MACHINE LEARNING ANALYSIS OF USER INTERFACE DESIGN

Techniques and solutions are described for improving user interfaces, such as by analyzing user interactions with a user interface with a machine learning component. The machine learning component can be trained with user interaction data that includes an interaction identifier and a timestamp. The...

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Bibliographic Details
Main Authors Devaraj, Natarajan, Baburaj, Sangeetha, V, Rajesh, Gouda S, Basavana, Bandaru, Sai, P K, Sumaiya, M K, Rohith, Bhattacharyya, Jumi
Format Patent
LanguageEnglish
Published 16.01.2020
Subjects
CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
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Summary:Techniques and solutions are described for improving user interfaces, such as by analyzing user interactions with a user interface with a machine learning component. The machine learning component can be trained with user interaction data that includes an interaction identifier and a timestamp. The identifiers and timestamps can be used to determine the duration of an interaction with a user interface element, as well as patterns of interactions. Training data can be used to establish baseline or threshold values or ranges for particular user interface elements or types of user interface elements. Test data can be obtained that includes identifiers and timestamps. The time taken to complete an interaction with a user interface element, and optionally an interaction pattern, can be analyzed. If the machine learning component determines that an interaction time or pattern is abnormal, various actions can be taken, such as providing a report or user interface guidance.
Bibliography:Application Number: US201816032325