{'fraction_non_alphanumeric': 0.017543859649122806, 'fraction_numerical': 0.007017543859649123, 'mean_word_length': 5.344444444444444, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Toward an improved concept-based information retrieval system

This paper presents a novel information retrieval system that includes 1) the addition of concepts to facilitate the identification of the correct word sense, 2) a natural language query interface, 3) the inclusion of weights and penalties for proper nouns that build upon the Okapi weighting scheme, and 4) a term clustering technique that exploits the spatial proximity of search terms in a document to further improve the performance. The effectiveness of the system is validated by experimental results.