集合知プログラミング第2章復習
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The document appears to contain code and tables related to recommender systems and calculating similarity scores between users based on movie ratings. It includes functions for getting recommendations for a user based on similarities to other users' ratings and calculating weighted averages of ratings by similarity. Tables of movie ratings and calculated similarity scores and totals are also present.
![sub get_recommendations {
my ($prefs, $person, $similarity) = @_;
$similarity ||= &sim_pearson;
my (%totals, %simSuns);
for my $other (keys %$prefs) {
##
next if $other eq $person;
my $sim = $similarity->($prefs, $person, $other);
## 0
next if $sim <= 0;
for my $item (keys %{$prefs->{$other}}) {
##
if ( !exists $prefs->{$person}{$item}
or $prefs->{$person}{$item} == 0 ) {
$totals{$item} += $prefs->{$other}{$item} * $sim;
$simSuns{$item} += $sim;
}
}
}
return sort {$b->[1] <=> $a->[1] }
map { [ $_, $totals{$_} / $simSuns{$_} ] } keys %totals;
}](https://image.slidesharecdn.com/2-090826055807-phpapp01/85/2-11-320.jpg)
集合知プログラミング第2章復習
- 1. 2 : id:ninjinkun
- 2. • • ‣ ‣ • • • vs
- 3. 1. ‣ × 2. ‣ × 3. × 4. × 1, 2
- 4. : • ‣ { 'Lisa Rose' => { 'Lady in the Water' => 2.5, 'Snakes on a Plane' => 3.5, 'Just My Luck' => 3.0, 'Superman Returns' => 3.5, 'You, Me and Dupree' => 2.5, 'The Night Listener' => 3.0, }, 'Toby' => { 'Snakes on a Plane' => 4.5, 'You, Me and Dupree' => 1.0, 'Superman Returns' => 4.0, }, 'Claudia Puig' => { 'Snakes on a Plane' => 3.5, 'Just My Luck' => 3.0, 'The Night Listener' => 4.5,
- 5. Toby Rose Puig • Snakes 5 4 3 ‣ 2 1 0 Dupree 0 0.8 1.6 2.4 3.2 4
- 6. • ‣ ‣ •
- 7. (cont.) • Gene Seymour 5 ‣ 4 3 2 1 Mick 0 Lasalle 0 0.8 1.6 2.4 3.2 4 Lisa Rose 4.0 3.2 2.4 1.6 0.8 0 Jack Matthews
- 8. • ‣ Night xNight Lady xLady Rose 0.99 3.0 2.97 2.5 2.475 Seymour 0.38 3.0 1.14 3.0 1.14 Pug 0.89 4.5 4.005 8.115 3.615 Sim. Sum 2.260 1.370 /Sim. Sum 3.591 2.639
- 9. • ‣ Night xNight Lady xLady Rose 0.99 3.0 2.97 2.5 2.475 Seymour 0.38 3.0 1.14 3.0 1.14 Pug 0.89 4.5 4.005 8.115 3.615 Sim. Sum 2.260 1.370 /Sim. Sum 3.591 2.639
- 10. • ‣ Night xNight Lady xLady Rose 0.99 3.0 2.97 2.5 2.475 Seymour 0.38 3.0 1.14 3.0 1.14 Pug 0.89 4.5 4.005 8.115 3.615 Sim. Sum 2.260 1.370 /Sim. Sum 3.591 2.639
- 11. sub get_recommendations { my ($prefs, $person, $similarity) = @_; $similarity ||= &sim_pearson; my (%totals, %simSuns); for my $other (keys %$prefs) { ## next if $other eq $person; my $sim = $similarity->($prefs, $person, $other); ## 0 next if $sim <= 0; for my $item (keys %{$prefs->{$other}}) { ## if ( !exists $prefs->{$person}{$item} or $prefs->{$person}{$item} == 0 ) { $totals{$item} += $prefs->{$other}{$item} * $sim; $simSuns{$item} += $sim; } } } return sort {$b->[1] <=> $a->[1] } map { [ $_, $totals{$_} / $simSuns{$_} ] } keys %totals; }
- 12. × • { 'Lady in the Water' => { 'Lisa Rose' => 2.5, 'Gene Seymour' => 3.0, 'Michael Phillips' => 2.5, }, 'You, Me and Dupree' => { 'Lisa Rose' => 2.5, 'Toby' => 1.0, }, },
- 13. • del.icio.us API ‣ ‣ ‣ 1 0
- 14. • • ‣ Night xNight Lady xLady Snakes 4.5 0.182 0.819 0.222 0.999 Superman 4 0.103 0.412 0.091 0.364 Dupree 1 0.148 0.148 0.4 0.4 0.433 1.379 0.713 1.763 3.185 2.473
- 15. • • ‣ Night xNight Lady xLady Snakes 4.5 0.182 0.819 0.222 0.999 Superman 4 0.103 0.412 0.091 0.364 Dupree 1 0.148 0.148 0.4 0.4 0.433 1.379 0.713 1.763 3.185 2.473
- 16. • • ‣ Night xNight Lady xLady Snakes 4.5 0.182 0.819 0.222 0.999 Superman 4 0.103 0.412 0.091 0.364 Dupree 1 0.148 0.148 0.4 0.4 0.433 1.379 0.713 1.763 3.185 2.473
- 17. (cont.) • ‣ ‣ • ‣ • ‣
- 18. vs • • • • • • • •
- 19. • ‣ ‣ • ‣ ‣ •
- 20. (cont.) • ‣ • ‣ ‣