Odaia Intelligence Inc.

Rogers Communications Inc.

Periklis Andritsos

Darius Braziunas

Michael Cvet

Francisco Estrada

The present disclosure generally relates to the field of data structures and in particular, a loop-aware footprint matrix data structure adapted for data process traversal. The proposed approach is directed to a computer-based analytic system and corresponding method that uses a specific data structure and processing thereof, in some embodiments, adapted to computationally estimate predictions of next events by first generating a data structure based on business process models obtained using process mining techniques, and then using the improved data structure for generating predictions, which can then be encapsulated in the form of computer instructions or machine instruction sets, having a specific sequence for execution.

Accurate and transparent path prediction using process mining

A platform for processing event traces to generate clusters of journey maps for an interactive user display. The clustering can be implemented using a genetic process. The clustering can be implemented using a distance measures. Other clustering techniques can be used. The platform can use the clustering results to generate interactive dynamic visualizations with interactive selectable portions. The platform can integrate processing mining and journey maps to generate interactive dynamic visualizations.

Data visualization platform for event-based behavior clustering

A document clustering system and method of assigning a document to a cluster of documents containing related content are provided. Each cluster is associated with a cluster summary describing the content of the documents in the cluster. The method comprises: determining, at a document clustering system, whether the document should be grouped with one or more previously created cluster summaries, the previously created cluster summaries being stored in a memory in a B-tree data structure; and if it is determined that the document should not be grouped with the one or more previously created cluster summaries, then creating, at a document clustering system, a cluster summary based on the content of the document and storing the created cluster summary in the B-tree data structure.

Growing community of inventors

Toronto, Canada

Periklis Andritsos