Videos tagged with Semantic Web

Summary In this interview from QCon San Francisco 2008, Stu Charlton discusses what the Semantic Web is, RDFa, large-scale adoption of Semantic Web, the SPARQL query language, implementing Semantic Web capabilities in an application, triple stores, and performing a Semantic Web query. Bio Stuart Charlton is the Chief Software Architect for Elastra, a provider of Cloud Computing software infrast...

The Semantic Web presents the vision of a distributed, dynamically growing knowledge base founded on formal logic. Common users, however, seem to have problems even with the simplest Boolean expression. So how can we help users to query a web of logic that they do not seem to understand? One frequently proposed solution to address this problem is the use of natural language (NL) for knowledge s...

Berners-Lee's vision of the Semantic Web is hindered by a chicken-and-egg problem, which can be best solved by a bootstrapping method: creating enough structured data to motivate the development of applications. We believe that autonomously `Semantifying Wikipedia' is the best way to bootstrap. We choose Wikipedia as an initial data source, because it is comprehensive, high-quality, modestly si...

Lecture slides: Beyond string search: fast and accurate retrieval of entities and dependencies. Plan Document Understanding Cartoon Beyond strings, beyond bag of words Structure & Domain Knowledge Demos Plan Language Representation Semantic tagging (some examples) Statistical Methods for Semantic Tagging Example: WordNet Supersense labels Dependency Parsing ( Publicity Break ) Noise & R...

The authoring of tags - unlike the authoring of traditional metadata - is highly popular among users. This harbours unprecedented opportunities for organizing content. However, tags are still poorly understood. What do they ''mean'', in what senses are they similar to or different from metadata? Different tags support different communities, but how exactly do they reflect the plurality of opini...

Lecture slides: Semantic Annotation in the Alvis Project Alvis Project Limitation of the Keyword-Based Search Our Framework Annotation of Semantic Unit and Relation Requires Linguistic Processing Semantic Annotation with Linguistic Processing Semantic Abstraction Linguistic Analysis Specific Resources Are Needed Learning the Resources Named-entity Learning Terminology Acquisition by YaTea Examp...

Social bookmarking is a recent phenomenon which has the potential to give us a great deal of data about pages on the web. One major question is whether that data can be used to augment systems like web search. To answer this question, over the past year we have gathered what we believe to be the largest dataset from a social bookmarking site yet analyzed by academic researchers. Our dataset rep...

We see an evolutionary path to supporting semantic search over text facilitated by extractors and annotators for ever-growing collections of entity and relation types and search systems that exploit a smooth continuum between structured entities and relations on one hand and uninterpreted text on the other. The extractors and annotators will be imperfect and incomplete. Author: Soumen Chakrabar...

Lecture slides: WP 2: Learning Web-service Domain Ontologies Outline of the Presentation Learning Web-service Ontologies Application Mining GATE Case Study Data Sources A Typical Java Class Creating a Document Network GATE Comment Reference Network Transforming Networks into Feature Vectors Combining Feature Vectors LATINO & OntoGen Demo OntoGen Demo Dassault Case Study: Inclusion Dependenc...

Currently, one of the most practical application spaces for Semantic Web technologies is creating an ontological layer over existing legacy databases. Such layering allows flexible applications to be built without the cost of restructuring large amounts of data while maintaining the performance advantages of a relational database. Whereas applications designed to directly query a database encod...