Knowledge mapping. Semantic Web. Sparql. Named graph. A named graph Named graphs are a simple extension of the RDF data model[2] through which graphs can be created but the model lacks an effective means of distinguishing between them once published on the Web at large. Named graphs and HTTP[edit] One conceptualization of the Web is as a graph of document nodes identified with URIs and connected by hyperlink arcs which are expressed within the HTML documents. By doing a HTTP GET on a URI (usually via a Web browser), a somehow-related document may be retrieved. This "follow your nose" approach also applies to RDF documents on the Web in the form of Linked Data, where typically an RDF syntax is used to express data as a series of statements, and URIs within the RDF point to other resources.
Describing a named graph Named graphs are a formalization of the intuitive idea that the contents of an RDF document (a graph) on the Web can be considered to be named by the URI of the document. Named graphs and RDF stores[edit] Example[edit] See also[edit] Www.markwatson.com/opencontent/book_lisp.pdf. Semantic Web – Annotation and Authoring.
Sentiment analysis. In the last few months, sentiment has become the next big thing in enterprise content processing. Manning & Napier, an investment firm, funded a number of projects for its search and content processing system that could determine what the computer scientists call "polarity" and I call the positive and negative aspect of a document. A human can read a document and make a comment like, "This customer is really annoyed at our warranty program," or "We need to get this letter over to marketing because our customer is raving about our new product. " Computers, as it turns out, can do a reasonably good job of determining the sentiment of a document or processing a large number of documents and providing a report that says, "Sixty-three percent of the messages about our service are positive. " Social media's impact Sentiment analysis is one of the facets of text analytics that can discern the softer or intentional components of a report, an e-mail or other communication.
Credibility rankings. SENSEnews (Hakia) Attensity.
Semantic search. Schema.org. Semantic technologies. Faviki. Google services (category)