Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 82 for “"Recommendation systems"”.
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Data-driven methods for personalized product recommendation systems
… of increasingly more sophisticated product recommendation systems. Thus, a competitive edge in this rapidly growing sector could be worth up to millions of dollars in revenue for an online seller. Motivated by this increasingly prevalent problem, we propose an innovative model that selects, …
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An integer programming clustering approach with application to recommendation systems
<p>Recommendation systems have become an important research area. Early recommendation systems were based on collaborative filtering, which uses the principle that if two people enjoy the same product they are likely to have common favorites. We present an alternative recommendation approach based …
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Consumer Responses to Preference Elicitation Processes in Destination Recommendation Systems
… experiment which involved using a destination recommendation system for Spring Break vacation destinations. The data was analyzed primarily using a structural equation modeling methodology. The results suggest that the content of the questions asked during the course of the preference …
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Graph Neural Networks for Health-Aware Food and Multi-Criteria Recommendation Systems
Recommender systems play a vital role in helping users discover items that align with their preferences and health needs. This thesis presents two frameworks: the Health-aware Food Recommendation System with Dual Attention in Heterogeneous Graphs (HFRS-DA) and the Multiview Graph Dual Attention and …
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AI Bias in Streaming Platform Recommendation Systems: Exploring the Impact on Corporate Reputation
Artificial intelligence (AI) systems, particularly recommendation algorithms, have transformed user engagement on digital platforms like Netflix and YouTube by delivering personalized experiences. However, biases in data, algorithms, and deployment environments raise significant social and …
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Nitrogen recommendation systems, weather effects on nitrogen response, and the prediction of nitrogen response in Illinois
… food production and farm revenue. Several recommendation methodologies have been proposed to provide fixed N recommendations to maximize profits. The maximum return to nitrogen (MRTN) system, currently in use in Illinois and other Corn Belt states, fits an appropriate function (linear, …
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Using K-means Clustering and Similarity Measure to Deal with Missing Rating in Collaborative Filtering Recommendation Systems
The Collaborative Filtering recommendation systems have been developed to address the information overload problem and personalize the content to the users for business and organizations. However, the Collaborative Filtering approach has its limitation of data sparsity and online scalability …
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ESSAYS ON CUSTOMER ANALYTICS IN MOBLIE ECOSYSTEMS
… behaviors and technology use in mobile ecosystems. The first essay of this dissertation examines the difference in the effects of recommendation systems across the PC and mobile channels on customer-level decision outcomes and market. I conduct two randomized field experiments and find that …
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A Hybrid Recommendation System Based on Association Rules
<p>Recommendation systems are widely used in e-commerce applications. The<br />engine of a current recommendation system recommends items to a particular user based on user preferences and previous high ratings. Various recommendation schemes such as collaborative filtering and content-based …
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A Recommendation System for Ideation: Enhancing Supermind Ideator
Recommendation systems are widely utilized across various domains such as e-commerce, entertainment, and social media to enhance user experience by personalizing content and suggestions. Despite their widespread use, these systems are rarely applied to the ideation process, presenting unique …
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ONLINE LEARNING WITH BANDITS FOR COVERAGE
… volume, streaming data compels decision support systems to predict a small number of unique data points in due time that can represent a massive amount of correlated data without much loss of precision. In this work, we formulate this problem as the {\it online set coverage problem} and propose …
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A dynamic multi-algorithm collaborative-filtering system
… of interest. This problem can be solved by recommendation systems. For example, recommendation systems can be used to create recommendations which fit to the preferences of users. Recommendation systems can use two different approaches for the creation of recommendations. They can take …
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Market research of commercial recommendation engines for online and offline retail
In the era of big data and predictive analytics, recommendation systems or recommendation engines that recommend merchandise or service offerings based on individual preferences have had a revolutionary impact on retail businesses by making "personalization" a reality. As recommendable engines …
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Exploring the application of Word2Vec to basket transaction data in the grocery retail industry
… which include Association Rules Mining (ARM) and Recommendation Systems. The results from the experiments showed that indeed product embeddings created by Word2vec on transaction data are meaningful and useful. It was clear that the idea of using transactions in the place of sentences to the …
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Theoretical study of two prediction-centric problems : graphical model learning and recommendations
… online algorithms for a latent variable model of recommendation systems: We consider an online model for recommendation systems, with each user being recommended an item at each time-step and providing 'like' or 'dislike' feedback. The user preferences are specified via a latent variable model: …
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Predictive analysis of real-time strategy games using graph mining
… intelligence have facilitated the development of recommendation systems for a broad range of domains. Such recommendations are based on contextual information that is explicitly provided or pervasively collected. Recommendation systems often improve decision-making or increase the efficacy of a …
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