Users will be able to search for documents by date, topic, person, location, etc. and will be able to do "document dives," collaboratively examining large sets of documents. Think of it as a card catalog for primary source documents. DocumentCloud is not meant to be a general document hosting service, like Scribd, Docstoc or Google Docs. Our goal is to build a service that makes source documents easier to find and share regardless of where they are hosted. It is a complement to these services, and not a competitor. the goal is to make documents even easier to find on search engines. DocumentCloud will have information about documents and relations between them, for example what locations, people, or organizations a group of documents have in common. Conceived of by journalists working at ProPublica and The New York Times, DocumentCloud will be managed as an independent nonprofit.
Free Downloads and Links - ODBMS.ORG was created to serve faculty and students at educational and research institutions as well as OO software developers in the open source community or at commercial companies.
Der Großausfall in der Amazon-Wolke sei nur die Spitze des Eisbergs an Problemen, die Cloud-Computing mit sich bringt, sagte Internetpionier Dave Farber zu ORF.at. Am Montag gab erneut ein Cloud-Anbieter das Geschäftsfeld auf.
Katta is a scalable, failure tolerant, distributed, data storage for real time access.
Katta serves large, replicated, indices as shards to serve high loads and very large data sets. These indices can be of different type. Currently implementations are available for Lucene and Hadoop mapfiles.
* Makes serving large or high load indices easy
* Serves very large Lucene or Hadoop Mapfile indices as index shards on many servers
* Replicate shards on different servers for performance and fault-tolerance
* Supports pluggable network topologies
* Master fail-over
* Fast, lightweight, easy to integrate
* Plays well with Hadoop clusters
* Apache Version 2 License
Amazon Web Service today announced a new AWS Import/Export feature. A potentially huge step forward for data portabilty when using the Amazon Cloud computing infrastructure.
Following up on KMeans Clustering Now Running on Elastic MapReduce, Stephen Green has generously documented the steps that was necessary to get an example of k-Means clustering up and running on Amazon’s Elastic MapReduce (EMR) on the Apache Lucene Mahout wiki.
V. Patil, S. Jejurkar, and S. Gadekar. International Journal on Recent and Innovation Trends in Computing and Communication, 3 (1):
184--189(January 2015)