Full metadata
Title
Multi-class and Multi-label classication of Darkweb Data
Description
In this research, I try to solve multi-class multi-label classication problem, where
the goal is to automatically assign one or more labels(tags) to discussion topics seen
in deepweb. I observed natural hierarchy in our dataset, and I used dierent
techniques to ensure hierarchical integrity constraint on the predicted tag list. To
solve `class imbalance' and `scarcity of labeled data' problems, I developed semisupervised
model based on elastic search(ES) document relevance score. I evaluate
our models using standard K-fold cross-validation method. Ensuring hierarchical
integrity constraints improved F1 score by 11.9% over standard supervised learning,
while our ES based semi-supervised learning model out-performed other models in
terms of precision(78.4%) score while maintaining comparable recall(21%) score.
the goal is to automatically assign one or more labels(tags) to discussion topics seen
in deepweb. I observed natural hierarchy in our dataset, and I used dierent
techniques to ensure hierarchical integrity constraint on the predicted tag list. To
solve `class imbalance' and `scarcity of labeled data' problems, I developed semisupervised
model based on elastic search(ES) document relevance score. I evaluate
our models using standard K-fold cross-validation method. Ensuring hierarchical
integrity constraints improved F1 score by 11.9% over standard supervised learning,
while our ES based semi-supervised learning model out-performed other models in
terms of precision(78.4%) score while maintaining comparable recall(21%) score.
Date Created
2018
Contributors
- Patil, Revanth (Author)
- Shakarian, Paulo (Thesis advisor)
- Doupe, Adam (Committee member)
- Davulcu, Hasan (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
40 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.48469
Level of coding
minimal
Note
Masters Thesis Computer Science 2018
System Created
- 2018-04-30 01:10:01
System Modified
- 2021-08-26 09:47:01
- 3 years 2 months ago
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