
(2008).
|
PDF (Accepted Manuscript)
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (412kB) | Preview |
| DOI (Digital Object Identifier) Link: | https://doi.org/10.1016/j.websem.2008.09.003 |
|---|---|
| Google Scholar: | Look up in Google Scholar |
Abstract
Revyu is a live, publicly accessible reviewing and rating Web site, designed to be usable by humans whilst transparently generating machine-readable RDF metadata for the Semantic Web, based on user input. The site uses Semantic Web specifications such as RDF and SPARQL, and the latest Linked Data best practices to create a major node in a potentially Web-wide ecosystem of reviews and related data. Throughout the implementation of Revyu design decisions have been made that aim to minimize the burden on users, by maximizing the reuse of external data sources, and allowing less structured human input (in the form of Web 2.0-style tagging) from which stronger semantics can later be derived. Links to external sources such as DBpedia are exploited to create human-oriented mashups at the HTML level, whilst links are also made in RDF to ensure Revyu plays a first class role in the blossoming Web of Data. In this paper we document design decisions made during the implementation of Revyu, discuss the techniques used for linking Revyu data with external sources, and outline how data from the site is being used to infer the trustworthiness of reviewers as sources of information and recommendations.
| Item Type: | Article |
|---|---|
| ISSN: | 1570-8268 |
| Keywords: | Semantic Web; Linked Data; Reviews; Ratings; Revyu |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Interdisciplinary Research Centre: | Centre for Research in Computing (CRC) |
| Item ID: | 12794 |
| Depositing User: | Enrico Motta |
| Date Deposited: | 27 Jan 2009 01:21 |
| Last Modified: | 15 May 2017 23:35 |
| URI: | http://oro.open.ac.uk/id/eprint/12794 |
| Share this page: |     |
Altmetrics | Scopus Citations |
Download history for this item
These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.
Altmetric
Altmetric