Beyond the Click-Through Rate: Web Link Selection with Multi-level Feedback
Authors: Kun Chen, Kechao Cai, Longbo Huang, John C.S. Lui
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We conduct extensive experiments on three real-world datasets, and show that Con UCB outperforms state-of-the-art context-free bandit algorithms concerning the multi-level feedback structure. |
| Researcher Affiliation | Academia | Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University Department of Computer Science and Engineering, The Chinese University of Hong Kong |
| Pseudocode | Yes | Algorithm 1 Constrained Upper Confidence Bound |
| Open Source Code | No | The paper does not provide any statement or link regarding the public availability of its source code. |
| Open Datasets | Yes | Two datasets, Coupon Purchase [Kaggle, 2016] and Ad-Clicks [Kaggle, 2015], with 271 coupons and 225 ads respectively, are shown to have a two-level feedback structure in [Cai et al., 2017]. The third dataset, ed X-Course, is extracted from the data on 290 Harvard and MIT ed X online courses [Chuang and Ho, 2016]. |
| Dataset Splits | No | The paper mentions running algorithms for 50,000 rounds and generating rewards, but does not specify train/validation/test dataset splits or their sizes. |
| Hardware Specification | No | The paper does not provide any specific hardware details used for running the experiments. |
| Software Dependencies | No | The paper mentions implementing several bandit algorithms but does not provide specific software dependencies or version numbers. |
| Experiment Setup | Yes | For the three datasets, we run the three algorithms together with Con-UCB for 50,000 rounds with parameter settings as shown in Figure 1-3, respectively. In particular, the parameters of EXP3.M and LEXP are set in accordance with Corollary 1 of [Uchiya et al., 2010] and Theorem 1 of [Cai et al., 2017], respectively. |