Documents

Project overview

• How Seeks let you do your Web search at home, E. Benazera, FOSDEM 2011, Feb. 2011.

 Overview of the machine learning and similarity analysis tools that empower a Seeks user locally, harnessing the power of his machine.

• • Video: http://www.youtube.com/user/fosdemtalks?blend=2&ob=5#p/u/0/CVhTvnHsE2I
• "Seeks Project": Let's take back websearch, E. Benazera, FOSDEM 2011, Feb. 2011.

 Overview of the Seeks Project with roadmap.

• 'Seeks' for freedom beyond conventional websearch, E. Benazera, RMLL, July 2010.
  • Same presentation, with some tiny updates, 'Seeks' for freedom beyond conventional websearch, E. Benazera, tmplab, October 2010.

 Slides from a public presentation at RMLL in 2010. 
 An overview of how Seeks differs from conventional search engines and why collaborative
 websearch and the principles it builds upon are an inevitable trend on data flooded networks.

• An open-source architecture for taking back websearch, E. Benazera, RMLL, July 2009.

 Slides from a public presentation at RMLL in 2009. 
 Gives an overview of the motivations for the project, and of the technical architecture 
 for slowly taking back websearch.

• Sharing queries, grouping users, and its relation to a decentralized Web index, E. Benazera, S. Drouin, 2007.

 Another very short overview of the project, its motivations and envisioned
 development steps.

• Seeks' manifesto, E. Benazera, S. Drouin, 2006

 The foundations and rationale behind the Seeks project and why it is of interest to the 
 OSS community.

Technical documents

• Seeks technical sheet, E. Benazera, S. Drouin, 2008.
  • Same in French Seeks fiche technique.

 A short architectural overview of Seeks.

• Seeks project: Architecture for collaborative social websearch, E. Benazera, S. Drouin, 2006.

• Towards collaborative searching over an overlay network, E. Benazera, 2006.

 A technical description of the structures and maths behind the computation of
 a similarity measure in the space of text queries, and the associated distributed
 collaborative filter. Slightly outdated as the LSH computation has evolved.