Treffer: Python for Collective Intelligence and Collaborative Filtering.

This paper will define the two terms Collective Intelligence and Collaborative Filtering and discuss how these two ideas can be used to create personally relevant filters allowing end users more personalized access to information on their chosen topics of interest. In addition various mathematical models used to filter data and compare preferences and their corresponding pythonic implementations will be discussed. Finally a simple example using web API's and Collective Intelligence algorithms will be demonstrated to provide an idea of the type of things that can be achieved, relatively easily, using python for Collective Intelligence and Collaborative Filtering. This short abstract will be accompanied by a talk given at PyCon Asia 2010. [ABSTRACT FROM AUTHOR]

Copyright of Python Papers Monograph is the property of Python Papers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)