Recommenadation aided Caching using Combinatorial Multi-armed Bandits

Autor:	J, Pavamana K, Singh, Chandramani Kishore
Rok vydání:	2024
Předmět:	Computer Science - Machine Learning Computer Science - Information Retrieval Computer Science - Networking and Internet Architecture
Druh dokumentu:	Working Paper
Popis:	We study content caching with recommendations in a wireless network where the users are connected through a base station equipped with a finite-capacity cache. We assume a fixed set of contents with unknown user preferences and content popularities. We can recommend a subset of the contents to the users which encourages the users to request these contents. Recommendation can thus be used to increase cache hits. We formulate the cache hit optimization problem as a combinatorial multi-armed bandit (CMAB). We propose a UCB-based algorithm to decide which contents to cache and recommend. We provide an upper bound on the regret of our algorithm. We numerically demonstrate the performance of our algorithm and compare it to state-of-the-art algorithms.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2405.00080 Zobrazit plný text záznamu View this record from Arxiv