Processing-in-Memory (PiM), which combines a memory device with a Processing Unit (PU) into an integrated chip, has drawn special attention in the field of Artificial Intelligence semiconductors. Currently, in the development and commercialization of...
In this paper we perform a comparative analysis of three models for a feature representation of text documents in the context of document classification. In particular, we consider the most often used family of bag-of-words models, the recently propo...
Document-level sentiment analysis is a challenging task given the large size of the text, which leads to an abundance of words and opinions, at times contradictory, in the same document. This analysis is particularly useful in analyzing press article...
With the growth of online information and sudden expansion in the number of electronic documents provided on websites and in electronic libraries, there is difficulty in categorizing text documents. Therefore, a rule-based approach is a solution to t...
With the exponential increase in information, it has become imperative to design mechanisms that allow users to access what matters to them as quickly as possible. The recommendation system (RS) with information technology development is the solution...
Outliers that deviate from a normal distribution are typically removed during the analysis process. However, the patterns of outliers are recognized as important information in the outlier detection method. This study proposes a technology trend scre...
This article describes a detailed methodology for the A-phase classification of the cyclic alternating patterns (CAPs) present in sleep electroencephalography (EEG). CAPs are a valuable EEG marker of sleep instability and represent an important patte...
In the domain of law and legal systems, jurisprudence principles (JPs) are considered major sources of legislative reasoning by jurisprudence scholars. Generally accepted JPs are often used to support the reasoning for a given jurisprudence case (JC)...
Pornographic and gambling websites become increasingly stubborn via disguising, misleading, blocking, and bypassing, which hinder the construction of a safe and healthy network environment. However, most traditional approaches conduct the detection p...
Currently, as an effect of the COVID-19 pandemic, bioinformatics, genomics, and biological computations are gaining increased attention. Genomes of viruses can be represented by character strings based on their nucleobases. Document similarity metric...
Document-level Sentiment Analysis is a complex task that implies the analysis of large textual content that can incorporate multiple contradictory polarities at the phrase and word levels. Most of the current approaches either represent textual data...
Japanese medical device adverse events terminology, published by the Japan Federation of Medical Devices Associations (JFMDA terminology), contains entries for 89 terminology items, with each of the terminology entries created independently. It is ne...
To effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks s...
Email is the most common and effective source of communication for most enterprises and individuals. In the corporate sector the volume of email received daily is significant while timely reply of each email is important. This generates a huge amount...
Gathering useful insights from social media data has gained great interest over the recent years. User representation can be a key task in mining publicly available user-generated rich content offered by the social media platforms. The way to automat...
This paper aims to enhance the Graphical Set-based model (GSB) for ranking and classification tasks by incorporating node and word embeddings. The model integrates a textual graph representation with a set-based model for information retrieval. Initi...
The rise in the use of social media networks has increased the prevalence of cyberbullying, and time is paramount to reduce the negative effects that derive from those behaviours on any social media platform. This paper aims to study the early detect...
Online conversation communities have become an influential source of consumer recommendations in recent years. We propose a set of meaningful user segments which emerge from user embedding representations, based exclusively on comments’ text in...
Paraphrase detection is important for a number of applications, including plagiarism detection, authorship attribution, question answering, text summarization, text mining in general, etc. In this paper, we give a performance overview of various type...
This article presents a comprehensive evaluation of traditional machine learning and deep learning models in analyzing sentiment trends within the SENT-COVID Twitter corpus, curated during the COVID-19 pandemic. The corpus, filtered by COVID-19 relat...
Nowadays, predicting customer churn is essential for the success of any company. Loyal customers generate continuous revenue streams, resulting in long-term success and growth. Moreover, companies are increasingly prioritizing the retention of existi...
It is widely considered that unlicensed taxis pose a risk to public safety and interfere with the effective management of traffic. Significant human and material resources are expended by traffic control departments to locate these vehicles with limi...
Social media makes it easy for individuals to publish and consume news, but it also facilitates the spread of rumors. This paper proposes a novel deep recurrent neural model with a symmetrical network architecture for automatic rumor detection in soc...
This study aims to explore the time series context and sentiment polarity features of rumors’ life cycles, and how to use them to optimize the CNN model parameters and improve the classification effect. The proposed model is a convolutional neural ne...
Personality is a fundamental psychological trait that exerts a long-term influence on human behavior patterns and social interactions. Automatic personality recognition (APR) has exhibited increasing importance across various domains, including Human...
This paper analyses the capabilities of different techniques to build a semantic representation of educational digital resources. Educational digital resources are modeled using the Learning Object Metadata (LOM) standard, and these semantic represen...
Traditional TRIZ theory provides methods and processes for systematic analysis on engineering problems, which can improve the efficiency of solving problems. However, the effect of solving problems is not necessarily guaranteed, and depends on the us...
User preference mining uses rating data, item content or comments to learn additional knowledge to support the prediction task. For the use of rating data, the usual approach is to take rating matrix as data source, and collaborative filtering as the...
There are several possibilities to improve classification in natural language processing tasks. In this article, we focused on the issue of coreference resolution that was applied to a manually annotated dataset of true and fake news. This dataset wa...
One of the most significant graph data analysis tasks is graph classification, as graphs are complex data structures used for illustrating relationships between entity pairs. Graphs are essential in many domains, such as the description of chemical m...
The rapid development of social networking platforms in recent years has made it possible for scholars to find partners who share similar research interests. Nevertheless, this task has become increasingly challenging with the dramatic increase in th...
Aligned with global Sustainable Development Goals (SDGs) and multidisciplinary approaches integrating AI with sustainability, this research introduces an innovative AI framework for analyzing Modern French Poetry. It applies feature extraction techni...
The Manufacturing Message Specification (MMS) protocol is frequently used to automate processes in IEC 61850-based substations and smart-grid systems. However, it may be susceptible to a variety of cyber-attacks. A frequently used protection strategy...
In the context of a new wave of scientific and technological revolution and industrial transformation, this study proposes an emerging technology identification framework that integrates a High-Value Patent Knowledge Graph with Social Network Analysi...
In recent years, deep learning has been applied to the field of recommendation, which can learn complex user interaction features and make better recommendations. However, deep learning only focuses on the interaction of high-order features and negle...
With the development of the Internet, the oversight of research integrity issues has extended beyond the scientific community to encompass the whole of society. If these issues are not addressed promptly, they can significantly impact the research cr...
In this study, based on a morpheme segmentation framework, we researched a text keyword extraction method for Uyghur, Kazakh and Kirghiz languages, which have similar grammatical and lexical structures. In these languages, affixes and a stem are join...
Various modern Chinese poetry styles have influenced the development of new Chinese poetry; therefore, the classification of poetry style is very important for understanding these poems and promoting education regarding new Chinese poetry. For poetry...
Recently, business sectors have focused on offering a wide variety of services through utilizing different modern technologies such as super apps in order to fulfill customers’ needs and create a satisfactory user experience. Accordingly, study...
Long non-coding RNA (LncRNA) and microRNA (miRNA) are both non-coding RNAs that play significant regulatory roles in many life processes. There is cumulating evidence showing that the interaction patterns between lncRNAs and miRNAs are highly related...