{'fraction_non_alphanumeric': 0.014732965009208104, 'fraction_numerical': 0.0, 'mean_word_length': 6.058441558441558, '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}}
Ontology-supported webpage classifier for scholar’s webpages in ubiquitous information environment

In this most developed and shifting era of Internet, the information of Internet does massively increase. Webpage indexing catalogues or search engines which can help Demanders on information to rapidly and precisely collect Web information on Internet have already become the indispensable and important tools in Internet. How to precisely do Webpage classification that can effectively assist with information searching, the semantic-supported automatic classifiers can provide this mechanism. This paper proposed the ontology-supported Webpage classifier ldquoOntoClassifierrdquo, in which users can input some related documents, under the domain ontology-supported, and then the system can handle and analyze those document contents for actively extracting and computing the domain word frequency to do those documents classification. The preliminary experiment outcomes proved the technology proposed in this paper could really up-rise the precision rate of Webpage classification.