{'fraction_non_alphanumeric': 0.011217948717948718, 'fraction_numerical': 0.0, 'mean_word_length': 5.510416666666667, '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}}
Graph-Based Algorithms for Text Summarization

Summarization is a brief and accurate representation of input text such that the output covers the most important concepts of the source in a condensed manner. Text Summarization is an emerging technique for understanding the main purpose of any kind of documents. To visualize a large text document within a short duration and small visible area like PDA screen, summarization provides a greater flexibility and convenience. This paper presents innovative unsupervised methods for automatic sentence extraction using graph-based ranking algorithms and shortest path algorithm.