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A Text Augmentation Method Based on Dual Diversity Generation

A Text Augmentation Method Based on Dual Diversity Generatio...

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Robotics, Intelligent Control and Artificial Intelligence (RICAI), international conference on

作者： Qingwu Fan Xinyue Guo Faculty of Information Science and Technology Beijing University of Technology Engineering Research Center of Digital Community Ministry of Education Beijing China

ISBN: (数字)9798331541699

ISBN: (纸本)9798331541705

In text augmentation in the field of natural language processing, it has been observed that most of the traditional methods often result in only minimal changes to the original text, which consequently limits the diversity of the augmented samples. In this paper, a novel text augmentation method based on Dual Diversity Generation is proposed, which effectively addresses the aforementioned limitation through two key components: keyword diversity and sample diversity. Initially, a sketch is constructed through keyphrase extraction, which is subsequently input into the text augmentation model for the generation of new samples. To mitigate the semantic overlap among the extracted keyphrases, keyphrase diversity is incorporated into the extraction process. Furthermore, sample diversity is emphasized during the generation phase to enhance the overall quality of the text augmentation. the performance of the proposed method is evaluated by text classification effect, and the experimental results indicate that the proposed method achieves significant improvements compared to other methods.

关键词： Text categorization Semantics Refining Diversity methods Solids Natural language processing Data mining Standards Robots Intelligent control

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Research on Software Isomerization technology Based on Diversified Compilation

Research on Software Isomerization Technology Based on Diver...

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6th international conference on Intelligent Computing and Signal processing (ICSP)

作者： Chuan He Bo Zhang Zesheng Xi Yunfan Wang Lu Chen Zhuo Lv State Grid Key Laboratory of Information & Network State Grid Smart Grid Research Institute co. Ltd. Nanjing China Information and Communication Branch of State Grid Anhui Electric Power co. Ltd. Nanjing China State Grid Henan Electric Power Research Institute Zhengzhou China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

this article first focuses on the implementation difficulties of software heterogeneous variants, studies the basic principles and implementation mechanisms of pre runtime software intermediate language diversification compilation technology, and combines the characteristics of endogenous security defense architecture. through efficient equivalent transformation technology at the source code, intermediate representation, binary and other levels, and corresponding code generation technology, it provides multi-level diversified compilation strategies and means, and provides a source code level heterogeneous redundant variant implementation framework for endogenous security defense. then, to address the issue of software heterogeneity at the intermediate code level, study the compilation process during the intermediate code generation stage; Research and analyze methods such as equivalent instruction replacement, control flow obfuscation, and blank instruction insertion. Propose diversified transformation methods for intermediate languages in application source code, implement diversified compilation techniques based on intermediate language transformation compilation, and achieve software heterogeneity in endogenous security defense architecture. Finally, build a testing environment to support the feasibility verification of the system architecture and key technologies.

关键词： Codes Runtime Processor scheduling Source coding Systems architecture Computer architecture Signal processing Software Security Testing

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Multi-Layer Visual Perception for No-Reference Image Quality Assessment

Multi-Layer Visual Perception for No-Reference Image Quality...

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IEEE international conference on Electronic information and Communication technology (ICEICT)

作者： Junwei Qi Yingzhen Wang Qingchun Wang Yingsong Li College of Computer Science and Technology Harbin Engineering University Harbin China College of Information and Communication Engineering Harbin Engineering University Harbin China Shanghai Yanding Information Technology Co. Ltd. Shanghai China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui China

In this work, we propose a no-reference image quality evaluation approach, aiming to solve the problem that the traditional convolutional neural network is insufficient to express the global information of the image. therefore, in order to make the captured image features have the coherence of global context information, we combine a Transformer structure widely used in NLP (natural language processing) with the traditional CNN to realize the attention mechanism in the human visual perception characteristics. Firstly, the self-attention mechanism of Transformer is used to learn the global representation of the image from the multi-layer features extracted from different levels of CNN. Additionally, to forecast the ultimate image quality score, the global and local attributes are combined. Finally, the proposed algorithm is evaluated on three public datasets commonly used in CSIQ [1], TID2013 [2] and LIVE [3]. Compared with eight traditional no-reference image quality evaluation algorithms and five methods based on deep learning, the proposed algorithm achieves competitive results.

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What Are the Latest Fake News in Romanian Politics? An Automated Analysis Based on BERT language Models 6th

What Are the Latest Fake News in Romanian Politics? An Autom...

