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Next-Cart Recommendation by Utilizing Personalized Item Frequency Information in Online Web Portals
In modern times, next-cart recommendation (NCR) has appeared as an excitable subject of research among researchers and is dominant in e-commerce. In...
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Next-item recommendation within a short session using the combined features of horizontal and vertical convolutional neural network
Session-based recommendation systems are designed to offer recommendations to users based on their current browsing session rather than relying on...
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Explicit Behavior Interaction with Heterogeneous Graph for Multi-behavior Recommendation
Multi-behavior recommendation systems exploit multi-type user–item interactions (e.g., clicking, adding to cart and collecting) as auxiliary...
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Click is not equal to purchase: multi-task reinforcement learning for multi-behavior recommendation
Reinforcement learning (RL) has achieved ideal performance in recommendation systems (RSs) by taking care of both immediate and future rewards from...
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LSTM-UBI: a user behavior inertia based recommendation method
Practice shows that human behavior has certain patterns, also called as behavioral inertia. It often plays a crucial role in user’s decision-making....
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Hybrid session-aware recommendation with feature-based models
Session-based recommender systems model the interests of users based on their browsing behavior with the goal of making suitable item suggestions in...
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Dual-view co-contrastive learning for multi-behavior recommendation
Multi-behavior recommender systems (MBR) typically utilize multi-typed user interactive behaviors (e.g., purchase, click, view and add-to-cart) in...
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Multi-behavior-based graph contrastive learning recommendation
Graph-based collaborative filtering recommendations can more effectively explore the interaction information between users and items. However, its...
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A Survey and Taxonomy of Sequential Recommender Systems for E-commerce Product Recommendation
E-commerce recommendation systems facilitate customers’ purchase decision by recommending products or services of interest (e.g., Amazon). Designing...
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ANN Based ANFIS controller Design Using Hybrid Meta-Heuristic Tuning Approach for Cart Inverted Pendulum System
The control system of the Inverted Pendulum System (IPS) has turned to be a common engineering issue for investigators because of its importance in...
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A Smart Shop** Cart: Ezi-KART
We often refrain from going to a supermarket, just because we dread the long queues at the billing counters. This system makes shop** easier, where...
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V-GMR: a variational autoencoder-based heterogeneous graph multi-behavior recommendation model
Compared to traditional single-behavior models, multibehavior recommendation models incorporate the auxiliary behavior information of users. This...
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NAH: neighbor-aware attention-based heterogeneous relation network model in E-commerce recommendation
Traditional recommender systems only utilize a single user-item interaction behavior as the optimization target behavior. However, multi-behavior...
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Bi-directional Contrastive Distillation for Multi-behavior Recommendation
Multi-behavior recommendation leverages auxiliary behaviors (e.g., view, add-to-cart) to improve the prediction for target behaviors (e.g., buy)....
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FSBPR: a novel approach to improving BPR for recommendation with the fusion of similarity
As an essential part of big data, the recommendation system is widely used because of its practicability. Most of the traditional rating prediction...
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Learning User Embeddings Based on Long Short-Term User Group Modeling for Next-Item Recommendation
Session-based recommender systems are increasingly applied to next-item recommendations. However, existing approaches encode session information of...
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HMAR: Hierarchical Masked Attention for Multi-behaviour Recommendation
In the context of recommendation systems, addressing multi-behavioral user interactions has become vital for understanding the evolving user...
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A GCN-Based Sequential Recommendation Model for Heterogeneous Information Networks
Sequential recommendation is an important task in the research of recommendation methods for heterogeneous information networks, which is a technique...
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Session-based recommendation by exploiting substitutable and complementary relationships from multi-behavior data
Session-based recommendation (SR) aims to dynamically recommend items to a user based on a sequence of the most recent user-item interactions. Most...
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Hi-GNN: hierarchical interactive graph neural networks for auxiliary information-enhanced recommendation
Networked auxiliary information (e.g., user social network, item transition network, etc.) plays a significant role to alleviate the sparse...
