Search results for "NLP"
showing 10 items of 24 documents
Semantic technologies for industry: From knowledge modeling and integration to intelligent applications
2013
Artificial Intelligence technologies are growingly used within several software systems ranging from Web services to mobile applications. It is by no doubt true that the more AI algorithms and methods are used the more they tend to depart from a pure "AI" spirit and end to refer to the sphere of standard software. In a sense, AI seems strongly connected with ideas, methods and tools that are not (yet) used by the general public. On the contrary, a more realistic view of it would be a rich and pervading set of successful paradigms and approaches. Industry is currently perceiving semantic technologies as a key contribution of AI to innovation. In this paper a survey of current industrial expe…
Supporting Emotion Automatic Detection and Analysis over Real-Life Text Corpora via Deep Learning: Model, Methodology, and Framework
2021
This paper describes an approach for supporting automatic satire detection through effective deep learning (DL) architecture that has been shown to be useful for addressing sarcasm/irony detection problems. We both trained and tested the system exploiting articles derived from two important satiric blogs, Lercio and IlFattoQuotidiano, and significant Italian newspapers.
Propaganda Barometer : A Supportive Tool to Improve Media Literacy Towards Building a Critically Thinking Society
2018
To smartly consume a huge and constantly growing volume of information, to identify fake news and resist propaganda in the context of Information Warfare, to improve personal critical thinking capabilities and increase media literacy, people require supportive environment with sophisticated technology facilitated tools. With rapid development of media, widespread popularity of social networks and fast growing amount of information distribution channels, propaganda and information warfare enter an absolutely new digital technology supported cyber era. Propaganda mining is not a trivial and very time consuming process for human. And, as with any new technology, human need certain time to unde…
Attention-based Model for Evaluating the Complexity of Sentences in English Language
2020
The automation of text complexity evaluation (ATCE) is an emerging problem which has been tackled by means of different methodologies. We present an effective deep learning- based solution which leverages both Recurrent Neural and the Attention mechanism. The developed system is capable of classifying sentences written in the English language by analysing their syntactical and lexical complexity. An accurate test phase has been carried out, and the system has been compared with a baseline tool based on the Support Vector Machine. This paper represents an extension of a previous deep learning model, which allows showing the suitability of Neural Networks to evaluate sentence complexity in tw…
Bilevel heat exchanger network synthesis with an interactive multi-objective optimization method
2012
Abstract Heat exchanger network synthesis (HENS) has been an active research area for more than 40 years because well-designed heat exchanger networks enable heat recovery in process industries in an energy- and cost-efficient manner. Due to ever increasing global competition and need to decrease the harmful effects done on the environment, there still is a continuous need to improve the heat exchanger networks and their synthesizing methods. In this work we present a HENS method that combines an interactive multi-objective optimization method with a simultaneous bilevel HENS method, where the bilevel part of the method is based on grouping of process streams and building aggregate streams …
Luonnollisten kielten kääntäminen ja konekäännös - Taustaa, teoriaa ja menetelmiä
2010
López, Elina I. Tietojärjestelmätieteen kandidaatintutkielma / Elina I. López Jyväskylä: Jyväskylän yliopisto, 2010. 36 s. Luonnollisten kielten kääntäminen on olennainen osa ihmisten elämää, erityi-sesti nykyisessä kansainvälisessä maailmassa. Ilman kääntämistä eivät esimer-kiksi yritykset pysty toimimaan. Käännettävät tekstimassat kuitenkin kasvavat kasvamistaan ja käännöstyön nopeuttamiseksi on haettu apua tietokoneista. Konekääntämistä onkin tutkittu ensimmäisten tietokoneiden käyttöönotosta lähtien. Tässä tutkielmassa käsitellään luonnollisia kieliä, perinteistä kääntämistä ja ko-nekäännöksiä. Tutkielmassa käydään läpi luonnollisten kielten jaotteluita ja ominaisuuksia, jotka tekevät …
Fake News Spreaders Detection: Sometimes Attention Is Not All You Need
2022
Guided by a corpus linguistics approach, in this article we present a comparative evaluation of State-of-the-Art (SotA) models, with a special focus on Transformers, to address the task of Fake News Spreaders (i.e., users that share Fake News) detection. First, we explore the reference multilingual dataset for the considered task, exploiting corpus linguistics techniques, such as chi-square test, keywords and Word Sketch. Second, we perform experiments on several models for Natural Language Processing. Third, we perform a comparative evaluation using the most recent Transformer-based models (RoBERTa, DistilBERT, BERT, XLNet, ELECTRA, Longformer) and other deep and non-deep SotA models (CNN,…
AI for Resource Allocation and Resource Allocation for AI: a two-fold paradigm at the network edge
2022
5G-and-beyond and Internet of Things (IoT) technologies are pushing a shift from the classic cloud-centric view of the network to a new edge-centric vision. In such a perspective, the computation, communication and storage resources are moved closer to the user, to the benefit of network responsiveness/latency, and of an improved context-awareness, that is, the ability to tailor the network services to the live user's experience. However, these improvements do not come for free: edge networks are highly constrained, and do not match the resource abundance of their cloud counterparts. In such a perspective, the proper management of the few available resources is of crucial importance to impr…
Enhancing Attention’s Explanation Using Interpretable Tsetlin Machine
2022
Explainability is one of the key factors in Natural Language Processing (NLP) specially for legal documents, medical diagnosis, and clinical text. Attention mechanism has been a popular choice for such explainability recently by estimating the relative importance of input units. Recent research has revealed, however, that such processes tend to misidentify irrelevant input units when explaining them. This is due to the fact that language representation layers are initialized by pre-trained word embedding that is not context-dependent. Such a lack of context-dependent knowledge in the initial layer makes it difficult for the model to concentrate on the important aspects of input. Usually, th…
McRock at SemEval-2022 Task 4: Patronizing and Condescending Language Detection using Multi-Channel CNN, Hybrid LSTM, DistilBERT and XLNet
2022
In this paper we propose four deep learning models for the task of detecting and classifying Patronizing and Condescending Language (PCL) using a corpus of over 13,000 annotated paragraphs in English. The task, hosted at SemEval-2022, consists of two different subtasks. The Subtask 1 is a binary classification problem. Namely, given a paragraph, a system must predict whether or not it contains any form of PCL. The Subtask 2 is a multi-label classification task. Given a paragraph, a system must identify which PCL categories express the condescension. A paragraph might contain one or more categories of PCL. To face with the first subtask we propose a multi-channel Convolutional Neural Network…