{'fraction_non_alphanumeric': 0.017179023508137433, 'fraction_numerical': 0.0, 'mean_word_length': 4.826315789473684, '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}}
Research on XML Keyword Query Method Based on Semantic

In this paper, we study the problem of effective keyword search over XML documents, Keyword search for smallest lowest common ancestor(SLCA) in XML data has recently been proposed as a meaningful way to identify interesting data nodes in XML data where their sub trees contain an input set of keywords. XML retrieval technology has been concerned widely by information retrieval researchers. XML data contains rich semantic information, but most of query methods can't make full use of the semantic information. There will be missed case if there is no enough semantic information. This paper proposed a new XML keyword query algorithm based on semantic(SKSA) to solve the question above. The algorithm takes full use of the node semantic information based on structural semantic. The same or similar results will be returned to users if there is no the keyword in XML document, which avoids the missed case. The test experiment result on the real XML data sets shows that SKSA has higher recall rate, and can match the user's query intention better.