Beyond Link Prediction: Predicting Hyperlinks in Adjacency Space

Authors: Muhan Zhang, Zhicheng Cui, Shali Jiang, Yixin Chen

AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We evaluate CMM on two novel tasks: predicting recipes of Chinese food, and finding missing reactions of metabolic networks. Experimental results demonstrate the superior performance of our method over many seemingly promising baselines.
Researcher Affiliation Academia Muhan Zhang, Zhicheng Cui, Shali Jiang, Yixin Chen Department of Computer Science and Engineering, Washington University in St. Louis {muhan, z.cui, jiang.s}@wustl.edu, chen@cse.wustl.edu
Pseudocode Yes Algorithm 1 Coordinated Matrix Minimization
Open Source Code Yes All the codes and data are available at https://github.com/muhanzhang/HyperLinkPrediction.
Open Datasets Yes We downloaded 882 most popular Sichuan recipes and Cantonese recipes from meishij.net, which is a professional platform to find Chinese recipes. and We downloaded all 11893 reactions from BIGG (http://bigg.ucsd.edu) to build a candidate reaction pool.
Dataset Splits No The paper mentions using 'cross validation' for hyperparameter tuning, but does not explicitly provide specific training, validation, and test dataset splits with percentages or sample counts for the main model evaluation.
Hardware Specification No The paper states 'All experiments were done on a 12-core Intel Xeon Linux server,' which is not specific enough (lacks exact CPU model, clock speed, GPU, or memory details).
Software Dependencies No The paper states 'We implement the proposed CMM in MATLAB,' but does not provide specific version numbers for MATLAB or any other software dependencies.
Experiment Setup Yes The number of latent factors k in CMM is set to 30. The maximum iteration number was set to 100. The convergence threshold was set to 1.0E-4. and The damping factor β is determined by searching over {0.001,0.005,0.01,0.1,0.5} using cross validation.