Academic Articles & Research Papers

SNPPhenA: a corpus for extracting ranked associations of single-nucleotide polymorphisms and phenotypes from literature

Abstract Background Single Nucleotide Polymorphisms (SNPs) are among the most important types of genetic variations influencing common diseases and phenotypes. Recently, some corpora and methods have been developed with the purpose of extra...

Examining Rural and Urban Sentiment Difference in COVID-19–Related Topics on Twitter: Word Embedding–Based Retrospective Study

BackgroundBy the end of 2022, more than 100 million people were infected with COVID-19 in the United States, and the cumulative death rate in rural areas (383.5/100,000) was much higher than in urban areas (280.1/100,000). As the pandemic s...

Multi-label classification of fundus images based on graph convolutional network

Abstract Background Diabetic Retinopathy (DR) is the most common and serious microvascular complication in the diabetic population. Using computer-aided diagnosis from the fundus images has become a method of detecting retinal diseases, but...

Big Data Major Security Issues: Challenges and Defense Strategies

Big data has unlocked the door to significant advances in a wide range of scientific fields, and it has emerged as a highly attractive subject both in the world of academia and in business as a result. It has also made significant contribut...

A search for $t\bar{t}$ resonances with the ATLAS detector in 2.05 fb−1 of proton-proton collisions at $\sqrt{s} = 7~\mathrm{TeV}$

Abstract A search for top quark pair resonances in final states containing at least one electron or muon has been performed with the ATLAS experiment at the CERN Large Hadron Collider. The search uses a data sample corresponding to an integ...

Approaching quantum computing

1 Preface 2 Introduction 2.1 Computing and the Laws of Physics 2.2 Quantum Information 2.3 Quantum Computers 2.4 The Wave and the Corpuscular Nature of Light 2.5 Deterministic versus Probabilistic Photon Behavior 2.6 State Description, Supe...

Neural Network Methods for Natural Language Processing

Deep learning has attracted dramatic attention in recent years, both in academia and industry. The popular term deep learning generally refers to neural network methods. Indeed, many core ideas and methods were born years ago in the era of ...

Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08

Welcome to the 2008 Conference on Empirical Methods in Natural Language Processing! The conference is organized under the auspices of SIGDAT, the ACL Special Interest Group for linguistic data and corpus-based approaches to natural language...

New trends in natural language processing: statistical natural language processing.

The field of natural language processing (NLP) has seen a dramatic shift in both research direction and methodology in the past several years. In the past, most work in computational linguistics tended to focus on purely symbolic methods. R...

Modeling Climate Change Issues in Indonesia Based on Media Headlines

Climate change has become a global issue affecting all countries in the last decades. This phenomenon poses a concern to Indonesia as it is one of the climate change’s epicenters. Various studies have shown that climate change can harm mult...

Carcinoma In Situ Skip Lesions of the Uterine Corpus in Cervical Squamous Cell Carcinoma: Impact on Target Setting in Radiotherapy.

Self-Repair and Language Selection in Bilingual Speech Processing

In psycholinguistic research the exact level of language selection in bilingual lexical access is still controversial and current models of bilingual speech production offer conflicting statements about the mechanisms and location of langua...

A Pattern Dictionary for Natural Language Processing

Résumé Cet article passe en revue de façon succincte trois des ressources principales utilisées actuellement pour la désambiguïsation lexicale (WordNet, FrameNet et les classes de Levin), et propose une approche alternative, en prenant comm...

Python Natural Language Processing

Leverage the power of machine learning and deep learning to extract information from text dataAbout This BookImplement Machine Learning and Deep Learning techniques for efficient natural language processingGet started with NLTK and implemen...

Neither Telling nor Describing. Reflective Passages and Perceived Reflectiveness 1700–1945

The paper analyses within-fiction reflections in 250 years of literary history. To this end, we formalised the concept of “reflective passage”, demonstrate how our annotation categories are deduced from literary theory and derive three subp...

Indikatoren für Verstehen, Missverstehen und Nichtverstehen

This paper discusses understanding, misunderstanding and not-understanding of German dialect expressions. Reactions indicating understanding, misunderstanding and not-understanding in discourse are listed and examples from a medical corpus,...

A comparative empirical evaluation of semantic clustering algorithms on static word embeddings

Objective: This study conducts a comprehensive empirical evaluation of semantic clustering algorithms to identify the most effective approach for automatically organizing and extracting meaning from textual data. By systematically comparing...

Machine Unlearning: A Perspective, Taxonomy, and Benchmark Evaluation

Machine Learning (ML) models trained on large-scale datasets learn useful predictive patterns, but they may also memorize undesired information, leading to risks such as information leakage, bias, copyright violations, and privacy attacks. ...

Distributional Memory: A General Framework for Corpus-Based Semantics

Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing - EMNLP '06

We are delighted to introduce the proceedings of the 11th Conference on Empirical Methods in Natural Language Processing, organized under the auspices of SIGDAT, the ACL Special Interest Group for linguistic data and corpus-based approaches...