# A Hybrid Approach Using Topic Modeling and Class-Association Rule Mining for Text Classification: the Case of Malware Detection

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-hybrid-approach-using-topic-modeling-and-class-association-rule-mining-for/

## Facts

| Field | Value |
| --- | --- |
| Author Names | B. Shravan Kumar,Vadlamani Ravi |
| Citations | 2 |
| DOI | 10.1109/icci-cc.2018.8482043 |
| Fields | Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2897318720 |
| Type | conference-paper |
| Year | 2018 |

## Paper authors

- [B. Shravan Kumar](https://scholariq.org/researchers/b-shravan-kumar/)

## Paper primary topic

- [Spam and Phishing Detection](https://scholariq.org/topics/spam-and-phishing-detection/)

## Paper topics

- [Spam and Phishing Detection](https://scholariq.org/topics/spam-and-phishing-detection/)
- [Advanced Malware Detection Techniques](https://scholariq.org/topics/advanced-malware-detection-techniques/)
- [Network Security and Intrusion Detection](https://scholariq.org/topics/network-security-and-intrusion-detection/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.