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].
JUMP: a Jointly Predictor for User Click and Dwell Time
Authors: Tengfei Zhou, Hui Qian, Zebang Shen, Chao Zhang, Chengwei Wang, Shichen Liu, Wenwu Ou
IJCAI 2018 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments demonstrate that JUMP outperforms state-of-the-art methods in both user click and dwell time prediction. |
| Researcher Affiliation | Collaboration | Tengfei Zhou1, Hui Qian1 , Zebang Shen1, Chao Zhang1,Chengwei Wang1, Shichen Liu2, Wenwu Ou2 1College of Computer Science and Technology, Zhejiang University, 2Searching Group of Alibaba Inc. EMAIL, EMAIL, EMAIL |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any specific links to source code repositories or explicitly state that the code for the described methodology is open-source or publicly available. |
| Open Datasets | Yes | We conduct experiments on three publicly available datasets including Rec Sys15, CIKM16, and REDDIT. |
| Dataset Splits | No | The paper states: "we split all sessions of the datasets into 80% for training and 20% for testing." It does not explicitly mention a separate validation split or its size. |
| Hardware Specification | Yes | All the compared methods are performed on the same PC with i7-7820HK CPU, 16GB RAM, and GTX1080 GPU. |
| Software Dependencies | No | The paper mentions "All the compared methods are optimized by Adam" but does not provide specific version numbers for any software dependencies, such as programming languages, libraries, or frameworks (e.g., Python version, TensorFlow/PyTorch versions). |
| Experiment Setup | Yes | All the compared methods are optimized by Adam with the batch size set to 100. For all the methods in our comparison, the dimension of item embedding vectors is set to 100... For our model, we set σ to 10, c1 = 2000 and c2 = 30. |