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48 lines
2.1 KiB
48 lines
2.1 KiB
import feature_extraction.lexicons as lexicons
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from utils.constants import REGEX_CONSTANTS
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""" List of supported features for feature extraction from Input String """
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FEATURE_LIST = ['COMPARE', 'CONTRAST', 'RESULT', 'INCREASE', 'CHANGE', 'USE', 'PRESENT',
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'IMPORTANT', 'RESEARCH', 'APPROACH', 'PUBLIC', 'BEFORE', 'BETTER_SOLUTION',
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'PROFESSIONALS', 'MEDICINE', 'MATH', 'COMPUTER_SCIENCE', 'CITATION',
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'ACRONYM', 'CONTAINS_YEAR', 'SEQUENCE', 'REFERENCE', 'PERCENTAGE', 'URL']
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""" Feature Name for Theta Bias -- need to add it to the list of features for all data instances """
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THETA_BIAS_FEATURE = 'THETA_BIAS'
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def extract_features_from_text(text: str):
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"""
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This function takes text string as input, extracts and returns a list of features by checking each word in
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:`~feature_extraction.lexicons.ALL_LEXICONS`
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:param text: takes string text as param
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:return: returns a list of extracted features from the text, empty list for no features
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"""
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# ALL_LEXICONS
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lexicon_dict = lexicons.ALL_LEXICONS
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# Initialize the feature list with Theta Bias feature, this feature must be added to all data instances
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text_feature_list = [THETA_BIAS_FEATURE]
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# Iterate through the list features and get list of words from the lexicon dictionary,
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# for each word in the word list, check if it appears in input text and add it to the text feature list
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for feature in FEATURE_LIST:
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# If the feature is Regex Pattern Match, get the pattern from :`~utils.constants.REGEX_CONSTANTS`
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# and match it with the input text
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if feature in REGEX_CONSTANTS:
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pattern = REGEX_CONSTANTS[feature]
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if bool(pattern.match(text)):
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text_feature_list.append(feature)
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continue
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# If the feature is not Regex Pattern Match, then get the list of dictionary words from lexicon dictionary
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word_list = lexicon_dict[feature]
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for word in word_list:
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if word in text.lower():
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text_feature_list.append(feature)
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break
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return text_feature_list
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