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Facebook machine learning technology improves; Redditors alaramed.

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Re: Facebook machine learning technology improves; Redditors alaramed.

#61

Post by reinhardt »

dhx wrote: post #57

LinkedIn appears to build "social graphs" based on profile views. If person A visits the profile of person B and C it is quite likely that some form of relationship exists (perhaps an inverse relationship too). It doesn't just have to be profile views -- LinkedIn most likely keeps track of search terms too. If a random unknown visitor comes along and searches for both "Person A" and "Person C" then it is likely that…

I was about to post about LinkedIn too. I am convinced it uses, among others, reverse view lookups. I have had suggestions for people I know whose LinkedIn profile I had never viewed or searched for myself; the only explanation is they had looked for me. I don't know if it's because I interact with it more frequently and using real personal info but its "people you may know" predictions are eerily more accurate than FB, or anything else for that matter.

Re: Facebook machine learning technology improves; Redditors alaramed.

#62

Post by forensic »

kokey wrote: post #52
jagira wrote: post #29

Just checked this. I took some pics on a regular digital camera (no GPS) in Indore. I uploaded them from New Delhi a few weeks later. And now FB is asking me "Were these pics taken in Indore?". Crazy shit. Update - I dug through my FB updates. Just before leaving for airport, I updated my status to "Off to Indore" and after coming back to New Delhi, I had some status updates about my office and a local park. Facebook…

I think you are actually getting to the bottom of it. A combination of timestamps, and status updates, and probably that of friends tagged in the same album. Could be quite effective, as we can see.

yeah this is by far most likely. The guy's wife or whatever had her phone turned on while in labour, facebook knows her GPS coords, facebook knows she's his wife, and so on

doesnt take much to throw out a guess based on a single GPS location + timestamp. Even if the guess is only right 5% of the time it is still a profitable guess to make.

Re: Facebook machine learning technology improves; Redditors alaramed.

#63

Post by simondlr »

Facebook has suggested twice accurately places I've visited, but I pretty much specified it in the album (Singapre and Australia).

There is an album now with random photos, with the location "Plekke" (which is afrikaans for "places"). They are suggesting "Plekke, San Juan, Puerto Rico". So, currently I wouldn't suggest machine learning, although it is not entirely dismissible. They have the largest photo db in the world, they could eventually learn and then seed it with stuff like checkins, status updates, etc.

EDIT: I have another album called "Kuala Lumpur and Thailand", which have pretty iconic pictures in it (Wat Pho, KL Towers, Batu Caves, etc) and they haven't asked me about that album at all.

Re: Facebook machine learning technology improves; Redditors alaramed.

#64

Post by zombielifestyle »

zombielifestyle wrote: post #54

I've tried it. i don't use fb for pics. i don't use wifi on my smartphone and i had the fb app only briefly installed. i also weren't on any trips outside my city. I've uploaded 4 screenshot-ed landscape (including one building) pics from flicker with absolutely no metadata. at least 2 of them should be very recognizable. the only thing that fb suggested was the single check-in that i had, minimum of 500km off. i'm p…

fb don't even matches the check-in of my fake wife at hollywood walk of fame to an pic of it uploaded by me.

Re: Facebook machine learning technology improves; Redditors alaramed.

#66

Post by amouat »

phpnode wrote: post #4

Here's my guess at how it's done: Redditor has facebook app installed on their smartphone (or just uses the website), sets status to "OMG wife is going into labour, at the hospital now". Facebook now knows roughly where redditor was at the specified time based on the ip, they can narrow this down further by looking at keywords in the status message and check it against a list of addresses in the local area and select…

My photo locations seemed to be mainly based on the album title - I was impressed that it got both locations from "St Catharines and Niagara" correct.

I haven't checked to see if the individual photos are correct. However, at the time I didn't have a smart phone and I'm pretty sure my camera wouldn't provide much useful info.

UPDATE: I take it back: fb thinks I was at a football camp called St Catharines and Niagara! http://www.facebook.com/pages/St-Catharines-and-Niagara/1821...

I think that shows that the title is the most important indicator to fb.

Re: Facebook machine learning technology improves; Redditors alaramed.

#68

Post by finnw »

dhx wrote: post #57

LinkedIn appears to build "social graphs" based on profile views. If person A visits the profile of person B and C it is quite likely that some form of relationship exists (perhaps an inverse relationship too). It doesn't just have to be profile views -- LinkedIn most likely keeps track of search terms too. If a random unknown visitor comes along and searches for both "Person A" and "Person C" then it is likely that…

I've found the opposite. LinkedIn has been right only once for me. The other 23 people it suggested I might know were people I have never heard of.

Facebook usually suggests people I have met but do not want to be "friends" with.

Re: Facebook machine learning technology improves; Redditors alaramed.

#70

Post by iradik »

freedompeace wrote: post #2

How could Facebook do this (technologically)? According to a redditor, " - It's not IP address . Facebook successfully identified a number of specific locations (bars, theaters, etc) even though I had uploaded the photos from my home - It's not geo-tagging . All of my photos were taken with a camera that does not geo-tag (Nikon d700). - It's not contextual tagging . There were no people tagged in the photos, no comme…

This is how it can be done without any EXIF/GPS data with a fairly dumb algorithm.

It's a picture of a baby at a hospital.

There are probably hundreds of baby photos being taken per day at that hospital being posted to FB. Some have GPS and some don't.

The images that do have GPS, get recognized and lumped together as the same "entity" since they all look the same.

FB then looks up where she lives, then looks for any photos that don't have a location (like her baby photo), then tries to match it with any photos within a 50 mi proximity to her hometown. Bingo finds 90% match on the baby pic in the hospital, and asks user for verification. She says YES, then this pic gets lumped together with all the other entities. FB also asks more often since it's "right".

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