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Isabelle Thore

Alain Gauthier

Mohannad El-Jayousi

Roy Ghorayeb

Rolan Abdukalykov

Vincent LaVoie

Xuebo Liang

Martin Parent

Marc Dorais

Joel Bao-Lan Tran

Nirmal Pothuraj

Mihai David

Ali Mahram Hassan Zada

Mackenzie Trenholm

Fuman Jin

Bianca Matei

In an example embodiment, a mechanism is provided that helps distinguish between email link clicks that are initiated by a human and those that are initiated by a bot. The mechanism provides three different processes for such detection, as well as processes for how to deal with clicks that are initiated by a bot, although it is not necessary to employ all three. These different processes include detection of high volumes of clicks from a particular address range in a short period of time, a hidden honey pot, and detection of duplicate clicks from different addresses. In additional example embodiments, a stall time is added to any evaluation of click metric to allow time for the aforementioned processes to detect and handle bot clicks. This stall time effectively keeps any clicks from 'counting' until the bot detection mechanism(s) can perform their tasks.

Email bot click detection

Scale(s) on one or more axes may be displayed. The scale(s) may present a range of values associated with at least one business object attribute. Visual representation(s) of business object(s) may be displayed. The visual representation(s) may be positioned relative to the scale(s). Detail boxes corresponding to each visually represented business object may be displayed. Each detail box may present information about a corresponding business object. All detail boxes may be displayed. Information presented by the detail box(es) may be an image and/or text. The information presented by the detail box(es) may be interactive. Displaying or not displaying the detail box(es) may be toggled. The visual representation(s) of the business object(s) may be repositioned based on the toggling.

Business object detail display

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Westmount, Canada

Isabelle Thore