@@ -3,6 +3,29 @@ This is a repository for NoMoAds - a system for predicting whether or not networ
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request for an ad. For other details about the project, visit the project
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[ website] ( http://athinagroup.eng.uci.edu/projects/nomoads/ ) .
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+ ## Citing NoMoAds
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+ If you create a publication (including web pages, papers published by a
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+ third party, and publicly available presentations) using NoMoAds or the
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+ NoMoAds dataset, please cite the
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+ [ corresponding paper] ( https://www.petsymposium.org/2018/files/papers/issue4/popets-2018-0035.pdf )
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+ as follows:
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+
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+ ```
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+ @article{shuba2018nomoads,
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+ title={{NoMoAds: Effective and Efficient Cross-App Mobile Ad-Blocking}},
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+ author={Shuba, Anastasia and Markopoulou, Athina and Shafiq, Zubair},
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+ journal={Proceedings on Privacy Enhancing Technologies},
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+ volume={2018},
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+ number={4},
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+ year={2018},
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+ publisher={De Gruyter Open}
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+ }
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+ ```
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+
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+ We also encourage you to provide us (<nomoads.uci@gmail.com >) with a
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+ link to your publication. We use this information in reports to our
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+ funding agencies.
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+
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## Quick Start
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### Prerequisites
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* Python 2.7
@@ -14,7 +37,7 @@ request for an ad. For other details about the project, visit the project
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* Download the NoMoAds dataset from
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[ our website] ( http://athinagroup.eng.uci.edu/projects/nomoads/data/ ) .
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- * Unzip the contents and place them in a folder of our choosing.
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+ * Unzip the contents and place them in a folder of your choosing.
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Throughout the document we will refer to this folder as ` DATA_ROOT ` .
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Your folder structure should look as follows:
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```
@@ -157,3 +180,6 @@ for other scripts to use.
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` utils.py ` - contains various global variables and utility methods
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used by other scripts.
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+
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+ ## Acknowledgements
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+ * [ ReCon] ( https://github.com/Eyasics/recon )
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