Search results for "Language Processing"

Stroke Cognitive Medical Assistant (StrokeCMA)

2018

Stroke is the number two killer after heart disease since it is responsible for almost 10% of all deaths worldwide. The main problem with a stroke is a significant delay in treatment that happened mainly due to inappropriate detection of stroke symptoms or inability of a person to perform further necessary actions, and might cause death, permanent disabilities, as well as more expensive treatment and rehabilitation. Nowadays assessment of a stroke is done by human, following widely adopted FAST approach of stroke assessment. Since a human factor become one of the causes of treatment delay, offered solution will try to minimize this factor. Artificial Intelligence, Cognitive Computing, Machi…

Part-of-speech labeling for Reuters database

2015

Even if the Vector Space Model used for document representation in information retrieval systems integrates a small quantity of knowledge it continues to be used due to its computational cost, speed execution and simplicity. We try to improve this document representation by adding some syntactic information such as the parts of speech. In this paper, we have evaluated three different tagging algorithms in order to select the most suitable tagger for using it to tag the Reuters dataset. In this work, we have evaluated the taggers using only five different parts of speech: noun, verb, adverb, adjective and others. We considered these particular tags being the most representative for describin…

Is VIRTU4L larger than VIR7UAL? Automatic processing of number quantity and lexical representations in leet words.

2015

Recent research has shown that leet words (i.e., words in which some of the letters are replaced by visually similar digits; e.g., VIRTU4L) can be processed as their base words without much cost. However, it remains unclear whether the digits inserted in leet words are simply processed as letters or whether they are simultaneously processed as numbers (i.e., in terms of access to their quantity representation). To address this question, we conducted two experiments that examined the size congruity effect (i.e., when comparisons of the physical size of numbers are affected by their numerical magnitudes) in a physical-size judgment task. Participants were presented with pairs of leet words th…

Correction to: Formalizing Natural Languages with NooJ 2018 and Its Natural Language Processing Applications

2019

Multi-system machine translation using online APIs for English-Latvian

2015

This paper describes a hybrid machine translation (HMT) system that employs several online MT system application program interfaces (APIs) forming a MultiSystem Machine Translation (MSMT) approach. The goal is to improve the automated translation of English – Latvian texts over each of the individual MT APIs. The selection of the best hypothesis translation is done by calculating the perplexity for each hypothesis. Experiment results show a slight improvement of BLEU score and WER (word error rate).

Eye Movement Analyses for Obtaining Readability Formula for Latvian Texts for Primary School

2017

To determine the difficulty of text, readability formulas can be used. The research was made to find readability formula for Latvian. Readability formulas for English were used as guidelines. The novelty was the use of eye movement tracking during reading to obtain quantitative data that lead to readability formula. Eye fixation durations were gathered during readability measurements. Average values of fixation durations were calculated to characterize texts and readers. 15 texts with various difficulty levels were composed for exposing them to readers. More than 300 children of grades 1 - 4 were participating in measurements. Average values of eye fixation durations of readers from a certa…

Overview of the Evalita 2014 SENTIment POLarity Classification Task

2014

International audience; English. The SENTIment POLarity Classification Task (SENTIPOLC), a new shared task in the Evalita evaluation campaign , focused on sentiment classification at the message level on Italian tweets. It included three subtasks: subjectivity classification, polarity classification, and irony detection. SENTIPOLC was the most participated Evalita task with a total of 35 submitted runs from 11 different teams. We present the datasets and the evaluation methodology, and discuss results and participating systems. Italiano. Descriviamo modalit a e risultati della campagna di valutazione di sistemi di sentiment analysis (SENTIment POLarity Classification Task), proposta per la …

Enriching Didactic Similarity Measures of Concept Maps by a Deep Learning Based Approach

2021

Concept maps are significant tools able to support several tasks in the educational area such as curriculum design, knowledge organization and modeling, students' assessment and many others. They are also successfully used in learning activities in which students have to represent domain knowledge according to teacher's assignment. In this context, the development of Learning Analytics approaches would benefit of methods that automatically compare concept maps. Detecting concept maps similarities is relevant to identify how the same concepts are used in different knowledge representations. Algorithms for comparing graphs have been extensively studied in the literature, but they do not appea…

Scatter Search and Local NLP Solvers: A Multistart Framework for Global Optimization

2007

The algorithm described here, called OptQuest/NLP or OQNLP, is a heuristic designed to find global optima for pure and mixed integer nonlinear problems with many constraints and variables, where all problem functions are differentiable with respect to the continuous variables. It uses OptQuest, a commercial implementation of scatter search developed by OptTek Systems, Inc., to provide starting points for any gradient-based local solver for nonlinear programming (NLP) problems. This solver seeks a local solution from a subset of these points, holding discrete variables fixed. The procedure is motivated by our desire to combine the superior accuracy and feasibility-seeking behavior of gradie…

Combining a context aware neural network with a denoising autoencoder for measuring string similarities

2020

Abstract Measuring similarities between strings is central for many established and fast-growing research areas, including information retrieval, biology, and natural-language processing. The traditional approach to string similarity measurements is to define a metric with respect to a word space that quantifies and sums up the differences between characters in two strings; surprisingly, these metrics have not evolved a great deal over the past few decades. Indeed, the majority of them are still based on making a simple comparison between character and character distributions without considering the words context. This paper proposes a string metric that encompasses similarities between str…