IRMay 8, 2014

SocRecM: A Scalable Social Recommender Engine for Online Marketplaces

arXiv:1405.1842v18 citations
Originality Synthesis-oriented
AI Analysis

This addresses recommendation challenges for online marketplace users, but it appears incremental as it builds on existing social recommendation concepts.

The paper tackles the problem of social recommendation in online marketplaces by developing SocRecM, a scalable framework that integrates social features and recommendation approaches, though it is described as work-in-progress with no concrete results or numbers provided.

In this paper, we present work-in-progress on SocRecM, a novel social recommendation framework for online marketplaces. We demonstrate that SocRecM is not only easy to integrate with existing Web technologies through a RESTful, scalable and easy-to-extend service-based architecture but also reveal the extent to which various social features and recommendation approaches are useful in an online social marketplace environment.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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