Method and Apparatus for Selecting Clusterings to Classify a Data Set
Gary King, Justin Grimmer. 2016.
"Method and Apparatus for Selecting Clusterings to Classify a Data Set".
United States of America 9,519,705 B2.

Abstract
In a computer assisted clustering method, a clustering space is generated from fixed basis partitiions that embed the entire space of all possible clusterings. A lower dimensional clustering space is created from the space of all possible clusterings by isometrically embedding the space of all possible clusterings in a lower dimensional Euclidean space. This lower dimensional space is then sampled based on the number of documents in the corpus. Partitions are then developed based on the samples that tessellate the space. Finally, using clusterings representative of these tessellations, a two-dimensional representation for users to explore is created.
See Also
- [Patent] Method and Apparatus for Selecting Clusterings to Classify A Predetermined Data Set (2013)
- [Presentation] Big Data Is Not About the Data! (2018)
- [Presentation] Big Data Reveals Made Up Data: How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument (2017)
- [Presentation] Big Data Is Not About the Data! The Power of Modern Analytics (2016)
- [Book] Preface: Big Data Is Not About the Data! (2016)
- [Presentation] Big Data Is Not About the Data, With Applications (2015)
- [Presentation] Big Data Is Not About The Data! (2013)
- [Paper] Preserving Quantitative Research-Elicited Data for Longitudinal Analysis. New Developments in Archiving Survey Data in the U.S. (2009)