As someone whose written this kind of anomaly detection system, can you elaborate a bit on what mechanisms you'd be using and how they'd be different or distinct from efforts in the past?
- Serge On Sun, Dec 18, 2016 at 6:38 PM, Animesh Sinha <sinha.animes...@gmail.com> wrote: > Hi, > > I am a first year masters students at Purdue University and would like to > propose a project idea for GSoC 2017. I have worked on Vandalism Detection > in Wikipedia in the past and understand how important it is to predict if an > information is correct or not as it may be misleading to others. > > Hence, I would like to propose this project idea: > > Title: Detect if a user edit made in OSM is a vandal edit or regular. > Summary: It's a very challenging task to monitor the malicious edits or > spams manually for a large active user base. I plan to identify the cases of > vandalism on OSM by classifying edits as either regular or vandal. This is > clearly a Binary Classification task, but if the distribution of regular and > vandalism cases in the dataset are skewed, it can also be explored as an > Anomaly Detection problem. > Requirements: Lots of data about the edits made, information about the users > making the edit, information about the people annotating the true labels, > etc. > > I would appreciate if someone can provide a feedback on the project idea and > the requirements needed. > > Thanks, > Animesh Sinha > > _______________________________________________ > dev mailing list > dev@openstreetmap.org > https://lists.openstreetmap.org/listinfo/dev > _______________________________________________ dev mailing list dev@openstreetmap.org https://lists.openstreetmap.org/listinfo/dev
