{'fraction_non_alphanumeric': 0.028148148148148148, 'fraction_numerical': 0.0014814814814814814, 'mean_word_length': 4.827586206896552, '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}}
Chinese Information Retrieval Based on Terms and Ontology

In this paper, we describe our approach for single language information retrieval (SLIR) on Chinese language of NTCIR4 tasks. Firstly, we automatically extract terms (short-terms and long terms) from document set and use them to build indexes; secondly, for a query, we use short terms in the query and documents to do initial retrieval; thirdly, we build an ontology for the query to do query expansion and implement second retrieval. Finally, we use long terms to reorder the top N retrieved documents. Experiments show that the method achieves good results for both T-run and D-Run SLIR tasks of Chinese language.