Part-of-Speech (POS) tagging is one of the most important tasks in the field of natural language processing (NLP). POS tagging for a word depends not only on the word itself but also on its position, its surrounding words, and their POS tags. POS tag...
Various research approaches have attempted to solve the length difference problem between the surface form and the base form of words in the Korean morphological analysis and part-of-speech (POS) tagging task. The compound POS tagging method is a pop...
Uyghur is an agglutinative and a morphologically rich language; natural language processing tasks in Uyghur can be a challenge. Word morphology is important in Uyghur part-of-speech (POS) tagging. However, POS tagging performance suffers from error p...
The assessment of Chinese text readability plays a significant role in Chinese language education. Due to the intrinsic differences between alphabetic languages and Chinese character representations, the readability assessment becomes more challengin...
Linguistic tasks such as Part-of-Speech (PoS) tagging can be tedious, but are crucial for the development of Natural Language Processing (NLP) tools. Games With A Purpose (GWAPs) aim to reduce the monotony of the task for native speakers and non-expe...
Chinese Medical Named Entity Recognition (Chinese-MNER) aims to identify potential entities and their categories from the unstructured Chinese medical text. Existing methods for this task mainly incorporate the dictionary knowledge on the basis of tr...
With the development of the Internet, the issue of cyberbullying on social media has gained significant attention. Cyberbullying is often expressed in text. Methods of identifying such text via machine learning have been growing, most of which rely o...
Transformer-based image captioning models have recently achieved remarkable performance by using new fully attentive paradigms. However, existing models generally follow the conventional language model of predicting the next word conditioned on the v...
It is highly significant from a research standpoint and a valuable practice to identify diseases, symptoms, drugs, examinations, and other medical entities in medical text data to support knowledge maps, question and answer systems, and other downstr...
To address the cost and efficiency issues of manually analysing requirement dependency in requirements engineering, a requirement dependency extraction method based on part-of-speech features and an improved stacking ensemble learning model (P-Stacki...
Natural language processing (NLP) has numerous applications and has been extensively developed in deep learning. In recent years, language models such as Transformer, BERT, and GPT have frequently been the foundation for related research. However, re...
In this work, we propose a novel priors-based attention neural network (PANN) for image captioning, which aims at incorporating two kinds of priors, i.e., the probabilities being mentioned for local region proposals (PBM priors) and part-of-speech cl...
Neural machine translation models are guided by loss function to select source sentence features and generate results close to human annotation. When the data resources are abundant, neural machine translation models can focus on the features used to...
Many natural language processing architectures are greatly affected by seemingly small design decisions, such as batching and curriculum learning (how the training data are ordered during training). In order to better understand the impact of these d...
Ainu is a critically endangered language spoken by the native inhabitants of northern Japan. This paper describes our research aimed at the development of technology for automatic processing of text in Ainu. In particular, we improved the existing to...
The creation of linguistic resources is crucial to the continued growth of research and development efforts in the field of natural language processing, especially for resource-scarce languages. In this paper, we describe the curation and annotation...
The statistical machine translation for the Arabic language integrates external linguistic resources such as part-of-speech tags. The current research presents a Bidirectional Long Short-Term Memory (Bi-LSTM)—Conditional Random Fields (CRF) seg...
Processing of social media text like tweets is challenging for traditional Natural Language Processing (NLP) tools developed for well-edited text due to the noisy nature of such text. However, demand for tools and resources to correctly process such...
We introduce DeReKoGram, a novel frequency dataset containing lemma and part-of-speech (POS) information for 1-, 2-, and 3-grams from the German Reference Corpus. The dataset contains information based on a corpus of 43.2 billion tokens and is divide...
Gold standard corpora (GSCs) are essential for the supervised training and evaluation of systems that perform natural language processing (NLP) tasks. Currently, most of the resources used in biomedical NLP tasks are mainly in English. Little effort...
Semantic ontologies have been widely utilized as crucial tools within natural language processing, underpinning applications such as knowledge extraction, question answering, machine translation, text comprehension, information retrieval, and text su...
With the recent evolution of deep learning, machine translation (MT) models and systems are being steadily improved. However, research on MT in low-resource languages such as Vietnamese and Korean is still very limited. In recent years, a state-of-th...
Text vectorization is the basic work of natural language processing tasks. High-quality vector representation with rich feature information can guarantee the quality of entity recognition and other downstream tasks in the field of traditional Chinese...
Part of Speech (POS) tagging is one of the most common techniques used in natural language processing (NLP) applications and corpus linguistics. Various POS tagging tools have been developed for Arabic. These taggers differ in several aspects, such a...
This study presents a new dataset for fake news analysis and detection, namely, the PolitiFact-Oslo Corpus. The corpus contains samples of both fake and real news in English, collected from the fact-checking website PolitiFact.com. It grew out of a n...
