ANN: Preview release of conTEXT for Linked-Data based text analytics

Hi all,
We are happy to announce the preview release of conTEXT — a platform for
lightweight text analytics using Linked Data.

To try it out please visit http://context.aksw.org

conTEXT enables social Web users to semantically analyze text corpora (such
as blogs, RSS/Atom feeds, Facebook, G+, Twitter or SlideWiki.org decks) and
provides novel ways for browsing and visualizing the results. The main
components of the conTEXT architecture are:

* Collector -> utilizes standard information access methods and protocols
as well as customized crawlers for building a corpus.
* Annotator ->  employs Natural Language Processing (NLP) services
(currently FOX[1] and DBpedia-Spotlight[2]) to link unstructured
information sources to the Linked Open Data cloud through DBpedia.
* Enricher -> utilizes DBpedia as well as matching with pre-defined
natural-language patterns  (BOA patterns[3]) to enrich data for exploration
and visualization.
* Mashup builder -> employs NLP Interchange Format (NIF[4])to deal with the
heterogeneity when dealing with multiple disparate NLP services.
* Feedback creator ->  enable users to refine the generated annotations
utilizing the RDFa Content Editor (RDFaCE[5])
* Visualizer -> generates different interactive views on the analyzed data
employing the Exhibit and D3.js libraries.

For more information on conTEXT visit:
* Online demo:  http://context.aksw.org
* Screencast: http://youtu.be/EiGdkDRu_Ew
* Some examples of analyzed corpora:  CNN, BBC, AKSW, LOD2 blogs or tweets
from Bill Gates, Barack Obama, Ali Khalili or Sören Auer
 * Publication (under review): Ali Khalili, Sören Auer, Axel-Cyrille Ngonga
Ngomo: conTEXT – Lightweight Text Analytics using Linked Data
* There will be a Webinar to introduce the main features of conTEXT on
Thursday, January 30, 2014, 4:00 PM - 5:00 PM CET. For further information,
visit https://www4.gotomeeting.com/register/334511455

Please help us to further improve the conTEXT by sending us your feedback
through the feedback button on the conTEXT website.

I would like to thank the members of AKSW research group 6] in particular
Prof. Sören Auer as well as the LOD2 project [7] for their support.

Ali Khalili
AKSW research group

[1] http://aksw.org/Projects/FOX.html
[2] http://spotlight.dbpedia.org/
[3] http://aksw.org/Projects/BOA.html
[4] http://nlp2rdf.org/
[5] http://rdface.aksw.org
[6] http://aksw.org
[7] http://lod2.eu