Thanks Ted. If you can please elaborate on this , Let's say for example I am recommending online books and 1000 users joined and added most of the popular books to their list and rate them high to be similar to other users , then they start adding books they want to advertise , how can I detect this attitude ? and how can I know if these are malicious users or true users that just have common interests ? Is there a way that I can solve this case that happened to Amazon http://news.cnet.com/2100-1023-976435.html
Thanks On Tue, Aug 28, 2012 at 8:23 PM, Ted Dunning <[email protected]> wrote: > The single most effective thing you can do with malicious users like this > is to let them think that they have won. In the ideal case, you can detect > simple click frauds and maintain a per user play adjustment so that they > see the fraudulent stats and everybody else sees the corrected stats. If > you can, this should even extend to your leader board pages. Once you have > this, the fraudsters will generally not increase the sophistication of > their attacks and you have a fairly simple situation. > > You also will have a bit of an advantage if you pick a metric that > indicates fairly serious engagement. With videos, for instance, I have > used plays > 30 seconds as the metric and this was handled by a beacon on > the page while the 30 second delay measurement was on the server side. > This requires a browser to be live and in focus for 30 seconds in order to > get a play event which substantially increases the cost of committing the > click fraud on the fraudsters side. > > With the recommendation analysis itself, the key is to flatten all > frequency metrics per user. With unsophisticated click fraud, the abuse > will center on creating high play frequencies for a few users which will > then be counted as a very small input signal since so few users are doing > it and their high play rates won't matter. Also, the major effect if any > will be to simply give the fraudsters recommendations for their own items > which will make them happy and won't matter to anyone else. > > On Tue, Aug 28, 2012 at 6:29 PM, Zia mel <[email protected]> wrote: > >> Hi , >> >> Is there any way to check for malicious users in mahout so I can >> remove them from the recommendations or reduce their effect ? >> Malicious users are the ones that want to play with the ratings and >> increase or downgrade it. >> >> Thanks, >>
