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Towards Metadata-Aware Algorithms for Recommender Systems

problem has always been of great interest for both academic and industry. Metadata such as content information about the items (attributes) have;

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Recommender Systems

robust product recommender systems using machine learning algorithms are helpful in filtering and exploring unseen data by users for better;

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Applied Recommender Systems with Python

learning for building recommender systems Who This Book Is ForData scientists, machine learning engineers, and Python;

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Applied Recommender Systems with Python

recommender systems that incorporate both content-based and collaborative filtering Leverage machine learning, NLP, and deep learning for building;

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Collaborative Recommendations: Algorithms, Practical Challenges And Applications

Recommender systems are very popular nowadays, as both an academic research field and services provided by numerous companies for e;

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Social Network-Based Recommender Systems

analysis and detailed summary. Social Network-Based Recommender Systems is designed as a reference for professionals and researchers working;

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Recommender Systems

This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to;

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Recommender Systems

This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to;

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Hands-On Recommendation Systems with Python

recommenders as quickly as possible.. In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You'll;

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Large scale Graph Analysis System Algorithm and Optimization

This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and;

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Large scale Graph Analysis System Algorithm and Optimization

This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and;

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Self-Aware Computing Systems

This book provides formal and informal definitions and taxonomies for self-aware computing systems, and explains how self-aware computing;

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Practical Recommender Systems

Description Recommender systems are practically a necessity for keeping a site's content current, useful, and interesting to visitors;

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Thermal-Aware Testing of Digital VLSI Circuits and Systems

circuit level and at system level Describes range of algorithms for addressing thermal-aware test issue, presents comparison of temperature;

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Thermal-Aware Testing of Digital VLSI Circuits and Systems

circuit level and at system level Describes range of algorithms for addressing thermal-aware test issue, presents comparison of temperature;

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Recommender Systems for Learning

introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other;

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Semantics in Adaptive and Personalised Systems

This monograph gives a complete overview of the techniques and the methods for semantics-aware content representation and shows how to;

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Machine Learning with PySpark

Build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business;

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Video Surveillance For Sensor Platforms

simulation results and a parallel and pipelined efficient architecture for implementing the algorithms is described.;

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Recommender System for Online Social Network

applies recommendation systems to the online social network systems, is presented in this book. Recommender systems for social networks differ;

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Statistical Methods for Recommender Systems

crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical;

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Active Learning for Recommender Systems

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Context Aware Pervasive Systems and Applications

machine-to-machine communication, wherein there is less human intervention. In turn, this creates a need for context-aware pervasive systems and;

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Machine Learning Paradigms

for the development of personalized software as the core mechanism behind the implementation of Recommender Systems. The book will be;

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Building a Recommendation System with R

build and optimize recommendation engines Who This Book Is For If you are a competent developer with some knowledge of machine learning;

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Metadata and Semantics Research

are organized in several sessions and tracks: Digital Libraries, Information Retrieval, Linked and Social Data, Metadata and Semantics for;

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Disinformation in Open Online Media

behaviour and mitigation, harm-aware news recommender systems.;

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