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 75 for “"recommender system"”.
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Smart Travel Recommender System
… of health problems. Current travel guidance systems such as Google Maps give recommendations to users mainly based on short travel time. Driven by the idea of improving air quality, mobility and quality of life for city residents, we contribute smart travel recommender system, which uses a …
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ACM Venue Recommender System
… to address this issue and have developed journal recommenders. In this thesis, our goal is to design and develop a similar recommendation system for the ACM dataset. We view this recommendation problem from a classification perspective. With the success of deep learning classifiers in recent times …
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Towards an Informative Recommender System
Recommender systems play a critical role in modern digital platforms, yet their effectiveness depends on how well they extract and utilize implicit information from available data. This dissertation explores informative learning—a paradigm that enhances recommendation quality by extracting, …
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A Layered Conversational Recommender System
In this thesis a new approach to building product recommender systems is introduced. By using a customer-centric dialogue, the customers' preferences are elicited. These are the basis for inferring utility estimations about the desired technical properties of the products in question. Systems built …
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Recommender System for Audio Recordings
… websites offer millions of products for sale. A Recommender system is defined as software used by such websites for recommending commercial or noncommercial product items to users according to the users’ tastes. In this project, we develop a recommender system for a private multimedia web service …
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TaskDo: A Daily Task Recommender System
… This problem has driven us to contribute a task recommender system which suggests a specific type of tasks to users based on their history of tasks and various factors at that specific time. This system not only suggests a specific type of task for the user but also collects feedback from the …
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A recommender system for e-retail
… the customer. In this dissertation, we develop a recommender system (RS), whose purpose is to provide suggestions for products that are most likely of interest to a particular customer. There are two primary contributions of this dissertation. First, we describe a set of six characteristics that …
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Cross-cultural recommender system use and design
… component of consumers’ everyday life. These recommender systems are employed on e-commerce sites across the world. However, despite their pervasive presence, the user interface design, and the way in which products are recommended, these systems are relatively similar across cultures. Across …
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soMLier: A South African Wine Recommender System
Though several commercial wine recommender systems exist, they are largely tailored to consumers outside of South Africa (SA). Consequently, these systems are of limited use to novice wine consumers in SA. To address this, the aim of this research is to develop a system for South African consumers …
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Sparsity-aware personalized recommender system via meta-learning
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-05-01
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An intelligent self-configuring recommender system as a service.
… ranging from music platforms to product recommenders and social media content suggestions, leading to a challenge in finding items that align with their individual preferences. To address this complexity, the development and implementation of Recommender Systems has become increasingly …
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Location Aware Multi-criteria Recommender System for Intelligent Data Mining
… order to achieve this objective, the design of Recommender Systems (RSs), which are systems designed to aid the users through different decision-making processes by providing recommendations to them, have been an active area of research. RSs may produce personalized and non-personalized …
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A review-aware multi-modal neural collaborative filtering recommender system
… become a ubiquitous aspect of modern life and recommender systems have become a crucial tool for e-commerce giants to efficiently sift through vast amounts of data to locate the infor mation that users are seeking. Within e-commerce, recommender systems aim to provide users with personalised …
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Egy turisztikai ajánlórendszer modellje = A Model of a Touristic Recommender System
Jelen dolgozat célja egy olyan turisztikai ajánlórendszer elméleti alapjainak lefektetése, mely képes elegendően pontos és személyre szabott útvonalak tervezésére egy idegen városban, figyelembe véve a felhasználó igényeit és lehetőségeit. A dolgozat a fentiekben vázolt kutatási célokat követve …
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Dimension reduction and efficient recommender system for large-scale complex data
… data with refreshment samples, and large-scale recommender systems. In the first part of this thesis, we incorporate correlation structure in sufficient dimension reduction for longitudinal data. Existing sufficient dimension reduction approaches assuming independence may lead to substantial …
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A Novel Combined Investment Recommender System Using Adaptive Neuro-Fuzzy Inference System
Investment recommendation systems (IRSs) are critical tools used by potential investors to make informed decisions about investment options. However, existing systems have limitations in terms of accuracy and efficiency, leading to a need for more effective and efficient recommendation systems. …
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Rich-context: an unsupervised context-driven recommender system based on user reviews
… amount of products or services to choose from. Recommender systems help to overcome this problem by suggesting which products or services to consume based on the users’ past behavior along with additional information about users, products and services. For the most part, however, they have done …
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Content based recommendation system & android application
Rising of the recommendation systems has come into markets which gives the suggestions to users. A recommendation system is a type of information filtering system that attempts to forecast a user need or we can say preference for an item. Although every application serves a unique function, not …
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Model Compression and AutoML for Efficient Click-Through Rate Prediction
… can adeptly learn to predict user response for recommender systems. However, these model architectures are often effective at the cost of large computational, and memory, cost. This limits their ability to run on edge devices with smaller hardwares, such as smartphones, which is a popular use …
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