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Recommender systems for niche and dynamic communities face persistent challenges from data sparsity, cold start users and items, and privacy constraints. Traditional collaborative filtering and content-based approaches underperform in these settings, either requiring invasive user data or failing when preference histories are absent. We present DeepNaniNet, a deep neural recommendation framework that addresses these challenges through an inductive graph-based architecture combining user-item interactions, item-item relations, and rich textual review embeddings derived from BERT. Our design enables cold start recommendations without profile mining, using a novel "content basket" user representation and an autoencoder-based generalization strategy for unseen users. We introduce AnimeULike, a new dataset of 10,000 anime titles and 13,000 users, to evaluate performance in realistic scenarios with high proportions of guest or low-activity users. DeepNaniNet achieves state-of-the-art cold start results on the CiteULike benchmark, matches DropoutNet in user recall without performance degradation for out-of-matrix users, and outperforms Weighted Matrix Factorization (WMF) and DropoutNet on AnimeULike warm start by up to 7x and 1.5x in Recall@100, respectively. Our findings demonstrate that DeepNaniNet delivers high-quality, privacy-preserving recommendations in data-sparse, cold start-heavy environments while effectively integrating heterogeneous content sources.

The global recorded music market grew by 5.9 percent last year. It was the fastest rate of growth since 1997 and was as a result of the shift from traditional CDs and portable devices to the ability to stream content anywhere, at any time. Yet despite an estimated 498 online music streaming services available in over 40 countries in 2007, many of these companies cease to exist today. This emphasizes the importance of building a clear growth strategy that can continuously appeal to a demographic that is yearning for instant and tailored music on demand. Today, brands across the globe are continually searching for fresh ways to connect and resonate with their audiences while striving to stand out from the competition in order to grow their business.

If your business wants to attract more qualified traffic and build your brand, then you need to think about the client's journey. Today's consumers are more informed and have more options than ever before when it comes to what they buy and how they buy it. When a customer buys your product or service, that transaction is only one part of their entire experience with your company. If you want to make the purchasing journey as easy as possible for your customers then, you need to think about every touch point that leads up to their purchase. There is so much data out there to consider if you want to optimize the customer journey of your audience.