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An Intelligent Data Analysis for Recommendation Systems Using Machine Learning

https://doi.org/10.1155/2019/5941096

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What this work says

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

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Content-based Recommender Systems: State of the Art and Trends

inferredcites →https://doi.org/10.1007/s11042-016-3833-0openalex-snapshot

Building a mobile movie recommendation service by user rating and APP usage with linked data on Hadoop

inferredcites →https://doi.org/10.1007/s12652-015-0335-2openalex-snapshot

Fuzzy and nonlinear programming approach for optimizing the performance of ubiquitous hotel recommendation

inferredcites →https://doi.org/10.1007/s13042-014-0316-3openalex-snapshot

Improving news articles recommendations via user clustering

inferredcites →https://doi.org/10.1016/j.elerap.2012.05.002openalex-snapshot

Combining user preferences and user opinions for accurate recommendation

inferredcites →https://doi.org/10.1016/j.elerap.2015.08.004openalex-snapshot

A multi-criteria collaborative filtering recommender system for the tourism domain using Expectation Maximization (EM) and PCA–ANFIS

inferredcites →https://doi.org/10.1016/j.elerap.2016.03.002openalex-snapshot

Improving the multidimensional sequencing of hotel rooms on an online travel agency web site

inferredcites →https://doi.org/10.1016/j.eswa.2011.04.152openalex-snapshot

Sem-Fit: A semantic based expert system to provide recommendations in the tourism domain

inferredcites →https://doi.org/10.1016/j.jdmm.2013.11.003openalex-snapshot

Managing change in tourism destinations: Key issues and current trends

inferredcites →https://doi.org/10.1016/j.knosys.2013.05.006openalex-snapshot

Preference-based clustering reviews for augmenting e-commerce recommendation

inferredcites →https://doi.org/10.1016/j.physa.2013.11.013openalex-snapshot

Collaborative filtering recommendation algorithm based on user preference derived from item domain features

inferredcites →https://doi.org/10.1016/j.tele.2009.05.003openalex-snapshot

Personalizing recommendations for tourists

inferredcites →https://doi.org/10.1023/a:1021240730564openalex-snapshot

Hybrid Recommender Systems: Survey and Experiments

inferredcites →https://doi.org/10.1080/13032917.2012.687690openalex-snapshot

The effects of marketing communication on the tourist's hotel reservation process

inferredcites →https://doi.org/10.1080/19368623.2011.615017openalex-snapshot

Image of All Hotel Scales on Travel Blogs: Its Impact on Customer Loyalty

inferredcites →https://doi.org/10.1109/access.2017.2778424openalex-snapshot

An Efficient Similarity Measure for User-Based Collaborative Filtering Recommender Systems Inspired by the Physical Resonance Principle

inferredcites →https://doi.org/10.1109/mc.2009.263openalex-snapshot

Matrix Factorization Techniques for Recommender Systems

inferredcites →https://doi.org/10.1109/mic.2003.1167344openalex-snapshot

Amazon.com recommendations: item-to-item collaborative filtering

inferredcites →https://doi.org/10.1109/tpds.2013.2297117openalex-snapshot

KASR: A Keyword-Aware Service Recommendation Method on MapReduce for Big Data Applications

inferredcites →https://doi.org/10.1145/1921591.1921593openalex-snapshot

Comparison of collaborative filtering algorithms

inferredcites →https://doi.org/10.1155/2018/8263704openalex-snapshot

A Sentiment‐Enhanced Hybrid Recommender System for Movie Recommendation: A Big Data Analytics Framework

inferredcites →https://doi.org/10.1155/2019/4589060openalex-snapshot

A Neural Network-Inspired Approach for Improved and True Movie Recommendations

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Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowd-Sourced Content

inferredcites →https://doi.org/10.14569/ijacsa.2016.070837openalex-snapshot

An Item-based Multi-Criteria Collaborative Filtering Algorithm for Personalized Recommender Systems

inferredcites →https://doi.org/10.1561/1100000009openalex-snapshot

Collaborative Filtering Recommender Systems

inferredcites →https://doi.org/10.19101/ijacr.2017.729004openalex-snapshot

Movies recommendation system using collaborative filtering and k-means

inferredcites →https://doi.org/10.3217/jucs-021-13-1810openalex-snapshot

A Distributed Recommendation Platform for Big Data

inferredcites →https://doi.org/10.3390/mca23010001openalex-snapshot

A Fast Recommender System for Cold User Using Categorized Items

inferredcites →https://doi.org/10.3390/su10114280openalex-snapshot

Design and Application of a Multi-Variant Expert System Using Apache Hadoop Framework

inferredcites →https://doi.org/10.71330/thenucleus.2016.141openalex-snapshot

Improved Scalable Recommender System

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Deep Representation Learning of User Preferences for Opinionclassification

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Content-Based Product Recommendation Systems—Review

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Intelligible Techniques for Producing Eminent Recommendations in Social Networks

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To Analyze the Various Machine Learning Algorithms That Can Effectively Process Large Volumes of Data and Extract Relevant Information for Personalized Travel Recommendations

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inferred← citeshttps://doi.org/10.1016/j.engappai.2023.106553openalex-snapshot

An enhanced recommender system based on heterogeneous graph link prediction

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Deep click interest network for reranking hotels

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A dynamic decision support system for evaluating peer-to-peer rental accommodations in the sharing economy

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Machine learning approaches for hotel recommendation

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A novel product recommendation system using hybrid deep learning-based opinion mining with collaborative filtering

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Selective dissemination of information (SDI) in the age of artificial intelligence (AI)

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Enhancing Performance of Movie Recommendations Using LSTM With Meta Path Analysis

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Recognition of Opinion Leaders in Social Networks Using Text Posts’ Trajectory Scoring and Users’ Comments Sentiment Analysis

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HMSTNet: A Deep Learning Multimodal Approach for Personalized English Literature Recommendations

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Restaurant Recommendation System Based on ML Algorithms and Real-Time Web Scraping

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Optimization Of Social Media Comments To Improve Customer Journey Using Machine Learning

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Hotel Recommendation System Based on Customer’s Reviews Content Based Filtering Approach

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A Systematic Review of Artificial Intelligence and Big Data for the Analysis and Interpretation of Customer Reviews

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Extra-Tree Classification of Customer Review for Hotel Recommendation

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A K-means Optimized Self-Organizing Map Neural Network Video Recommendation Framework

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