Transcoding for web accessibility for the blind : semantics from structure

True accessibility requires minimizing the scanning time to find a particular piece of information. Sequentially reading web pages do not provide this type of accessibility, for instance before the user gets to the actual text content of the page it has to go through a lot of menus and headers. However if the user could navigate a web page based through semantically classified blocks then the user could jump faster to the actual content of the page, skipping all the menus and other parts of the page. We propose a transcoding engine that tackles accessibility at two distinct, yet complementary, levels: for specific known sites and general unknown sites. We present a tool for building customized scripts for known sites that turns this process in an extremely simple task, which can be performed by anyone, without any expertise. For general unknown sites, our approach relies on statistical analysis of the structural blocks that define a web page to infer a semantic for the block.(undefined

Winnowing ontologies based on application use

The requirements of specific applications and services are often over estimated when ontologies are reused or built. This sometimes results in many ontologies being too large for their intended purposes. It is not uncommon that when applications and services are deployed over an ontology, only a few parts of the ontology are queried and used. Identifying which parts of an ontology are being used could be helpful to winnow the ontology, i.e., simplify or shrink the ontology to smaller, more fit for purpose size. Some approaches to handle this problem have already been suggested in the literature. However, none of that work showed how ontology-based applications can be used in the ontology-resizing process, or how they might be affected by it. This paper presents a study on the use of the AKT Reference Ontology by a number of applications and services,and investigates the possibility of relying on this usage information to winnow that ontology

Ontology Driven Web Extraction from Semi-structured and Unstructured Data for B2B Market Analysis

The Market Blended Insight project1 has the objective of improving the UK business to business marketing performance using the semantic web technologies. In this project, we are implementing an ontology driven web extraction and translation framework to supplement our backend triple store of UK companies, people and geographical information. It deals with both the semi-structured data and the unstructured text on the web, to annotate and then translate the extracted data according to the backend schema