Search · four archives
Search · four archives
18 papers · ranked by Valyu relevance
Michela Assale, Linda Greta Dui, Andrea Cina, Andrea Seveso + 1 more
'Federico Cabitza'] Problem: Clinical practice requires the production of a time- and resource-consuming great amount of notes. They contain relevant information, but their secondary use is almost impossible, due to their unstructured nature. Researchers are trying to address this problems, with traditional and…
Michael Chary, Saumil Parikh, Alex F. Manini, Edward W. Boyer + 1 more
'Michael Radeos'] Natural language processing (NLP) aims to program machines to interpret human language as humans do. It could quantify aspects of medical education that were previously amenable only to qualitative methods. The application of NLP to medical education has been accelerating over the past several years.…
Georgiana Tucudean, Marian Bucos, Bogdan Dragulescu, Catalin Daniel Caleanu + 1 more
'Catalin Daniel Caleanu' 'Maria Navarro-Caceres'] Natural language processing (NLP) tasks can be addressed with several deep learning architectures, and many different approaches have proven to be efficient. This study aims to briefly summarize the use cases for NLP tasks along with the main architectures. This…
Claudio Crema, Giuseppe Attardi, Daniele Sartiano, Alberto Redolfi
Natural language processing (NLP) is rapidly becoming an important topic in the medical community. The ability to automatically analyze any type of medical document could be the key factor to fully exploit the data it contains. Cutting-edge artificial intelligence (AI) architectures, particularly machine learning and…
Anne E. Thessen, Hong Cui, Dmitry Mozzherin
Centuries of biological knowledge are contained in the massive body of scientific literature, written for human-readability but too big for any one person to consume. Large-scale mining of information from the literature is necessary if biology is to transform into a data-driven science. A computer can handle the…
Joshua Conrad Jackson, Joseph Watts, Johann-Mattis List, Curtis Puryear + 2 more
'Curtis Puryear' 'Ryan Drabble' 'Kristen A. Lindquist'] Humans have been using language for millennia but have only just begun to scratch the surface of what natural language can reveal about the mind. Here we propose that language offers a unique window into psychology. After briefly summarizing the legacy of language…
Gunther Eysenbach, Bo Jin, Seongsoon Kim, Yanshan Wang + 6 more
Background Qualitative research methods are increasingly being used across disciplines because of their ability to help investigators understand the perspectives of participants in their own words. However, qualitative analysis is a laborious and resource-intensive process. To achieve depth, researchers are limited to…
Alessandro Lenci, Sebastian Padó
Natural Language Processing (NLP) today-like most of Artificial Intelligence (AI)-is much more of an “engineering” discipline than it originally was, when it sought to develop a general theory of human language understanding that not only translates into language technology, but that is also linguistically meaningful…
Ming Che Lee, Jia Wei Chang, Tung Cheng Hsieh
This paper presents a grammar and semantic corpus based similarity algorithm for natural language sentences. Natural language, in opposition to “artificial language”, such as computer programming languages, is the language used by the general public for daily communication. Traditional information retrieval approaches…
Guido M. Linders, Max M. Louwerse
Most natural language models and tools are restricted to one language, typically English. For researchers in the behavioral sciences investigating languages other than English, and for those researchers who would like to make cross-linguistic comparisons, hardly any computational linguistic tools exist, particularly…
Nicola Angius, Pietro Perconti, Alessio Plebe, Alessandro Acciai
This article provides an epistemological analysis of current attempts of explaining how the relatively simple algorithmic components of neural language models (NLMs) provide them with genuine linguistic competence. After introducing the Transformer architecture, at the basis of most of current NLMs, the paper firstly…
Maxwell J. Farrell, Nicolas Le Guillarme, Liam Brierley, Bronwen Hunter + 4 more
'Bronwen Hunter' 'Daan Scheepens' 'Anna Willoughby' 'Andrew Yates' 'Nicole Mideo'] In ecology and evolutionary biology, the synthesis and modelling of data from published literature are commonly used to generate insights and test theories across systems. However, the tasks of searching, screening, and extracting data…
Reto Gubelmann
Taking Leibniz' ideal of a universal truth-calculating machine as a vantage point, this article provides a philosophically sound analysis of the concept of reasoning in NLP. It argues that reasoning always involves inference, which in turn requires being guided by reason relations. Based on this, the article argues…
Saranlita Chotirat, Phayung Meesad
Question classification is a crucial task for answer selection. Question classification could help define the structure of question sentences generated by features extraction from a sentence, such as who, when, where, and how. In this paper, we proposed a methodology to improve question classification from texts by…
Dario Borrelli, Gabriela Gongora Svartzman, Carlo Lipizzi, Christopher M. Danforth
'Christopher M. Danforth'] Symbolic sequential data are produced in huge quantities in numerous contexts, such as text and speech data, biometrics, genomics, financial market indexes, music sheets, and online social media posts. In this paper, an unsupervised approach for the chunking of idiomatic units of sequential…
Andrea Gasparetto, Alessandro Zangari, Matteo Marcuzzo, Andrea Albarelli + 1 more
Text Classification methods have been improving at an unparalleled speed in the last decade thanks to the success brought about by deep learning. Historically, state-of-the-art approaches have been developed for and benchmarked against English datasets, while other languages have had to catch up and deal with…
Ricky K. Taira, Anders O. Garlid, William Speier, Ilya Safro
Medical natural language processing (NLP) systems are a key enabling technology for transforming Big Data from clinical report repositories to information used to support disease models and validate intervention methods. However, current medical NLP systems fall considerably short when faced with the task of logically…
Philippe Blache
Most architectures and models of language processing have been built upon a restricted view of language, which is limited to sentence processing. These approaches fail to capture one primordial characteristic: efficiency. Many facilitation effects are known to be at play in natural situations such as conversation…