Liangda Li

606 citations
21 papers · 356 · h-index 11

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Advanced Text Analysis Techniques
    • Information Retrieval and Search Behavior
    • Web Data Mining and Analysis
    • Recommender Systems and Techniques

Papers in

Liangda Li

21 papers receiving 346 citations

Peers

Liangda Li
Comparison fields: 5 of 68
  • Artificial Intelligence 166
  • Information Systems 115
  • Computational Mathematics 3
  • Signal Processing 48
  • Transportation 25
Replace Weifeng Su with:
Weifeng Su China
Yutao Zhu China
João Vinagre Portugal
Yuan Zhong China
Nicolas Usunier France
Paolo Rosso Switzerland
Jiali Xia China
Sami Faïz Tunisia
Marcin Sydow Poland
Liangda Li relative to Weifeng Su China Weifeng Su's profile →
Citations per field
00.5×3.4×
Weifeng Su · 1×
Citations per year

Countries citing papers authored by Liangda Li

Since Specialization
Citations

This map shows the geographic impact of Liangda Li'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 Liangda Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liangda Li more than expected).

Fields of papers citing papers by Liangda Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Liangda Li. 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 Liangda Li. The network helps show where Liangda Li may publish in the future.

Co-authors

The 25 scholars most cited alongside Liangda Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Liangda Li Line = papers co-authored together Liangda Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200984
2 201444
3 201130
4 201525
5 201921
6 201420
7 201220
8 201718
9 201318
10 201912
11 201910
12 20209
13 20179
14 20158
15 20167
16
Household structure analysis via hawkes processes for enhancing energy disaggregation
20166
17 20176
18 20154
19 20183
20 20191

About Liangda Li

Liangda Li is a scholar working on Artificial Intelligence, Molecular Biology, Applied Mathematics, Signal Processing and Information Systems, having authored 21 papers that have together received 356 indexed citations. Recurring topics across this work include Point processes and geometric inequalities (6 papers), Diffusion and Search Dynamics (4 papers), Bayesian Methods and Mixture Models (4 papers), Information Retrieval and Search Behavior (3 papers), Data Management and Algorithms (2 papers), Mobile Crowdsensing and Crowdsourcing (2 papers), Economic and Environmental Valuation (2 papers) and Data-Driven Disease Surveillance (2 papers). The work is most often cited by research in Artificial Intelligence (166 citations), Information Systems (115 citations), Computational Mathematics (3 citations), Signal Processing (48 citations) and Transportation (25 citations). Liangda Li has collaborated with scholars based in United States and China. Frequent co-authors include Hongyuan Zha, Yong Yu, Gui-Rong Xue, Ke Zhou, Yi Chang, Hongbo Deng, Anlei Dong, Guy Lebanon, Haesun Park and Ricardo Baeza‐Yates. Their work appears in journals such as Frontiers in Immunology, Plant Diversity, The American Journal of Gastroenterology, ACM Transactions on Intelligent Systems and Technology and Gastroenterology.

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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