{'fraction_non_alphanumeric': 0.020937188434695914, 'fraction_numerical': 0.0, 'mean_word_length': 5.6490066225165565, '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}}
Enhancing Academic Recommendation Regarding Common Coauthors' Publication Records

In this chapter, the authors investigated the feasibility of any improvement in paper recommendation by recommending similar papers to an input paper from the publication record of the first author. Although there are numerous approaches for recommending academic papers, they did not consider intellectually recommending papers based on the publication record of common coauthors. Consequently, they are motivated to introduce a remedy for this shortcoming by recommending scholarly papers based on similarity of textual references to visual features which considers the similarity of text fragments of one's publication record to any of their visual features (i.e., tables and figures). Based on the results of evaluation, the proposed enhancement will increase the mean precision, recall, and accordingly, the F-measure. In addition, it increases the position of the relevant papers in the returned list of documents.