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The widespread use of social media has led to the rapid generation of opinion-rich short texts, posing increasingly complex and high-variance challenges for public discourse analysis. These texts are typically informal, ...

This paper addresses the growing need for implementing intelligent Natural Language Processing (NLP) systems on low-power, memory-limited devices such as Raspberry Pi, mobile phones, and IoT edge hardware. As edge comput...

Graph-based text classification has become an effective paradigm for modeling corpus-level structure, particularly under limited supervision. However, most existing approaches rely on document–word representations...

IntroductionThe complex interplay between environmental dynamics, biodiversity loss, and public health necessitates advanced methodologies for quantifying and interpreting their interactions. Respiratory health, highly s...

The increasing growth of documents available in the World Wide Web has resulted in a difficult situation for those end-users who search for a particular piece of information. A common approach to facilitate search is to ...

Document classification has already been widely studied. In fact, some studies compared feature selection techniques or feature space transformation whereas some others compared the performance of different algorithms. R...

The objective of this study was to characterize the wooden breast (WB) myopathy in the poultry industry, and establish degrees of severity by analyzing the composition and important characteristics of meat quality. 175 c...

With the improvement of communication speeds and the spread of smartphones and IoT devices, there is an abundance of sports video content on the Internet, and users can watch game broadcasts and highlight videos without ...

Abstract Precise extraction of medical phenotypes and entities from electronic health record (EHR) text is vital for numerous clinical research tasks, including cohort classification, tracking temporal patterns in diseas...

Abstract Understanding human emotions across multiple modalities such as text and images, is increasingly important for applications including content personalization, social media analysis, and Human–Computer Interact...

A number of texture classification approaches have been developed in the past but most of these studies target graylevel textures. In this work, novel results are presented on Neural Network based classification of color...

Texture is one of the important characteristics used in identifying objects or regions of interest in an image, whether the image be a photomicrograph, an aerial photograph, or a satellite image. This paper describes som...

Subjects / keywords: Pattern recognition (psychology); Artificial intelligence; Texture (cosmology); Computer science; Feature (linguistics); Sample (material); Image (mathematics); Chromatography; Philosophy; Linguistics; Chemistry

Presents a theoretically very simple, yet efficient, multiresolution approach to gray-scale and rotation invariant texture classification based on local binary patterns and nonparametric discrimination of sample and prot...

Subjects / keywords: JOHANNSEN, ALBERT; THE UNIVERSITY OF CHICAGO PRESS; 552.1 J65d2

In arid and semiarid areas, the interplant spaces are usually covered by physical and biological soil crusts. These crusts, though representing an almost negligible portion of the soil profile, have a number of crucial r...

It is estimated that approximately 80% of all data gathered by companies are text documents. This article is devoted to one of the most common problems in text mining, i.e. text classification in sentiment analysis, whic...

The development of artificial intelligence (AI) technology, especially large language models like ChatGPT, presents challenges related to the authenticity and validity of digital content. AI's ability to produce human-li...

This study examines public sentiment toward Indonesia’s Constitutional Court (Mahkamah Konstitusi, MK) following its 2024 regional election ruling. Using sentiment analysis and Martin and White’s (2005) Appraisal The...

We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian model, in which each item of a collection ...

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date ...

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date ...

Both The functionality and the non-functionality for what the system does as well as doesn't of software systems requirements are documented in a Software Requirements Specification (SRS). Moreover in requirements engin...

Abstract Quality defects in substandard medicines represent a threat to public health. Rapid and accurate identification of these defects is critical to prioritise the cases and implement regulatory measures. However, th...