Building Human Values into Recommender Systems: An Interdisciplinary Synthesis by Stray, Jonathan, Halevy, Alon, Assar, Parisa, Hadfield-Menell, Dylan, Boutilier, Craig, Ashar, Amar, Bakalar, Chloe, Beattie, Lex, Ekstrand, Michael, Leibowicz, Claire, Moon Sehat, Connie, Johansen, Sara, Kerlin, Lianne, Vickrey, David, Singh, Spandana, Vrijenhoek, Sanne, Zhang, Amy, Andrus, McKane, Helberger, Natali, Proutskova, Polina

“…Recommender systems are the algorithms which select, filter, and personalize content across many of the world?…”
Get full text

A Recommendation System for Ideation: Enhancing Supermind Ideator by Papacica, Daniel

“…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. …”
Get full text

Creating a web page recommendation system for Haystack by Derryberry, Jonathan C. (Jonathan Carlyle), 1979-

Get full text

Utilizing Review Summarization in a Spoken Recommendation System by Liu, Jingjing, Seneff, Stephanie, Zue, Victor

“…In this paper we present a framework for spoken recommendation systems. To provide reliable recommendations to users, we incorporate a review summarization technique which extracts informative opinion summaries from grass-roots users‘ reviews. …”
Get full text
Get full text
Get full text

Challenges in recommender systems : scalability, privacy, and structured recommendations by Xin, Yu, Ph. D. Massachusetts Institute of Technology

Get full text

A re-visit of the popularity baseline in recommender systems by Ji, Yitong, Sun, Aixin, Zhang, Jie, Li, Chenliang

Subjects: Get full text

Recommendation systems based on extreme multi-label classification by Chua, Song Ann

“…This project aims to implement a recommender system using extreme multi-label classification algorithms. …”
Get full text

User-specific recommender systems: from data to model by Lin, Zhuoyi

“…In the era of big data, recommender systems are widely adopted by online platforms (e.g., Amazon and YouTube), so as to provide target users with meaningful recommendation and alleviate the problem of information overload. …”
Get full text

An investigation of the application of graph neural networks in recommendation systems by Koh, Jaylene Jia Ying

“…Matrix Factorization, popularized by the Netflix Prize, has established itself as the prevailing method for recommendation systems based on latent factor models. While traditional latent factor models like matrix factorization focus on capturing latent factors using linear algebra techniques, Graph Neural Networks extend this concept by considering more intricate relations within graphs. …”
Get full text

Real estate application and recommendation system development (I) by Lim, Jensen Chang Sheng

“…Moreover, the designed recommendation system incorporates proven methodologies, along with enhancements to these approaches. …”
Get full text

Streamsight: a toolkit for offline evaluation of recommender systems by Ng, Tze Kean

Subjects: Get full text

Multi-method evaluation in scientific paper recommender systems by Sesagiri Raamkumar, Aravind, Foo, Schubert

Subjects: “…Scientific Paper Recommender Systems…”
Get full text
Get full text

Solving the apparent diversity-accuracy dilemma of recommender systems by Liu, J, Zhou, T, Kuscsik, Z, Medo, M, Wakeling, J, Zhang, Y

“…Recommender systems use data on past user preferences to predict possible future likes and interests. …”

Capturing knowledge of user preferences: ontologies in recommender systems. by Middleton, SE, Roure, D, Roure, D, Shadbolt, N, Shadbolt, N

“…A multi-class approach to paper classification is used, allowing the paper topic taxonomy to be utilised during profile construction. The Quickstep recommender system is presented and two empirical studies evaluate it in a real work setting, measuring the effectiveness of using a hierarchical topic ontology compared with an extendable flat list.…”

A context-aware recommendation system for mobile devices by Lee, J, Hwang, T, Park, J, Lee, Y, Motik, B, Horrocks, I

Solving the apparent diversity-accuracy dilemma of recommender systems by Liu, J

Measuring learner's performance in e-learning recommender systems by Ghauth, Khairil Imran, Abdullah, Nor Aniza

“…A recommender system is a piece of software that helps users to identify the most interesting and relevant learning items from a large number of items. …”
Get full text

Multi-objective deep reinforcement learning for recommendation systems by Keat, Ee Yeo, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…Most existing recommendation systems (RSs) are primarily concerned about the accuracy of rating prediction and only recommending popular items. …”

On Measuring the Contextual Relevance of Research Paper Recommendation Systems by Haruna, Khalid, Ismail, Maizatul Akmar

“…The contextual information present in scholarly papers plays a vital role in the implementation of research paper recommendation systems. However, the most critical concern is how to measure the contextual relevance of scholarly papers for better recommendations? …”
Get full text

Review-based collaborative recommender system using deep learning methods / by Aminu Da’u, 1980-, author 633229, Naomie Salim supervisor 612144, Fakulti Kejuruteraan. Sekolah Komputeran 619086

Get full text