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Kirill Tyshchuk, Polina Karpikova, Andrew Spiridonov, Anastasiia Prutianova, Anton Razzhigaev and Alexander Panchenko
Embeddings, i.e., vector representations of objects, such as texts, images, or graphs, play a key role in deep learning methodologies nowadays. Prior research has shown the importance of analyzing the isotropy of textual embeddings for transformer-based ...
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Xiu Li, Aron Henriksson, Martin Duneld, Jalal Nouri and Yongchao Wu
Educational content recommendation is a cornerstone of AI-enhanced learning. In particular, to facilitate navigating the diverse learning resources available on learning platforms, methods are needed for automatically linking learning materials, e.g., in...
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Cunxiang Xie, Limin Zhang and Zhaogen Zhong
In practical application, there are different knowledge graphs in different fields, such as financial graph, commodity graph, medical graph, and so on. Entity alignment technique can be applied to the fusion of multiple knowledge graphs in different doma...
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Erasmo Purificato, Sabine Wehnert and Ernesto William De Luca
In the age of digital information, where the internet and social networks, as well as personalised systems, have become an integral part of everyone?s life, it is often challenging to be aware of the amount of data produced daily and, unfortunately, of t...
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Simone Leonardi, Diego Monti, Giuseppe Rizzo and Maurizio Morisio
Intelligent agents have the potential to understand personality traits of human beings because of their every day interaction with us. The assessment of our psychological traits is a useful tool when we require them to simulate empathy. Since the creatio...
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Cristian Cardellino, Laura Alonso Alemany
Pág. 67 - 81
This work explores the use of word embeddings as features for Spanish verb sense disambiguation (VSD). This type of learning technique is named disjoint semisupervised learning: an unsupervised algorithm (i.e. the word embeddings) is trained on unl...
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Shengyu Liu, Buzhou Tang, Qingcai Chen and Xiaolong Wang
Semantic features are very important for machine learning-based drug name recognition (DNR) systems. The semantic features used in most DNR systems are based on drug dictionaries manually constructed by experts. Building large-scale drug dictionaries is ...
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Florin Leon, Marius Gavrilescu, Sabina-Adriana Floria and Alina Adriana Minea
This paper proposes a classification methodology aimed at identifying correlations between job ad requirements and transversal skill sets, with a focus on predicting the necessary skills for individual job descriptions using a deep learning model. The ap...
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Carlo Galli, Nikolaos Donos and Elena Calciolari
Systematic reviews are cumbersome yet essential to the epistemic process of medical science. Finding significant reports, however, is a daunting task because the sheer volume of published literature makes the manual screening of databases time-consuming....
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Rongsheng Li, Jin Xu, Zhixiong Cao, Hai-Tao Zheng and Hong-Gee Kim
In the realm of large language models (LLMs), extending the context window for long text processing is crucial for enhancing performance. This paper introduces SBA-RoPE (Segmented Base Adjustment for Rotary Position Embeddings), a novel approach designed...
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Olga Kurasova, Arnoldas Bud?ys and Viktor Medvedev
As artificial intelligence has evolved, deep learning models have become important in extracting and interpreting complex patterns from raw multidimensional data. These models produce multidimensional embeddings that, while containing a lot of informatio...
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Salama Shady, Vera Paola Shoda and Takashi Kamihigashi
This paper presents a comprehensive analysis of the social media posts of prefectural governors in Japan during the COVID-19 pandemic. It investigates the correlation between social media activity levels, governors? characteristics, and engagement metric...
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Sergiu Zaharia, Traian Rebedea and Stefan Trausan-Matu
The research presented in the paper aims at increasing the capacity to identify security weaknesses in programming languages that are less supported by specialized security analysis tools, based on the knowledge gathered from securing the popular ones, f...
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Apichat Suratanee and Kitiporn Plaimas
Identifying genes associated with autism spectrum disorder (ASD) is crucial for understanding the underlying mechanisms of the disorder. However, ASD is a complex condition involving multiple mechanisms, and this has resulted in an unclear understanding ...
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Bardia Rafieian, Pedro Hermosilla and Pere-Pau Vázquez
In data science and visualization, dimensionality reduction techniques have been extensively employed for exploring large datasets. These techniques involve the transformation of high-dimensional data into reduced versions, typically in 2D, with the aim ...
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Martina Pticek and Jasminka Dob?a
Metaphors are an integral and important part of human communication and greatly impact the way our thinking is formed and how we understand the world. The theory of the conceptual metaphor has shifted the focus of research from words to thinking, and als...
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Wael H. Gomaa, Abdelrahman E. Nagib, Mostafa M. Saeed, Abdulmohsen Algarni and Emad Nabil
Automated scoring systems have been revolutionized by natural language processing, enabling the evaluation of students? diverse answers across various academic disciplines. However, this presents a challenge as students? responses may vary significantly ...
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Nasrin Elhassan, Giuseppe Varone, Rami Ahmed, Mandar Gogate, Kia Dashtipour, Hani Almoamari, Mohammed A. El-Affendi, Bassam Naji Al-Tamimi, Faisal Albalwy and Amir Hussain
Social media networks have grown exponentially over the last two decades, providing the opportunity for users of the internet to communicate and exchange ideas on a variety of topics. The outcome is that opinion mining plays a crucial role in analyzing u...
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Grigorios-Aris Cheimariotis and Nikolaos Mitianoudis
This work describes a methodology for sound event detection in domestic environments. Efficient solutions in this task can support the autonomous living of the elderly. The methodology deals with the ?Challenge on Detection and Classification of Acoustic...
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Tao Peng, Kun She, Yimin Shen, Xiangliang Xu and Yue Yu
Requirement traceability links are an essential part of requirement management software and are a basic prerequisite for software artifact changes. The manual establishment of requirement traceability links is time-consuming. When faced with large projec...
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