Mobile Query Recommendation via Tensor Function Learning
Authors: Zhou Zhao, Ruihua Song, Xing Xie, Xiaofei He, Yueting Zhuang
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We empirically evaluate our approach based on the mobile query dataset from Bing search engine in the city of Beijing, China, and show that our method can outperform several state-of-the-art approaches. |
| Researcher Affiliation | Collaboration | Zhou Zhao1, Ruihua Song3, Xing Xie3, Xiaofei He2 and Yueting Zhuang1 1College of Computer Science, Zhejiang University 2State Key Lab of CAD&CG, Zhejiang University 3Microsoft Research, Beijing, China |
| Pseudocode | Yes | Algorithm 1 Solving Problem (5) via TFL |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described (no repository link, explicit code release statement, or code in supplementary materials). |
| Open Datasets | No | In the experiment, we apply our method on the Bing mobile dataset, which consists of users location and their mobile queries from Bing search engine during Jan. 2014 to June 2014 in the city of Beijing, China. To protect users privacy, we remove the GPS points for work places, homes, and users information, and use the sampled data for doing the experiments. |
| Dataset Splits | Yes | We randomly sample 90% of the observed querylocation-user relations in tensor Y as training data. We then consider the remaining 10% of the observed relations as testing data. |
| Hardware Specification | Yes | The experiments are conducted by using Matlab and Tensor Tool Box [Bader et al., 2015], tested on machines with Windows OS Intel(R) Core(TM) i7-2600 CPU 3.40GHz, and 128 GB RAM. |
| Software Dependencies | Yes | The experiments are conducted by using Matlab and Tensor Tool Box [Bader et al., 2015]. The cited reference [Bader et al., 2015] explicitly states 'Matlab tensor toolbox version 2.6'. |
| Experiment Setup | No | The paper describes the evaluation criteria and data splitting, but does not provide specific hyperparameter values (e.g., learning rate, batch size) or other detailed training configurations for the proposed model. |