function recommender_similarity_classical in Recommender API 6.2

Same name and namespace in other branches

1. 5 recommender.module \recommender_similarity_classical()
2. 6 recommender.module \recommender_similarity_classical()

classical collaborative filtering algorithm based on correlation coefficient. could be used in the classical user-user or item-item algorithm see the README file for more details

Parameters

$app_name the application name that uses this function.:

$table_name the input table name, don't use {tablename} here because it'll get expanded later:

$field_mouse the input table field for mouse:

$field_cheese the input table field for cheese:

$field_weight the input table field weight:

$options an array of options: 'performance': whether to do calculation in memory or in database. 'auto' is to decide automatically. 'missing': how to handle missing data -- 'none' do nothing; 'zero' fill in missing data with zero; 'adjusted' skip mice that don't share cheese in common. 'sensitivity': if similarity is smaller enough to be less than a certain value (sensitivity), we just discard those

Return value

null {recommender_similarity} will be filled with similarity data

File

./recommender.module, line 27

Code

function recommender_similarity_classical($app_name, $table_name, $field_mouse, $field_cheese, $field_weight, $options = array()) {
  $recommender = new CorrelationRecommender($app_name, $table_name, $field_mouse, $field_cheese, $field_weight, $options);
  $recommender
    ->computeSimilarity();
}