Semantic Data Representation for Improving Tensor Factorization
Authors: Makoto Nakatsuji, Yasuhiro Fujiwara, Hiroyuki Toda, Hiroshi Sawada, Jin Zheng, James Hendler
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments show that SRTF achieves up to 10% higher accuracy than state-of-the-art methods. |
| Researcher Affiliation | Collaboration | Makoto Nakatsuji1, Yasuhiro Fujiwara2, Hiroyuki Toda3, Hiroshi Sawada4, Jin Zheng5, James A. Hendler6 1,3,4NTT Service Evolution Laboratories, NTT Corporation, 1-1 Hikarinooka, Yokosuka-Shi, Kanagawa 239-0847 Japan 2NTT Software Innovation Center, NTT Corporation, 3-9-11 Midori-Cho, Musashino-Shi, Tokyo 180-8585 Japan 5,6Tetherless World Constellation, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180-3590 USA |
| Pseudocode | No | No clearly labeled pseudocode or algorithm blocks were found. The paper describes the MCMC procedure in numbered prose steps. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | Yes | Available at http://www.grouplens.org/node/73 |
| Dataset Splits | Yes | We divided the dataset into three parts and performed three-fold cross validation. |
| Hardware Specification | No | Since GCTF requires much more computation than BPTF or SRTF (see Preliminary), we could not apply GCTF to the whole evaluation dataset on our computer. |
| Software Dependencies | No | The paper mentions tools like 'Stanford-parser' but does not specify version numbers for any software libraries or dependencies used in the implementation. |
| Experiment Setup | Yes | Following (Xiong et al. 2010), the parameters are µ0=0, ν0=0, β0=0, W0=I, ν0=1, and W0=1. L is 500. |