35 lines
1.9 KiB
Python
35 lines
1.9 KiB
Python
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# Title: Project 1 - Social Network Attribute Prediction
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# Author: Rory Healy
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# Date created - 18th April 2019
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def friendship_closeness():
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'''Assigns a "friendship-closeness" value, from 0 to 1, based on the number
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of degrees of seperation between people. The further the seperation, the
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closer this value is to 0. Takes a dictionary of sets of friends
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"bestie_dict" and returns a dictionary of sets of friends with their
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"friendship-closeness" value.'''
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def prioritise_friendships():
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'''Make the predictions prioritise those from the people with the highest
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"friendship-closeness" value. Takes a user, stored as the string
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"unknown_user", and returns a list of sets of other people in order of
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highest to lowest closeness (e.g. degree-one friends are in the first set,
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degree-two people are in the second set, etc.).'''
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def friendly_prediction(unknown_user, features, bestie_dict, feat_dict):
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'''Takes a user, stored as the string "unknown_user", features of the user
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that are used to predict attributes, stored as a set "features", a
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dictionary of sets of friends "bestie_dict", and a dictionary containing
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the known attributes for each user "feat_dict". Returns a dictionary of
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features with a predicted list of values for each feature.'''
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# For the first given example, the predicted favourite author comes from
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# Kim, while the predicted university comes from both Sandy and Alex. As
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# Sandy and Alex are both degree-two friends, preference can be given to
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# neither without further information. This is a main limitation for the
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# 'friendship-closeness' value being used to make a prediction, as the
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# unknown user may be closer to one degree-two friends than another. I
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# know that this isn't necessarily relevent to creating this program, just
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# something that I was thinking about while fixing up the other parts of
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# this project.
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