Epiphany: Adaptable RDFa Generation Linking the Web of Documents to the Web of Data

نویسندگان

  • Benjamin Adrian
  • Jörn Hees
  • Ivan Herman
  • Michael Sintek
  • Andreas Dengel
چکیده

The appearance of Linked Open Data (LOD) was an important milestone for reaching a Web of Data. More and more RDF data sets get published to be consumed and integrated into a variety of applications. Pointing out one application, Linked Data can be used to enrich web pages with semantic annotations. This gives readers the chance to recall Semantic Web’s knowledge about text passages. RDFa provides a well-defined base, as it extends HTML tags in web pages to a form that contains RDF data. Nevertheless, asking web authors to manually annotate their web pages with semantic annotations is illusive. We present Epiphany, a service that annotates Linked Data to web pages automatically by creating RDFa enhanced versions of the input HTML pages. In Epiphany, Linked Data can be any RDF dataset or mashup (e.g., DBpedia, BBC programs, etc.). Based on ontology-based information extraction and the dataset, Epiphany generates an RDF graph about a web page’s content. Based on this RDF graph, RDFa annotations are generated and integrated in an RDFa enhanced version of the web page. Authors can use Epiphany to get RDFa enhanced versions of their articles that link to Linked Data models. Readers may use Epiphany to receive RDFa enhanced versions of web pages while surfing. We analysed results of Epiphany with Linked Data from BBC about music biographies and show a similar quality compared to results of Open Calais. Epiphany provides annotations from a couple of Linked Data sets.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The Callimachus Project: RDFa as a Web Template Language

The uptake of semantic technology depends on the availability of simple tools that enable Web developers to build complete applications, with particular emphasis on the last mile, the user interface. RDFa is a vocabulary for adding semantic annotations to standard XHTML and HTML5 documents. This allows the page to contain machine-readable content that is easier to find and mashable with other c...

متن کامل

Semantic Navigator: Use of Semantic Data in Web Navigation

Semantic web search engines can take advantage of machineunderstandable data published on the Web to provide more precise search results and advanced query capabilities. Semantic data embedded in web documents (serialized as RDFa or microformats, for example) can be used in conjunction with a semantic web search engine to provide a better web navigation experience. We present Semantic Navigator...

متن کامل

RRLUFF: Ranking function based on Reinforcement Learning using User Feedback and Web Document Features

Principal aim of a search engine is to provide the sorted results according to user’s requirements. To achieve this aim, it employs ranking methods to rank the web documents based on their significance and relevance to user query. The novelty of this paper is to provide user feedback-based ranking algorithm using reinforcement learning. The proposed algorithm is called RRLUFF, in which the rank...

متن کامل

RDFa2: Lightweight Semantic Enrichment for Hypertext Content

RDFa is a syntactic format that allows RDF triples to be integrated into hypertext content of HTML/XHTML documents. Although a growing number of methods or tools have been designed attempting at generating or digesting RDFa, comparatively little work has been carried out on finding a generic solution for publishing existing RDF data sets with the RDFa serialisation format. This paper proposes a...

متن کامل

Web pages ranking algorithm based on reinforcement learning and user feedback

The main challenge of a search engine is ranking web documents to provide the best response to a user`s query. Despite the huge number of the extracted results for user`s query, only a small number of the first results are examined by users; therefore, the insertion of the related results in the first ranks is of great importance. In this paper, a ranking algorithm based on the reinforcement le...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2010