Recommender Systems
portes grátis
Recommender Systems
Algorithms and Applications
Nandan Mohanty, Sachi; Pavan Kumar, P.; Vairachilai, S.; Potluri, Sirisha
Taylor & Francis Ltd
10/2024
230
Mole
9780367631871
Pré-lançamento - envio 15 a 20 dias após a sua edição
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Preface. Acknowledgements. Editors. List of Contributors. Chapter 1 Collaborative Filtering-based Robust Recommender System using Machine Learning Algorithms. Chapter 2 An Experimental Analysis of Community Detection Algorithms on a Temporally Evolving Dataset. Chapter 3 Why This Recommendation: Explainable Product Recommendations with Ontological Knowledge Reasoning. Chapter 4 Model-based Filtering Systems using a Latent-factor Technique. Chapter 5 Recommender Systems for the Social Networking Context for Collaborative Filtering and Content-Based Approaches. Chapter 6 Recommendation System for Risk Assessment in Requirements Engineering of Software with Tropos Goal-Risk Model. Chapter 7 A Comprehensive Overview to the Recommender System: Approaches, Algorithms and Challenges. Chapter 8 Collaborative Filtering Techniques: Algorithms and Advances. Index.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
collaborative filtering techniques;commercial applications;Social networking;community detection algorithms;content-based approaches;Filtering algorithms;latent factor technique;E-business;Machine Learning algorithms;model-based filtering systems;ontological knowledge reasoning;product recommendations;recommender systems;risk assessment;Tropos Goal-Risk Model;Collaborative Filtering;Latent Factor Models;Stochastic Gradient Descent;Neighbourhood Model;Collaborative Filtering Technique;Cold Start Problem;SWRL Rule;Rating Matrix;Matrix Factorization;Cd Algorithm;Edge Betweenness;RF;Matrix Factorization Models;CF System;Collaborating Filtering Methods;PRA;Huffman Code;Non-negative Matrix Factorization;Adjacency Matrix;Item Bias;Cd;LDA;Cc;Baseline Predictors
Preface. Acknowledgements. Editors. List of Contributors. Chapter 1 Collaborative Filtering-based Robust Recommender System using Machine Learning Algorithms. Chapter 2 An Experimental Analysis of Community Detection Algorithms on a Temporally Evolving Dataset. Chapter 3 Why This Recommendation: Explainable Product Recommendations with Ontological Knowledge Reasoning. Chapter 4 Model-based Filtering Systems using a Latent-factor Technique. Chapter 5 Recommender Systems for the Social Networking Context for Collaborative Filtering and Content-Based Approaches. Chapter 6 Recommendation System for Risk Assessment in Requirements Engineering of Software with Tropos Goal-Risk Model. Chapter 7 A Comprehensive Overview to the Recommender System: Approaches, Algorithms and Challenges. Chapter 8 Collaborative Filtering Techniques: Algorithms and Advances. Index.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
collaborative filtering techniques;commercial applications;Social networking;community detection algorithms;content-based approaches;Filtering algorithms;latent factor technique;E-business;Machine Learning algorithms;model-based filtering systems;ontological knowledge reasoning;product recommendations;recommender systems;risk assessment;Tropos Goal-Risk Model;Collaborative Filtering;Latent Factor Models;Stochastic Gradient Descent;Neighbourhood Model;Collaborative Filtering Technique;Cold Start Problem;SWRL Rule;Rating Matrix;Matrix Factorization;Cd Algorithm;Edge Betweenness;RF;Matrix Factorization Models;CF System;Collaborating Filtering Methods;PRA;Huffman Code;Non-negative Matrix Factorization;Adjacency Matrix;Item Bias;Cd;LDA;Cc;Baseline Predictors
