IBM Data and AI Ideas Portal for Customers


Shape the future of IBM!

We invite you to shape the future of IBM, including product roadmaps, by submitting ideas that matter to you the most. Here's how it works:

Post your ideas

Post ideas and requests to enhance a product or service. Take a look at ideas others have posted and upvote them if they matter to you,

  1. Post an idea

  2. Upvote ideas that matter most to you

  3. Get feedback from the IBM team to refine your idea

Help IBM prioritize your ideas and requests

The IBM team may need your help to refine the ideas so they may ask for more information or feedback. The product management team will then decide if they can begin working on your idea. If they can start during the next development cycle, they will put the idea on the priority list. Each team at IBM works on a different schedule, where some ideas can be implemented right away, others may be placed on a different schedule.

Receive notification on the decision

Some ideas can be implemented at IBM, while others may not fit within the development plans for the product. In either case, the team will let you know as soon as possible. In some cases, we may be able to find alternatives for ideas which cannot be implemented in a reasonable time.

Additional Information

To view our roadmaps: http://ibm.biz/Data-and-AI-Roadmaps

Reminder: This is not the place to submit defects or support needs, please use normal support channel for these cases

IBM Employees:

The correct URL for entering your ideas is: https://hybridcloudunit-internal.ideas.aha.io


Status Delivered
Created by Guest
Created on May 8, 2018

Relevancy Training for End Users

Currently WDS only accepts one relevancy training rating per query, meaning if a user rates a particular answer and some time later, they rate it again, their earlier rating gets overwritten. This works for an operating model where only one person or group, e.g. an SME or data scientist manages the training of WDS, but it means that we can't allow users to do the training themselves as each person would be overwriting someone elses training.

To account for this, I suggest a mode in WDS that allows relevancy training to be weighted so that each additional rating can either incrementally increase or decrease the value of the rating applied.