The transformation of Websites to APIs refers to the steps needed to leverage the Web content to self-defined data structures that can be consumed by machines and Web agents, called semantic annotations. Cornerstone requirement for this to happen is the incorporation of the correct vocabulary terms in a website. The presented approach addresses this challenge by helping to identify the most appropriate set of Linked Open Vocabulary terms for a given Web content context by leveraging the existing dynamics within the LOV graph and the LOD cloud.
A user interface (UI) has been added to the vocab-recommender which makes it easier to submit queries to the backend API. A link has been added to the main project page of vocab-recommender.
Read More - December 25, 2016The research paper was presented at SEMANTICS2016 at the Data Science track. The slides have already been shared online via slideshare.
Read More - September 12, 2016An implementation details overview of the underlying LOVR methodology of the vocab-recommender framework has been accepted as a demo/poster paper, under the title Towards a Vocabulary Terms Discovery Assistant, that was submitted to the SEMANTiCS 2016 conference that will take place in Leipzig in September.
Read More - August 5, 2016New updates in the ranking algorithm have been accepted in a full research paper, under the title Linked Open Vocabulary Ranking and Terms Discovery, that was submitted to the SEMANTiCS 2016 conference that will take place in Leipzig in September.
Read More - June 11, 2016The first working version of the framework is out and supports the extraction and recommendation of static HTML parts (i.e. images, etc.).
Read More - March 15, 2016Great news! The PhD topic that I am working on received a scholarship by Netidee.
Read More - November 11, 2015A short video has been published on YouTube to explain in 2’ the idea behind the vocab-recommender project, which consists my PhD topic. Check it here!
Read More - October 31, 2015