{'fraction_non_alphanumeric': 0.015366430260047281, 'fraction_numerical': 0.0, 'mean_word_length': 4.6092715231788075, '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}}
Semantic Web Image Search through Manual Annotation

Over years the searches made over web still remains non semantic. The internet media is filled with lot of unstructured data that results this state of non semantic search over web. To make the search more specific over the query given, its attributes are to be defined while the search along with its object name. By defining so the normal web search appears to be semantic. The attributes relevant to the context is made easy over text, audio and video files. Whereas Image files still suffers with its undefined attributes along with the relevant image being uploaded. Moreover the images over web aren‟t tagged yet with relevant attributes in them. JPEG, Bitmap and all other commonly used image supporters yet remain without tags. Only this leads a non semantic search over images on web.