-
公开(公告)号：US10929772B1
公开(公告)日：2021-02-23
申请号：US15385318
申请日：2016-12-20
Applicant: Facebook, Inc.
Inventor： Carlos Gregorio Diuk Wasser , Michael Lee Develin , Smriti Bhagat , Viet An Nguyen , Daniel Matthew Merl
Abstract: Systems, methods, and non-transitory computer readable media are configured to apply a machine learning model to predict an age division for a user based on user information. An age bracket within the age division including a largest number of connections of the user can be determined. The determined age bracket can be assigned for the user.
-
公开(公告)号：US10180935B2
公开(公告)日：2019-01-15
申请号：US15422463
申请日：2017-02-02
Applicant: Facebook, Inc.
Inventor： Daniel Matthew Merl , Aditya Pal , Stanislav Funiak , Seyoung Park , Fei Huang , Amac Herdagdelen
Abstract: A system for identifying language(s) for content items is disclosed. The system can identify different languages for content item words segments by identifying segment languages that maximize a probability across the segments. The probability can be a combination of: an author's likelihood for the language identified for the first word; a combination of transition frequencies for selected languages identified for words, the transition frequencies indicating likelihoods that a transition occurred to the selected language from the previous word's language; and a combination of observation probabilities indicating, for a given word in the content item, a likelihood the given word is in the identified language. For an in-vocabulary word, the observation probabilities can be based on learned probability for that word. For an out-of-vocabulary word, the probability can be computed by breaking the word into overlapping n-grams and computing combined learned probabilities that each n-gram is in the given language.
-
公开(公告)号：US20180189259A1
公开(公告)日：2018-07-05
申请号：US15422463
申请日：2017-02-02
Applicant: Facebook, Inc.
Inventor： Daniel Matthew Merl , Aditya Pal , Stanislav Funiak , Seyoung Park , Fei Huang , Amac Herdagdelen
IPC: G06F17/27
CPC classification number: G06F17/275 , G06F17/2294 , G06F17/2775
Abstract: A system for identifying language(s) for content items is disclosed. The system can identify different languages for content item words segments by identifying segment languages that maximize a probability across the segments. The probability can be a combination of: an author's likelihood for the language identified for the first word; a combination of transition frequencies for selected languages identified for words, the transition frequencies indicating likelihoods that a transition occurred to the selected language from the previous word's language; and a combination of observation probabilities indicating, for a given word in the content item, a likelihood the given word is in the identified language. For an in-vocabulary word, the observation probabilities can be based on learned probability for that word. For an out-of-vocabulary word, the probability can be computed by breaking the word into overlapping n-grams and computing combined learned probabilities that each n-gram is in the given language.
-
-
Search Results
3
records
(took 0.01 seconds)
