Results 91 to 100 of about 46,255 (310)

A collaborative filtering recommendation algorithm based on biclustering

open access: yes, 2015
Collaborative filtering has been widely used in many fields such as movie recommendation and e-commerce. However, there are still some problems such as data sparsity which restrict its further development. To address the data sparsity problem we proposed
Wang JS(汪家升)   +5 more
core   +1 more source

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

open access: yesAdvanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed   +6 more
wiley   +1 more source

Measuring user similarity using electric circuit analysis: application to collaborative filtering. [PDF]

open access: yesPLoS ONE, 2012
We propose a new technique of measuring user similarity in collaborative filtering using electric circuit analysis. Electric circuit analysis is used to measure the potential differences between nodes on an electric circuit.
Joonhyuk Yang   +3 more
doaj   +1 more source

Collaborative browsing and visualisation of the search process [PDF]

open access: yes, 1996
The term browsing is frequently applied to information searching activities although it is has been defined in many different ways4. In this paper we highlight the social and collaborative aspects of browsing and discuss how they may be assisted by ...
David M. Nichols   +3 more
core  

A model for mobile content filtering on non-interactive recommendation systems

open access: yes, 2011
To overcome the problem of information overloading in mobile communication, a recommendation system can be used to help mobile device users. However, there are problems relating to sparsity of information from a first-time user in regard to initial ...
Wong, K.W.   +5 more
core   +1 more source

Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows

open access: yesAdvanced Engineering Materials, EarlyView.
A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba   +5 more
wiley   +1 more source

Building Switching Hybrid Recommender System Using Machine Learning Classifiers and Collaborative Filtering

open access: yes, 2010
Recommender systems apply machine learning and data mining techniques for filtering unseen information and can predict whether a user would like a given resource.
Prugel-Bennett, Adam   +1 more
core  

Deep variational models for collaborative filtering-based recommender systems

open access: yes, 2022
CRUE-CSIC (Acuerdos Transformativos 2022)Deep learning provides accurate collaborative filtering models to improve recommender system results. Deep matrix factorization and their related collaborative neural networks are the state of the art in the field;
Ortega, Fernando   +3 more
core   +1 more source

Incorporation of Selenium into Sol–Gel‐Derived Bioactive Glass: Influence on Glass Structure, Bioactivity, and its Selective Cytotoxicity

open access: yesAdvanced Engineering Materials, EarlyView.
Selenium was incorporated into a sol–gel‐derived bioactive glass to enable sustained therapeutic ion release. The selenium‐containing glass preserved bioactivity while selectively inducing cytotoxicity in osteosarcoma cells and maintaining osteoblastic viability.
Breno Rocha Barrioni   +7 more
wiley   +1 more source

An improved switching hybrid recommender system using naive Bayes classifier and collaborative filtering

open access: yes, 2010
Recommender Systems apply machine learning and data mining techniques for filtering unseen information and can predict whether a user would like a given resource.
Prugel-Bennett, Adam   +1 more
core  

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