- Tag Recommendations in Folksonomies Robert Jaschke1,2
- BPR: Bayesian Personalized Ranking from Implicit Feedback Steffen Rendle, Christoph Freudenthaler, Zeno Gantner and Lars Schmidt-Thieme
- Factorization Models for Forecasting Student Performance Nguyen Thai-Nghe, Tomas Horvath and Lars Schmidt-Thieme, University of Hildesheim, Germany
- Factorization Models for Context-/Time-Aware Movie Recommendations
- Eigenmode Identification in Campbell Diagrams Krisztian Buza, Christine Preisach, Andre Busche, Lars Schmidt-Thieme
- Procedia Computer Science 01 (2010) 19 Procedia Computer
- Collaborative Tag Recommendations Leandro Balby Marinho and Lars Schmidt-Thieme
- Personalized Forecasting Student Performance Nguyen Thai-Nghe
- Online-Updating Regularized Kernel Matrix Factorization Models for Large-Scale Recommender Systems
- Learning Optimal Threshold on Resampling Data to Deal with Class Imbalance
- Integrating OLAP and Recommender Systems: An Evaluation Perspective
- Scaling Record Linkage to Non-Uniform Distributed Class Sizes
- class AlgBase{ void f(args);
- Attribute Aware Anonymous Recommender Systems
- A New Evaluation Measure for Learning from Imbalanced Data Nguyen Thai-Nghe, Zeno Gantner, and Lars Schmidt-Thieme, Member, IEEE
- XMedia: Web People Search by Clustering with Machinely Learned Similarity Measures
- aho@cs.uni-kassel.de Lars Schmidt-Thieme
- Semi-Supervised Tag Recommendation -Using Untagged Resources to Mitigate Cold-Start Problems
- Relational Classification for Personalized Tag Recommendation
- Tag-aware Recommender Systems by Fusion of Collaborative Filtering Algorithms
- Automatic Content-based Categorization of Wikipedia Articles Zeno Gantner
- Exploiting Semantic Product Descriptions for Recommender Systems
- GQR: A Fast Solver for Binary Qualitative Constraint Networks Matthias Westphal and Stefan Wolfl
- Factor Models for Tag Recommendation in BibSonomy
- Factorization Techniques for Predicting Student Performance
- Learning Attribute-to-Feature Mappings for Cold-Start Recommendations Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, Steffen Rendle and Lars Schmidt-Thieme
- Information Integration of Partially Labeled Data
- FLarsScdt-Thieme 2. Basic Eclat Algorithm
- IQ Estimation for Accurate Time-Series Classification
- Pairwise Interaction Tensor Factorization for Personalized Tag Recommendation
- Time-Series Classification based on Individualised Error Prediction Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme
- Relational Ensemble Classification Christine Preisach
- Comparison of Recommender System Algorithms focusing on the New-Item and
- Cost-Sensitive Learning Methods for Imbalanced Data Nguyen Thai-Nghe, Zeno Gantner, and Lars Schmidt-Thieme, Member, IEEE
- Mining Music Playlogs for Next Song Recommendations Andre Busche, Artus Krohn-Grimberghe, Lars Schmidt-Thieme
- On Learning Knowledge Bases for Collabularies Krisztian Buza, Dipl.-Ing.1 3
- Object Identification with Constraints Steffen Rendle, Lars Schmidt-Thieme
- Improving Academic Performance Prediction by Dealing with Class Imbalance Nguyen Thai-Nghe, Andre Busche, and Lars Schmidt-Thieme
- Towards Better Modeling of Supermarkets K. Buza*, A. Buza** and P.B. Kis**
- A Simple Ensemble Technique Team: ISMLL
- Sensitivity of Attributes on the Performance of Attribute-Aware Collaborative Filtering
- A Novel Multidimensional Framework for Evaluating Recommender Systems
- Graph-based Model-Selection Framework for Large Ensembles
- Optimal Ranking for Video Recommendation Zeno Gantner, Christoph Freudenthaler, Steffen Rendle, and Lars
- Learning Optimal Ranking with Tensor Factorization for Tag Recommendation
- Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference
- Folksonomy-based Collabulary Learning Leandro Balby Marinho, Krisztian Buza and Lars Schmidt-Thieme
- Empirical Analysis of Attribute-Aware Recommender System Algorithms Using
- Ideas and Improvements for Semantic Wikis Jochen Fischer, Zeno Gantner, Steffen Rendle,
- Evaluation of Attribute-aware Recommender System Algorithms on Data with Varying
- Attribute-Aware Collaborative Filtering Karen Tso and Lars Schmidt-Thieme
- Optimal Discretization of Quantitative Attributes for Association Rules
- Reservation Price Estimation by Adaptive Conjoint Analysis
- Az AIDS elrehaladsnak felismerse gpi tanuls eszkzeivel
- GQR A Fast Reasoner for Binary Qualitative Constraint Calculi Zeno Gantner
- Recommending in Social Tagging Systems based on Kernelized Multiway Analysis
- MATRIX AND TENSOR FACTORIZATION FOR PREDICTING STUDENT PERFORMANCE
- Bayesian Personalized Ranking for Non-Uniformly Sampled Items
- Fast Classification of Electrocardiograph Signals via Instance Selection Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme
- MyMediaLite: A Free Recommender System Library Zeno Gantner
- Fusion of Similarity Measures for Time Series Classification
- Multi-Relational Factorization Models for Predicting Student Performance
- Individualized Error Estimation for Classification and Regression Models
- INSIGHT: Efficient and Effective Instance Selection for Time-Series Classification
- Scalable Event-based Clustering of Social Media via Record Linkage Techniques Timo Reuter, Philipp Cimiano
- Fast Context-aware Recommendations with Factorization Machines
- Fusion Methods for Time-Series Classification
- IJCSNS International Journal of Computer Science and Network Security, VOL.7 No.4, April 2007 255 New Multi Attributes Procurement Auction for Agent-
- Factorizing Markov Models for Categorical Time Series Christoph Freudenthaler
- Comparing Prediction Models for Active Learning in Recommender Systems
- Towards Optimal Active Learning for Matrix Factorization in Recommender Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme
- Factorization Machines Factorized Polynomial Regression Models
- Abstract--There are a lot of patterns for software development which Model-View-Controller (MVC) pattern is one of them. In
- Non-myopic Active Learning for Recommender Systems Based on Matrix Factorization
- RFID-Enhanced Museum for Interactive Rasoul Karimi, Alexandros Nanopoulos, Lars Schmidt-Thieme
- Active Learning for Aspect Model in Recommender Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme
- Bayesian Factorization Machines Christoph Freudenthaler, Lars Schmidt-Thieme
- Multi-Relational Matrix Factorization using Bayesian Personalized Ranking for Social Network Data
