On the public citation graph

Enhancing New Product Recommendation in E-Commerce Platforms through Semantic Intelligence: An Integrated Approach Using Large Language Models and Graph Learning

https://doi.org/10.2139/ssrn.7167442
0 signed · 16 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.dss.2015.03.008openalex-snapshot
Recommender system application developments: A survey
inferredcites →https://doi.org/10.1016/j.dss.2024.114339openalex-snapshot
Session context data integration to address the cold start problem in e-commerce recommender systems
inferredcites →https://doi.org/10.1109/access.2022.3218882openalex-snapshot
RTN-GNNR: Fusing Review Text Features and Node Features for Graph Neural Network Recommendation
inferredcites →https://doi.org/10.1109/tkde.2025.3540912openalex-snapshot
CoLLM: Integrating Collaborative Embeddings Into Large Language Models for Recommendation
inferredcites →https://doi.org/10.1145/3437963.3441738openalex-snapshot
Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation
inferredcites →https://doi.org/10.1145/3485447.3512104openalex-snapshot
Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning
inferredcites →https://doi.org/10.1145/3534678.3539381openalex-snapshot
Towards Universal Sequence Representation Learning for Recommender Systems
inferredcites →https://doi.org/10.1145/3535101openalex-snapshot
Graph Neural Networks in Recommender Systems: A Survey
inferredcites →https://doi.org/10.1145/3539597.3570472openalex-snapshot
DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation
inferredcites →https://doi.org/10.1145/3543507.3583286openalex-snapshot
Contrastive Collaborative Filtering for Cold-Start Item Recommendation
inferredcites →https://doi.org/10.1145/3589334.3645358openalex-snapshot
Harnessing Large Language Models for Text-Rich Sequential Recommendation
inferredcites →https://doi.org/10.1145/3589334.3645458openalex-snapshot
Representation Learning with Large Language Models for Recommendation
inferredcites →https://doi.org/10.1145/3589335.3648307openalex-snapshot
Enhancing Sequential Recommendation via LLM-based Semantic Embedding Learning
inferredcites →https://doi.org/10.1145/3627158openalex-snapshot
Contrastive Self-supervised Learning in Recommender Systems: A Survey
inferredcites →https://doi.org/10.1145/3640457.3688104openalex-snapshot
Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models
inferredcites →https://doi.org/10.1145/3694784openalex-snapshot
A Survey on Recommender Systems Using Graph Neural Network
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.