Abstract
Presented herein is technology that provides for improving collaborative experiences through dynamic real-time detection and quantification of attention for specific topics mentioned during online collaborative meetings to profile user interests. This knowledge of a person’s interests allows for a personalized experience when collaborating or using various tools and applications. The technology presented herein not only understands user preferences, but also refines how users may engage with information. The technology may enable cognitive artificial intelligence (AI) companions that can be utilized across a variety of scenarios including providing customized meeting summaries, offering curated topic-based highlights, and ensuring that users are engaged in topics or discussions that are only of relevance to their personal interest.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Addepalli, Sree Gowri; Holl, Steve; Shao, Qihong; Picado, Alejandro Avila; Chavez, Jesus Garcia; and Suresh, Archana, "INTEREST-BASED PROFILING THROUGH ATTENTION MEASUREMENTS TO AUGMENT INTELLIGENCE IN COLLABORATION SOLUTIONS", Technical Disclosure Commons, (September 30, 2024)
https://www.tdcommons.org/dpubs_series/7387