Decision4Rec: A Jev-Inspired Framework of Decision Models on Knowledge and Active Graphs for Multi-Agent Recommender Systems

Key points

• Decision models, such as the commercial Jev, are language models that return one probability for each option of a question instead of generating text.1
• A knowledge graph writes the logs of each recommendation scenario as short statements on a defined scale, such as "sold: top 10%".1
• A decision model, trained once on real choices of three scenarios, reads them through one interface of typed questions, and a fusion step combines its answers with the score of the ranker.1
• Any model with this interface can be used, and we run the commercial Jev, the released open Kev and Kev models trained by us on recommendation requests.1

Sources (1)

• [1]Decision4Rec: A Jev-Inspired Framework of Decision Models on Knowledge and Active Graphs for Multi-Agent Recommender Systems
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 19, 08:56 AM

  We present Decision4Rec, an open and modular framework that makes decision models useful for recommendation.

  Decision models, such as the commercial Jev, are language models that return one probability for each option of a question instead of generating text.

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