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 15 of 15 for “"Recommendation algorithms"”.
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EFFICIENT LEARNING-BASED RECOMMENDATION ALGORITHMS FOR TOP-N TASKS AND TOP-N WORKERS IN LARGE-SCALE CROWDSOURCING SYSTEMS
A pressing need for efficient personalized recommendations has emerged in crowdsourcing systems. On the one hand, workers confront a flood of tasks, and they often spend too much time to find tasks matching their skills and interests. Thus, workers want effective recommendation of the most suitable …
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Testing two existing fertilizer recommendation algorithms: Stanford's 1.2 rule for corn and site-specific nutrient management for irrigated rice
U of I Only Restriction Lifted for Item 49800 on 2016-09-22T20:59:24Z.
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Group recommendation with automatic detection and classification of groups
This PhD thesis presents ART (Automatic Recommendation Technologies), a set of group recommendation algorithms that detect groups of users with similar preferences. With respect to classic group recommendation, the first step that such systems have to compute is the detection of groups of people …
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Hybrid recommender systems for personalized government-to-business e-services
… are the most popular and widely adopted recommendation approaches. Regardless of the success of CF-based approaches in various recommendation applications, they still suffer from data uncertainty, data sparsity, cold-start item and cold-start user problems, resulting in poor …
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Dynamic Matching of Users and Creators on Social Media Platforms
… and users. Existing literature on content recommendation algorithms used by platforms often focuses on user preferences and decisions, and does not jointly address creator incentives. We propose a model of content recommendation that explicitly focuses on dynamic user-content matching, with …
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AI Bias in Streaming Platform Recommendation Systems: Exploring the Impact on Corporate Reputation
… 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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Privacy risk and de-anonymization in heterogeneous information networks
… users’ profile, social interaction, and recommendation log data in KDD Cup 2012 to call for recommendation algorithms. Since the entities (users and so on) and edges (links among entities) are of multiple types, the released social network is a heterogeneous information network. Prior …
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Quantifying aesthetics of visual design applied to automatic design
… in order to create personalized designs via recommendation algorithms based on the user's preferences.</p>
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System design and architecture of an online, adaptive, and personalized learning platform
… content maps, learning nuggets, and nugget recommendation algorithms. A learner scenario helps readers visualize the functionality of the platform. To describe the platform's software architecture, the author provides conceptual data models, process flow models, and service group …
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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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Sequential decision making in artificial musical intelligence
… on two aspects of musical intelligence: music recommendation and human-agent (and more generally agent-agent) interaction in the context of music. The key contributions of this thesis are the design of better music playlist recommendation algorithms; the design of algorithms for tracking user …
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Feasibility optimality of periodwise static priority policies for a quality of service model in wireless networks and convergence analysis for an online recommendation system
… advice. At the present time, several web-based recommendation systems use votes from experts or other users to recommend objects to other customers. We apply the `learning from expert advice' framework for this system, and propose a recommendation algorithm that uses a weighted update rule. …
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A Novel Adaptation Model for E-Learning Recommender Systems Based on Student’s Learning Style
… from drawbacks in terms of making the right recommendations for learning resources. This can be attributed to the differences among learners’ preferences such as varying learning styles, knowledge levels and sequential learning patterns. Hence, to identify the needs of an individual student, …
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Towards Maintainable and Explainable AI Systems with Dataflow
… in speech generation, drug discovery, recommendation algorithms, and more, all achieved with the help of machine learning. It is vital to realise that any practical application of machine learning is not limited to just creating an accurate model based on a sanitised dataset. Such …
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Installectualism: Public Intellectuals in a Digital World
… how, through a complex algorithmic system of recommendations and reinforcement learning, machines have galvanised the phenomenon, established ego-centred network chambers, and created clusters of polarised communities.