LOD-a-lot democratizes access to the Linked Open Data (LOD) Cloud by serving more than 28 billion unique triples from 650K datasets from a single self-indexed file. This corpus can be queried online with a sustainable Linked Data Fragments interface, or it can be downloaded and consumed locally: LOD-a-lot is easy to deploy and only requires limited resources (524 GB of disk space and 15.7 GB of RAM), enabling web-scale repeatable experimentation and research from a high-end laptop.
D. Lawrie, and W. Croft. Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2003, page 457--458. (2003)
A. Schenker, H. Bunke, M. Last, and A. Kandel. Document Analysis Systems, volume 3163 of Lecture Notes in Computer Science, page 401-412. Springer, (2004)
R. Cooley, B. Mobasher, and J. Srivastava. Proceedings of the Ninth IEEE International Conference on Tools with Artificial Intelligence (ICTAI'97), IEEE Computer Society, (November 1997)
X. Wu, L. Zhang, and Y. Yu. WWW '06: Proceedings of the 15th international conference on World Wide Web, page 417--426. New York, NY, USA, ACM Press, (2006)