Affinio Inc.

Stephen James Frederic Hankinson

Timothy Andrew Burke

A method and a system for securely applying proprietary software functions of software sources to proprietary data of a population of users are disclosed. The proprietary data of a user is not exposed to software sources, and the proprietary software of a software source is not accessible to users. A collaboration software module, placed in at least one cloud, is configured to establish, and continually update, a data structure holding task permissions from grantors to grantees, a grantor being a software source or a user, and a grantee is also a software source or a user. The collaboration software module of a cloud applies software function of a software source, communicatively coupled to the cloud, to proprietary data of an originating user, communicatively coupled to the same cloud, to produce a requisite result which is only accessible to the originating user or any grantees of the originating user (the grantor).

Method and system for secure distributed software-service

A method of complementary clustering of a vast population of objects is disclosed. The method aims at maximizing a global measure of object affinity within naturally-formed clusters. A first clustering procedure produces primary centroids of clusters of objects and a second clustering procedure produces secondary clusters of the primary centroids and corresponding secondary centroids. Refined clusters of the population of objects are formed based on object proximity to the secondary centroids. The first clustering procedure is preferably based on a variation of the K-means method, and the second clustering procedure is preferably based on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN). An apparatus implementing the method is devised to facilitate conflict-free parallel processing.

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Hammonds Plains, Canada

Stephen James Frederic Hankinson