Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Recommendation with Social Dimensions
Authors: Jiliang Tang, Suhang Wang, Xia Hu, Dawei Yin, Yingzhou Bi, Yi Chang, Huan Liu
AAAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results on real-world data sets demonstrate the effectiveness of the proposed framework. |
| Researcher Affiliation | Collaboration | Texas A&M University, EMAIL Yahoo Labs, EMAIL Arizona State University, EMAIL Guangxi Teachers Education University, EMAIL |
| Pseudocode | No | No structured pseudocode or algorithm blocks were found. The paper describes the mathematical equations for the model and updates. |
| Open Source Code | No | No concrete access to source code for the methodology was provided. The links given are for datasets only. |
| Open Datasets | Yes | We collect two datasets to evaluate our proposed recommender system, i.e., Epinions and Ciao1, and these two datasets are publicly available via the homepage of the first author 2. 1http://www.ciao.co.uk/ 2http://www.jiliang.xyz/trust.html |
| Dataset Splits | No | For each dataset, we choose x% as the training set to learn parameters and the remaining 1 x% as the testing set where x is varied as {45, 65, 85}. The paper mentions training and testing sets, but does not explicitly detail a separate validation set or its split. |
| Hardware Specification | No | No specific hardware details (e.g., GPU/CPU models, memory, or computing cluster specifications) were provided for the experimental setup. |
| Software Dependencies | No | No specific software dependencies with version numbers were mentioned. The paper describes the mathematical framework and algorithms but does not list programming languages, libraries, or solvers with versions. |
| Experiment Setup | Yes | For So Dim Rec, we set {K = 20, c = 100, λ1 = 5, λ2 = 100} and {K = 30, c = 500, λ1 = 10, λ2 = 100} for Ciao and Epinions, respectively. α is empirically set to 0.1. |