Document Processing Using Machine Learning aims at presenting a handful of resources for students and researchers working in the document image analysis (DIA) domain using machine learning since it covers multiple document processing problems. Starting with an explanation of how Artificial Intelligence (AI) plays an important role in this domain, the book further discusses how different machine learning algorithms can be applied for classification/recognition and clustering problems regardless the type of input data: images or text. In brief, the book offers comprehensive coverage of the most essential topics, including: * The role of AI for document image analysis * Optical character recognition * Machine learning algorithms for document analysis * Extreme learning machines and their applications * Mathematical foundation for Web text document analysis * Social media data analysis * Modalities for document dataset generation This book serves both undergraduate and graduate scholars in Computer Science/Information Technology/Electrical and Computer Engineering. Further, it is a great fit for early career research scientists and industrialists in the domain.

This book constitutes the proceedings of the 14th International Conference on Computational Processing of the Portuguese Language, PROPOR 2020, held in Evora, Portugal, in March 2020. The 36 full papers presented together with 5 short papers were carefully reviewed and selected from 70 submissions. They are grouped in topical sections on speech processing; resources and evaluation; natural language processing applications; semantics; natural language processing tasks; and multilinguality.

This book constitutes the refereed proceedings of the 7th International Conference of the CLEF Initiative, CLEF 2016, held in Toulouse, France, in September 2016. The 10 full papers and 8 short papers presented together with 5 best of the labs papers were carefully reviewed and selected from 36 submissions. In addition to these talks, this volume contains the results of 7 benchmarking labs reporting their year long activities in overview talks and lab sessions. The papers address all aspects of information access in any modality and language and cover a broad rangeof topics in the fields of multilingual and multimodal information access evaluation.