Part-of-speech (POS) tagging in low-resource, morphologically rich languages (LRLs/MRLs) remains challenging due to extensive affixation, high out-of-vocabulary (OOV) rates, and pervasive polysemy. We propose MRL-POS, a unified Transformer-CRF framew...
The automatic construction of learners’ dictionaries requires robust methods for identifying non-literal word combinations, or collocations, which represent a significant challenge for second-language (L2) learners. This paper addresses the cri...
For most automatic speech recognition systems, many unacceptable hypothesis errors still make the recognition results absurd and difficult to understand. In this paper, we introduce the grammar information to improve the performance of the grammatica...
In a setting where multiple automatic annotation approaches coexist and advance separately but none completely solve a specific problem, the key might be in their combination and integration. This paper outlines a scalable architecture for Part-of-Sp...
Software clones are code fragments with similar or nearly similar functionality or structures. These clones are introduced in a project either accidentally or deliberately during software development or maintenance process. The presence of clones pos...
This study investigates the distributions of word classes in English speeches made in the European Parliament and their German (written) translations and simultaneous interpretations. For comparison, a sample of original German speeches and a selecti...
In the low signal-to-noise ratio region, a large number of bit errors occur, and it may exceed the channel error correction capability of the receiver. Traditional communication system may use the technology of automatic repeat-request to deal with t...
Understanding the public’s diverse linguistic expressions about rainfall and flood provides a basis for flood disaster studies and enhances linguistic and cultural awareness. However, existing research tends to overlook linguistic complexity, p...
Language development is inextricably linked to the development of fundamental human abilities. A language problem can result from abnormal language development in childhood, which has a severe impact on other elements of life. As a result, early trea...
(1) Background: Information overload challenges decision-making in the Industry 4.0 era. While Natural Language Processing (NLP), especially Automatic Text Summarization (ATS), offers solutions, issues with factual accuracy persist. This research bri...
In the derived approach, an analysis is performed on Twitter data for World Cup soccer 2014 held in Brazil to detect the sentiment of the people throughout the world using machine learning techniques. By filtering and analyzing the data using natural...
In highly sophisticated network attacks, command-and-control (C&C) servers always use domain generation algorithms (DGAs) to dynamically produce several candidate domains instead of static hard-coded lists of IP addresses or domain names. Disting...
Aspect-based sentiment analysis is a fine-grained task where the key goal is to predict sentiment polarities of one or more aspects in a given sentence. Currently, graph neural network models built upon dependency trees are widely employed for aspect...
The purpose of this paper is to address the extraction of entities and relationships from unstructured Chinese text, with a particular emphasis on the challenges of Named Entity Recognition (NER) and Relation Extraction (RE). This will be achieved by...
A microblog is a new type of social media for information publishing, acquiring, and spreading. Finding the significant topics of a microblog is necessary for popularity tracing and public opinion following. This paper puts forward a method to detect...
Wide adoption of social media has caused an explosion of information stored online, with the majority of that information containing subjective, opinionated, and emotional content produced daily by users. The field of emotion analysis has helped effe...
Manufacturing industry faces increasing complexity in the performance of assembly tasks due to escalating demand for complex products with a greater number of variations. Operators require robust assistance systems to enhance productivity, efficiency...
This study analyzes the relationship between the degrees of resemblance and distances between dialects based on several dialectological atlases. This analysis investigates various correspondence data with respect to total valid data in setting refere...
Due to the constantly evolving social media and different types of sources of information, we are facing different fake news and different types of misinformation. Currently, we are working on a project to identify applicable methods for identifying...
The promised dataset was obtained from daily Turkish words and phrases pronounced by various people in videos posted on YouTube. The purpose of compiling the dataset was to provide a method for the detection of the spoken word by recognizing patterns...
In pursuing the mapping between syntax and phonology/prosody, little attention has been paid to the kinds of syntactic information that can affect prosody. In this paper, we explore Japanese downstep, a process in phrasal phonology. What syntactic in...
This study presents a comprehensive NLP infrastructure for Modern Greek that bridges grammatical analysis and ontological representation, integrating linguistic theory, algorithmic modeling, and semantic structuring within a unified computational fra...
Similar text fragments extraction from weakly formalized data is the task of natural language processing and intelligent data analysis and is used for solving the problem of automatic identification of connected knowledge fields. In order to search s...
Arabic natural language processing (NLP) has garnered significant attention in recent years due to the growing demand for automated text and Arabic-based intelligent systems, in addition to digital transformation in the Arab world. However, the uniqu...
In the context of the BiblIndex project, which is an online index of biblical textual reuses by the Church Fathers, intrabiblical intertextuality must be considered to better understand the underlying basis of the Church Fathers’ thought. This...
of 8