Coupa Software Inc.

Fang Chang

Maggie Mae Joy

Arjun Ramaratnam

Mikin Faldu

Kiran Ratnapu

Prasanna Kumar

Amit Vijayant

Jeffrey Hellman

Ethan Laub

Chris Mayor

Anshuman Nene

Rahul Mehta

Thomas Klein

Computer-implemented techniques for repeatable and interpretable divisive analysis. In one embodiment, for example, a method comprises: identifying top-level cohorts of data items based on one or more characteristics of the data items in common; recursively or iteratively dividing a selected top-level cohort in a top-down manner resulting in a plurality of sub-level cohorts arranged in a hierarchy; detecting a particular data item that is a statistical outlier among data items of a leaf cohort in the hierarchy; and causing display of an indication in a computer user interface that the particular data item is an outlier.

System and method for repeatable and interpretable divisive analysis

A method and apparatus for generating search data for items in an e-procurement system is provided. In various embodiments, a digital image is created or selected and data comprising search key data is generated based on the digital image. In various embodiments, the search key data is sent to a search repository listing items in an e-procurement system. In various embodiments, search data is sorted according to received search key data to present search results relating to items corresponding to the digital image.

Method and computer-readable media for real-time image-based catalog search

Techniques for using a graphical user interface to automatically generate expense lines from images are described herein. According to an embodiment, a server computer causes storing in a data repository, data identifying a plurality of users, the data comprising feature data extracted from one or more images of the users. The server computer receives a digital photographic image captured using a camera in a mobile computing device. The server computer identifies one or more faces in the digital photographic image and determines that the one or more faces in the digital photographic image match a particular user. The server computer generates and stores an expense line in an expense data table in the data repository, the expense line comprising an identification of the particular user.

Automatic generation of expense data using facial recognition in digitally captured photographic images

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Mountain View, CA, United States of America

Fang Chang