This repository collects decision tree research papers with implementations.
Open source
24 alternativesAwesome Fraud Detection Papers
This repository curates data mining research papers focused on fraud detection.
About Awesome Fraud Detection Papers
Awesome Fraud Detection Papers is a curated GitHub repository that lists data mining research papers about fraud detection. Each entry includes the paper title, venue and year, authors, and a link to the paper. The list draws on papers from named conferences in network science, data science, natural language processing, data mining, artificial intelligence and databases. The repository is open source and written in Python.
The homepage excerpt shows entries from 2024 and 2025. Its pricing is unknown, and the excerpt does not state how many papers the list contains or how often it is updated.
Key features
- Curated list of fraud detection papers from named research conferences
- Papers grouped by year and by conference
- Conference groups span network science, data science, NLP, data mining, AI and databases
- Each entry lists title, venue, year, authors and a paper link
- Repository includes a Python file named awesome.py
Best for: Researchers, students and data scientists who want a starting point for reading published work on fraud detection.
Good for
- Open source repository
- Papers are organized by year and by conference
- Each entry links to the source paper
Watch out for
- Papers are limited to the conferences named in the list
Awesome Fraud Detection Papers at a glance
- Category
- AI & Machine Learning › AI Search & Research
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Awesome Fraud Detection Papers FAQ
Which conferences are covered by the list?
The excerpt names ASONAM, Complex Networks, DSAA, ACL, KDD, ICDM, SIGIR, SDM, WWW, CIKM, AAAI, AISTATS, IJCAI, UAI and VLDB.
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