Behavioral Intelligence Platforms: From Event Streams to Autonomous Insight via Probabilistic Journey Graphs, Behavioral Knowledge Extraction, and Grounded Language Generation
The paper introduces the Behavioral Intelligence Platform (BIP), a system architecture designed to autonomously generate insights from raw event streams without requiring users to pose explicit queries. BIP uses probabilistic journey graphs, behavioral knowledge extraction, and grounded language generation to detect and explain behavioral patterns. It aims to shift behavioral analytics from a user-driven, query-based model to an automated, insight-driven approach. The system includes mechanisms for prioritizing insights based on an interestingness score and ensuring narrative outputs are factually grounded.
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Computer Science > Information Retrieval arXiv:2604.22762 (cs) [Submitted on 12 Mar 2026 (v1), last revised 28 Apr 2026 (this version, v2)] Title:Behavioral Intelligence Platforms: From Event Streams to Autonomous Insight via Probabilistic Journey Graphs, Behavioral Knowledge Extraction, and Grounded Language Generation Authors:Arun Patra, Bhushan Vadgave View a PDF of the paper titled Behavioral Intelligence Platforms: From Event Streams to Autonomous Insight via Probabilistic Journey Graphs, Behavioral Knowledge Extraction, and Grounded Language Generation, by Arun Patra and 1 other authors View PDF HTML (experimental) Abstract:Contemporary product analytics systems require users to pose explicit queries, such as writing SQL, configuring dashboards, or constructing funnels, before…
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