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6th international conference on Smart Learning Ecosystems and Regional Development, SLERD 2021

作者： Busioc, Costin Dumitru, Vlad Ruseti, Stefan Terian-Dan, Simina Dascalu, Mihai Rebedea, Traian Department of Computer Science University Politehnica of Bucharest 313 Splaiul Independentei Bucharest060042 Romania Department of Romance Studies Lucian Blaga University of Sibiu 10 Bld Victoriei Sibiu550024 Romania Academy of Romanian Scientists 3 Str. Ilfov Bucharest050044 Romania

ISBN: (纸本)9789811639296

Social media and news outlets facilitate information sharing, while the web is flooded by information posted online on a daily basis. However, content may be differently transmitted from case to case, based on the authors’ intentions and vocabulary, to the extent that it generates completely opposite points of view. As such, fake news have become a global phenomenon, and recent events highlight a high impact of distorted or fake information, especially on the political side, when candidates’ discourses include tendentious statements that require careful validation before completely trusting the source. this paper proposes an automated analysis of political statements in Romanian by applying different state-of-the-art Natural language processing techniques, and evaluating the importance of context in determining their veracity. Our corpus consists of entries from Factual, a recent Romanian fact-checking initiative that assembled a list of public statements, alongside relevant contextual information for their interpretation. Our results are comparable to similar experiments performed on the PolitiFact dataset, and represent a strong baseline for experiments in low-resource languages, like Romanian. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Natural language processing systems

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Enhancing Text Extraction Using OCR with AWS Textract Service 6th

Enhancing Text Extraction Using OCR with AWS Textract Servic...

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6th international conference on advanced Informatics for Computing Research, ICAICR 2023

作者： Bawasker, Aakash Dedania, Yash Karia, Vrushti Bhatt, Nirav Prajapati, Purvi Bhatt, Nikita Chandubhai S. Patel Institue of Technology Charotar University of Science and Technology Gujarat Anand India

ISBN: (纸本)9783031840616

the advent of Optical Character Recognition (OCR) technology has revolutionized document handling for businesses, enabling the conversion of handwritten text into machine-readable content. this project explores Amazon web Services Textract, a cutting-edge OCR service integrating advanced machine learning and deep learning models. Emphasis is placed on dissecting Textract's architecture, features, and practical applications, showcasing its proficiency in extracting text, forms, and tables from diverse document types such as scanned papers, PDFs, and images. Real-world examples demonstrate Textract's seamless integration with document management systems, facilitating data analysis and ***, the article conducts a comprehensive evaluation of the efficiency and accuracy of three OCR solutions: Tesseract (English text), Amazon Textract (Arabic text), and Google DocumentAI (English text). through a comparative analysis of their performance and identification of distinctions in handling common text imperfections, the study aids researchers in informed decision-making for OCR solutions aligned with specific research ***, the project underscores the utility and benefits of incorporating AWS Textract into OCR applications. It highlights how Textract enhances document processing efficiency, improves data accessibility, and ensures compliance adherence. Valuable insights are provided for organizations seeking to optimize document management workflows and leverage OCR capabilities through AWS Textract. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Optical data processing

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Corpus Design Challenges and Analysis of Acoustic information for Automatic Dialect Classification 6

Corpus Design Challenges and Analysis of Acoustic Informatio...

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6th IEEE international conference on Signal processing, Computing and Control, ISPCC 2021

作者： Arora, Ashima Singh, Amitoj Kadyan, Virender Chitkara University Institute Of Engineering And Technology Punjab India Maharaja Ranjit Singh Punjab Technical University Department Of Computer Science And Engineering Punjab India University Of Petroleum And Energy Studies Department Of Informatics School Of Computer Science Uttarakhand Dehradun India

ISBN: (纸本)9781665425520

the primary challenge across the field of automatic speech communication relies upon the understanding of creation of such acoustic models that are capable of representing distinct differences throughout the spoken languages. the design of such systems is undoubtedly affected by the parameters such as an Individual's age, gender, speaking style, dialectal variability, recording environment etc. this work investigates on the various challenges faced during designing an enriching corpus and analyzing the dialectal variations by tracking the variance of different acoustic parameters such as pitch contour, formant frequency, and intensity for different toneme sounds. the article also makes an attempt to discuss the process and problem of tone assimilation (tone sandhi) in di/multi-syllable words of Punjabi language where the occurrence of more than one tone is being anticipated. the pitch variations of the input signal are performed using PRATT toolkit, to establish a relation between the pitch variations across the various tonemes. the model is further evaluated using the ANOVA test for the comparative classification of dialects based on acoustic features. the entire work is based upon the four dialects of Punjabi language;classified as the 10th most spoken language across the world, with over 105 million native speakers. © 2021 IEEE.

关键词： Speech communication

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Syntactical Analysis of Student's Descriptive Answer Sheets and Predict Student's Performance Using NLP and Tensor flow Decision Forests

Syntactical Analysis of Student's Descriptive Answer Sheets ...

