Na Mou

1.2k total citations · 1 hit paper
7 papers, 628 citations indexed

About

Na Mou is a scholar working on Information Systems, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Na Mou has authored 7 papers receiving a total of 628 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Information Systems, 4 papers in Computer Vision and Pattern Recognition and 3 papers in Artificial Intelligence. Recurrent topics in Na Mou's work include Recommender Systems and Techniques (6 papers), Image Retrieval and Classification Techniques (3 papers) and Advanced Manufacturing and Logistics Optimization (1 paper). Na Mou is often cited by papers focused on Recommender Systems and Techniques (6 papers), Image Retrieval and Classification Techniques (3 papers) and Advanced Manufacturing and Logistics Optimization (1 paper). Na Mou collaborates with scholars based in China and United States. Na Mou's co-authors include Guorui Zhou, Weijie Bian, Kun Gai, Ying Fan, Chang Zhou, Xiaoqiang Zhu, Lejian Ren, Kailun Wu, Xiang-Rong Sheng and Yujing Zhang and has published in prestigious journals such as Applied Mechanics and Materials and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Na Mou

7 papers receiving 597 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep Interest Evolution Network for Click-Through Rate Prediction

2019 578 citations Guorui Zhou, Na Mou et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Na Mou China	3	528	325	229	106	95	7	628
Jiahui Liu China	6	365 0.7×	234 0.7×	128 0.6×	71 0.7×	71 0.7×	18	508
Keping Yang China	10	286 0.5×	267 0.8×	90 0.4×	89 0.8×	31 0.3×	16	420
Bo Long United States	10	381 0.7×	304 0.9×	106 0.5×	107 1.0×	47 0.5×	21	506
Refuoe Mokhosi China	5	540 1.0×	455 1.4×	113 0.5×	166 1.6×	50 0.5×	9	602
Mohammad Yahya H. Al-Shamri Saudi Arabia	8	371 0.7×	185 0.6×	133 0.6×	70 0.7×	93 1.0×	20	513
Ziwei Fan China	11	437 0.8×	396 1.2×	99 0.4×	103 1.0×	63 0.7×	37	570
Balázs Hidasi Hungary	7	419 0.8×	288 0.9×	148 0.6×	113 1.1×	45 0.5×	14	488
Xiangwu Meng China	15	457 0.9×	229 0.7×	122 0.5×	37 0.3×	136 1.4×	67	539
Shengxian Wan China	6	378 0.7×	516 1.6×	170 0.7×	87 0.8×	46 0.5×	6	704
Vreixo Formoso Spain	4	351 0.7×	119 0.4×	117 0.5×	71 0.7×	61 0.6×	13	380

Countries citing papers authored by Na Mou

Since Specialization

Citations

This map shows the geographic impact of Na Mou's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Na Mou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Na Mou more than expected).

Fields of papers citing papers by Na Mou

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Na Mou. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Na Mou. The network helps show where Na Mou may publish in the future.

Co-authorship network of co-authors of Na Mou

This figure shows the co-authorship network connecting the top 25 collaborators of Na Mou. A scholar is included among the top collaborators of Na Mou based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Na Mou. Na Mou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Wang, Chaokun, et al.. (2025). Pone-GNN: Integrating Positive and Negative Feedback in Graph Neural Networks for Recommender Systems. 3(2). 1–23. 1 indexed citations

2.

Liu, Chi, et al.. (2025). DimeRec: A Unified Framework for Enhanced Sequential Recommendation via Generative Diffusion Models. 726–734. 2 indexed citations

3.

Mou, Na, et al.. (2024). Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems. 3621–3631. 2 indexed citations

4.

Tan, Jianchao, et al.. (2023). SHARK: A Lightweight Model Compression Approach for Large-scale Recommender Systems. 4930–4937. 4 indexed citations

5.

Bian, Weijie, Kailun Wu, Lejian Ren, et al.. (2022). CAN. 57–65. 40 indexed citations

6.

Zhou, Guorui, Na Mou, Ying Fan, et al.. (2019). Deep Interest Evolution Network for Click-Through Rate Prediction. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 5941–5948. 578 indexed citations breakdown →

7.

Mou, Na, et al.. (2014). A Study for Storage Allocation in Synchronized Zones Based on the Association Analysis of Goods. Applied Mechanics and Materials. 687-691. 4658–4665. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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