def __init__(self): config_loader = Config_loader('config.ini') self.config = config_loader.load_config() reverse_index_builder = Reverse_index_builder( ponderation_method=self.config['Reverse_index']['ponderation'], index_type=self.config['Reverse_index']['index_type'], save_folder_path=self.config['Reverse_index']['save_folder_path']) self.reverse_index = reverse_index_builder.create_reverse_index( 'sources/cacm.all', 'sources/common_words') self._lauch_engine()
def __init__(self): config_loader = Config_loader('config.ini') self.config = config_loader.load_config() reverse_index_builder = Reverse_index_builder( ponderation_method=self.config['Reverse_index']['ponderation'], index_type=self.config['Reverse_index']['index_type'], save_folder_path=self.config['Reverse_index']['save_folder_path'] ) self.reverse_index = reverse_index_builder.create_reverse_index('sources/cacm.all', 'sources/common_words') self._lauch_engine()
def __init__(self, queries_filename, answers_filename): config_loader = Config_loader('config.ini') self.config = config_loader.load_config() self.queries_filename = queries_filename self.answers_filename = answers_filename self.ponderation_method = self.config['Reverse_index']['ponderation'] self.beta = self.config['Measures']['beta'] self.alpha = 1. / (1 + self.beta ** 2) if self.config['Research_engine']['type'] == 'vectorial': self.similarity_method = self.config['Vectorial_search']['similarity'] elif self.config['Research_engine']['type'] == 'boolean': self.p_norm = self.config['Boolean_search']['p_norm'] self.default_similarity = self.config['Boolean_search']['default_similarity'] elif self.config['Research_engine']['type'] == 'probabilistic': self.rsv_relevant_method = self.config['Probabilistic_search']['rsv_relevant_method'] self.lines = []