Stance detection on social media has attracted significant attention recently. However, for a hot event, it is not easy to determine the stance of a comment on a given target, because there is complex comment-target-e...
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ISBN:
(纸本)9798350349122;9798350349115
Stance detection on social media has attracted significant attention recently. However, for a hot event, it is not easy to determine the stance of a comment on a given target, because there is complex comment-target-event-stance relationship behind it. To alleviate this problem, a new fusion method is proposed, which integrates explicit stance label and brief event background into BERT-based stance classifier. By fine-tuning the BERT model, it learns to reason about accurate stances based on the fused information. Experiments on a Weibo stance detection dataset demonstrate the effectiveness of the method.
The overwhelming volume of scientific documents necessitates automatic summarization to assist researchers in efficiently finding relevant data, making informed decisions, and retrieving appropriate answers to their q...
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The field of space science and applications, rich in domain knowledge, has witnessed research on domain knowledge extraction and the preliminary construction of domain knowledge graphs. Entity linking serves as a fund...
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naturallanguageprocessing (NLP) is an interdisciplinary field that enables machines to understand and generate human language. One of the crucial steps in several NLP tasks, such as emotion and sentiment analysis, t...
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In this paper we introduce a new Controlled naturallanguage (CNL) known as "Noam". It is used to express cyber security knowledge and for reasoning over it. The approach follows examples set by other domain...
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ISBN:
(纸本)9783031516634;9783031516641
In this paper we introduce a new Controlled naturallanguage (CNL) known as "Noam". It is used to express cyber security knowledge and for reasoning over it. The approach follows examples set by other domain-specific languages and constrained grammars, but is highly unusual due to its singular focus on cyber security. Like most CNLs Noam is both human-readable and machine-solvable, thus fulfilling important assurance requirements with respect to transparency and explainability. The language seeks to address a growing problem faced by security engineers and architects;namely, that their endeavours are constrained by the complexity and sheer interconnectedness of the systems they protect. This is further compounded by year-on-year vulnerability disclosure rates and diversification of the Tactics, Techniques and Procedures used by threat actors. Our approach is analogical in which the Noam CNL is used to construct a system model, instrument it with data from the real environment and apply functional programming techniques in order to 'solve-for' certain conditions of interest. The intention is to demonstrate the value of CNLs and semantic reasoning within cyber security, framed in the context of improving the information available to security engineers, architects and other decision-makers.
The task of image caption generation aims to automatically produce naturallanguage descriptions that match the content of images, integrating the fields of machine vision and naturallanguageprocessing, which holds ...
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In the development of new industries, there is a growing demand for innovative materials. However, locating such materials is a laborious and time-consuming endeavor. In response, there has been a shift toward studyin...
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In the development of new industries, there is a growing demand for innovative materials. However, locating such materials is a laborious and time-consuming endeavor. In response, there has been a shift toward studying new materials more efficiently using existing material science research knowledge. There has been an increase in the number of materials science-related papers over the past two decades, and attempts to use them for research purposes have increased as the methods have been systematized. Past research papers, for instance, can be used to predict new materials or obtain optimal synthesis parameters for materials with the desired properties. In this movement, naturallanguageprocessing (NLP) is a crucial technology. In the past decade, NLP has emerged as one of the most rapidly expanding areas of artificial intelligence, proving to be a valuable tool for processinglanguage-based data. In this review, we will examine how NLP is used in the materials science literature, what processes it can be used for, and the primary NLP technologies currently in use, with a particular focus on specific use cases. We will also discuss this approach's limitations.
Large language models excel in various naturallanguageprocessing tasks but often struggle with knowledge-intensive queries, particularly those involve rare entities or require precise factual information. This paper...
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As a key medium to eliminate language barriers and enhance international understanding, English translation software plays an important role in the rapid and accurate circulation of information. This article aims to e...
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With the rise of social media, hate speech has become increasingly widespread and potent. A notable type of hate speech is dehumanization, which has been hypothesized to enable harmful behavior towards members of soci...
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