An Attention-Based Latent Information Extraction Network (ALIEN) for High-Order Feature Interactions

An Attention-Based Latent Information Extraction Network (ALIEN) for High-Order Feature Interactions

One of the primary tasks for commercial recommender systems is to predict the probabilities of users clicking items, e.g., advertisements, music and products. This is because such predictions have a decisive impact on profitability. The classic recommendation algorithm, collaborative filtering (CF),...

Full description

Bibliographic Details
Main Authors:	Ruo Huang, Shelby McIntyre, Meina Song, Haihong E, Zhonghong Ou
Format:	Article
Language:	English
Published:	MDPI AG 2020-08-01
Series:	Applied Sciences
Subjects:	recommender systems collaborative filtering click-through rate prediction high-order feature interactions attention mechanism explainable recommendation
Online Access:	https://www.mdpi.com/2076-3417/10/16/5468

Similar Items

Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation
by: Qingyao Ai, et al.
Published: (2018-09-01)

An Attention-Based Recommender System to Predict Contextual Intent Based on Choice Histories across and within Sessions
by: Ruo Huang, et al.
Published: (2018-11-01)

An Attention-Based User Preference Matching Network for Recommender System
by: Yuchen Liu, et al.
Published: (2020-01-01)

Integrating an Attention Mechanism and Convolution Collaborative Filtering for Document Context-Aware Rating Prediction
by: Bangzuo Zhang, et al.
Published: (2019-01-01)

sDeepFM: Multi-Scale Stacking Feature Interactions for Click-Through Rate Prediction
by: Baohua Qiang, et al.
Published: (2020-02-01)

Improving Collaborative Filtering-Based Image Recommendation through Use of Eye Gaze Tracking
by: Ernani Viriato Melo
Published: (2018-10-01)

A Dual-Attention Autoencoder Network for Efficient Recommendation System
by: Chao Duan, et al.
Published: (2021-06-01)

Visual and Textual Jointly Enhanced Interpretable Fashion Recommendation
by: Qianqian Wu, et al.
Published: (2020-01-01)

A Session-Based Customer Preference Learning Method by Using the Gated Recurrent Units With Attention Function
by: Jenhui Chen, et al.
Published: (2019-01-01)

DARES: An Asynchronous Distributed Recommender System Using Deep Reinforcement Learning
by: Bichen Shi, et al.
Published: (2021-01-01)

Improved Movie Recommendations Based on a Hybrid Feature Combination Method
by: Gharbi Alshammari, et al.
Published: (2019-08-01)

ACCF: Learning Attentional Conformity for Collaborative Filtering
by: Bin Liang, et al.
Published: (2019-01-01)

Automatic Evaluation of Recommendation Models
by: Olga Alieva, et al.
Published: (2020-09-01)

Multi-Level Fine-Grained Interactions for Collaborative Filtering
by: Xingjie Feng, et al.
Published: (2019-01-01)

Matrix Factorisation Based Recommendation for Web Mashups
by: Ou, Jacky
Published: (2020)

On Explainable Fuzzy Recommenders and their Performance Evaluation
by: Rutkowski Tomasz, et al.
Published: (2019-09-01)

MP4Rec: Explainable and Accurate Top-N Recommendations in Heterogeneous Information Networks
by: Makbule Gulcin Ozsoy, et al.
Published: (2020-01-01)

Group Recommendation via Self-Attention and Collaborative Metric Learning Model
by: Haiyan Wang, et al.
Published: (2019-01-01)

Movie recommendation system using machine learning
by: F. Furtado, et al.
Published: (2020-03-01)

Experimental Analysis of Friend-And-Native Based Location Awareness for Accurate Collaborative Filtering
by: Aaron Ling Chi Yi, et al.
Published: (2021-03-01)

Research on Algorithm Recommended by Online Education for Big Data
by: Feng Tao, et al.
Published: (2015-01-01)

A Literature Review on Recommender Systems Algorithms, Techniques and Evaluations
by: Kasra Madadipouya, et al.
Published: (2017-07-01)

HYPNER: A Hybrid Approach for Personalized News Recommendation
by: Asghar Darvishy, et al.
Published: (2020-01-01)

Recommended System: Attentive Neural Collaborative Filtering
by: Yanli Guo, et al.
Published: (2020-01-01)

The Use of Items Personality Profiles in Recommender Systems
by: Alharthi, Haifa
Published: (2015)

Attention Collaborative Autoencoder for Explicit Recommender Systems
by: Shuo Chen, et al.
Published: (2020-10-01)

CONTENT BASED DAN COLLABORATIVE FILTERING PADA REKOMENDASI TUJUAN PARIWISATA DI DAERAH YOGYAKARTA
by: Aprilia Saptu Ningrum, et al.
Published: (2019-04-01)

Friend and POI recommendation based on social trust cluster in location-based social networks
by: Jinghua Zhu, et al.
Published: (2019-04-01)

A Collaborative Filtering Probabilistic Approach for Recommendation to Large Homogeneous and Automatically Detected Groups
by: Jesús Bobadilla, et al.
Published: (2020-06-01)

Context-Aware Location Recommendation Using Geotagged Photos in Social Media
by: Haosheng Huang
Published: (2016-10-01)

A Cascade Framework for Privacy-Preserving Point-of-Interest Recommender System
by: Cui, L., et al.
Published: (2022)

Recommendation to Groups of Users Using the Singularities Concept
by: Fernando Ortega, et al.
Published: (2018-01-01)

Improving the Prediction Quality in Memory-Based Collaborative Filtering Using Categorical Features
by: Lei Chen, et al.
Published: (2021-01-01)

Improved Music Recommendation Algorithm for Deep Neural Network Based on Attention Mechanism
by: He, X.
Published: (2022)

A Systematic Review of Recommender Systems and Their Applications in Cybersecurity
by: Aleksandra Pawlicka, et al.
Published: (2021-08-01)

Research on collaborative filtering algorithm optimization
by: XIONG Boyuan, et al.
Published: (2018-10-01)

BSO-MV: An Optimized Multiview Clustering Approach for Items Recommendation in Social Networks
by: Lamia Berkani, et al.
Published: (2021-07-01)

Fusing Knowledge and Aspect Sentiment for Explainable Recommendation
by: Peng Bai, et al.
Published: (2020-01-01)

Classification and Comparison of the Hybrid Collaborative Filtering Systems
by: F. S. Gohari, et al.
Published: (2017-06-01)

Improving Recommendations by Embedding Multi-Entity Relationships With Latent Dual-Metric Learning
by: Yuanbo Xu, et al.
Published: (2019-01-01)

Cannot write session to /tmp/vufind_sessions/sess_shl598r6f20ct6v8ntimmlgj7c