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1. US20200167666 - PREDICTIVE MODEL BASED ON DIGITAL FOOTPRINTS OF WEB APPLICATIONS

Office United States of America
Application Number 16202400
Application Date 28.11.2018
Publication Number 20200167666
Publication Date 28.05.2020
Publication Kind A1
IPC
G06N 5/02
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
5Computer systems using knowledge-based models
02Knowledge representation
G06N 7/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
7Computer systems based on specific mathematical models
CPC
G06N 7/005
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
7Computer systems based on specific mathematical models
005Probabilistic networks
G06N 5/022
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
5Computer systems using knowledge-based models
02Knowledge representation
022Knowledge engineering; Knowledge acquisition
Applicants CITRIX SYSTEMS, INC.
Inventors JEROEN MATTIJS VAN ROTTERDAM
Title
(EN) PREDICTIVE MODEL BASED ON DIGITAL FOOTPRINTS OF WEB APPLICATIONS
Abstract
(EN)

A web server includes a web application being accessed by a plurality of users, and a processor that logs application inputs and outputs during a respective user session for each user, and creates a state diagram for each user during the respective user session based on the logged application inputs and outputs. Each state diagram represents states and transitions between the states. The processor translates each state diagram into vector space constructed by a sum of transition sequences defined by the transitions between the states, clusters similar transition sequences in each state diagram, and reduces each cluster of similar transition sequences in each state diagram into a single transition sequence. A reduced state diagram is generated for each state diagram based on the single transition sequences. The reduced state diagrams are analyzed to generate a predictive model representing a probability of state transitions between the different states.

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