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international conference on Contemporary Computing and Informatics (IC3I)

作者： Abhilash Kumar Saxena Raghavendra R College Of Computing Science And Information Technology Teerthanker Mahaveer University Moradabad Uttar Pradesh India College of Computing Sciences And Information Technology Jain (Deemed to be) University Bangalore Karnataka India

the employment of computer-based assessment methods has become increasingly significant on a global scale for various types of academic evaluations. this approach exhibits a relatively higher speed compared to our conventional manual assessment procedure. the present study introduces a novel approach for assessing students' concise responses, including descriptive answers, through the utilization of Natural language processing (NLP) techniques. Within this framework, an educator generates an answer sheet and a dataset of keywords to facilitate the examination procedure. the dataset is stored in designated data storage, while the students input their responses on the examination page. this research endeavour involves conducting syntactical analysis to compare standard responses and recording the results in a database. Additionally, an evaluation of the same response is performed using a Natural language processing (NLP) algorithm to identify grammatical errors, and the results are analysed using Tensorflow in the database. through the implementation of these techniques, we can achieve optimal outcomes. the outcomes produced by the system are contrasted with the assessment conducted by the academic staff.

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Harnessing In-Context Learning for Personality Elicitation in Large language Models

Harnessing In-Context Learning for Personality Elicitation i...

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Frontiers technology of information and Computer (ICFTIC), IEEE international conference on

作者： Haoyang Zhang Department of Applied Mathematic The Hong Kong Polytechnic University Hong Kong China

ISBN: (数字)9798331541750

ISBN: (纸本)9798331541767

With the rapid advancements in deep learning and natural language processing, large language models (LLMs) have demonstrated remarkable performance across a variety of tasks. While previous studies have explored the existence of personality traits within LLMs, the potential to systematically control and induce specific personalities remains under-researched. this paper introduces a novel approach using In-Context Learning (ICL) to induce personality traits in LLMs, specifically grounded in the Big Five personality theory. We present a curated example set designed to evoke each of the five key personality dimensions: openness, conscientiousness, extraversion, agreeableness, and neuroticism. Using the Machine Personality Inventory (MPI), we quantitatively measure LLMs' personality traits and analyze the effects of example complexity, relevance, and diversity on the stability and effectiveness of personality induction. Experimental results indicate that LLMs can exhibit personality traits similar to humans and that the ICL method significantly enhances the prominence of these traits. Additionally, LLMs exhibit strong generalization capabilities in scenario-based tests, suggesting their potential for personalized AI applications. this study advances the understanding of personality control in LLMs and highlights the implications for human-AI interaction.

关键词： Deep learning Large language models Control systems Stability analysis Natural language processing Complexity theory Prompt engineering Testing

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Improving Chinese Named Entity Recognition by Glyph and Part-of-Speech

Improving Chinese Named Entity Recognition by Glyph and Part...

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international conference on Artificial Intelligence and Big Data (ICAIBD)

作者： Qiurong Tan Yuanyuan Li Xi Xiong Jianghe Wang Ling He Feihu Huang School of Cybersecurity Chengdu University of Information Technology Chengdu China Mental Health Center West China Hospital of Sichuan University Chengdu China College of Biomedical Engineering Sichuan University Chengdu China College of Computer Science Sichuan University Chengdu China

Chinese characters are a unique type of morpheme-syllabic characters that are integral to the ideographic writing system used in the Chinese language. the most widely used word formation method in Chinese is the formation of compound words from roots according to syntactic relationships, which is basically the same as the syntax of combining words into phrases. However, the appropriate use of glyph information and lexical information in natural language processing tasks is still limited. To solve above problem, this paper proposes a novel approach, named GP-NER, to enhance Chinese character representation by glyph features and inject word information with part-of-speech information. Specifically, GP-NER uses a gate mechanism to enhance the representation of characters by combining glyph features, and then uses part-of-speech information to enhance the contextual representation of text sequences through attention mechanisms. Experimental results demonstrate the effectiveness of the proposed model.

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6th international conference on information, Communication and Computing technology, ICICCT 2021

6th International Conference on Information, Communication a...

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6th international conference on information, Communication and Computing technology, ICICCT 2021

ISBN: (纸本)9783030883775

the proceedings contain 20 papers. the special focus in this conference is on information, Communication and Computing technology. the topics include: Predicting the Decomposition Level of Forest Trees through Ensembling Methods;can Machine Learning Predict an Employee’s Mental Health?;predicting the Stock Market Trend: An Ensemble Approach Using Impactful Exploratory Data Analysis;detecting Text-Bullying on Twitter Using Machine Learning Algorithms;empirical Laws of Natural language processing for Neural language Generated Text;quantum Based Deep Learning Models for Pattern Recognition;performance Analysis of Named Entity Recognition Approaches on Code-Mixed Data;measurement of Liquid Level Using Prediction Methodology;A MapReduce Approach to Automatic Key File Updates for SPT (Squeeze, Pack and Transfer) Algorithm;web-Based Real-Time Gesture Recognition with Voice;performance Enhancement in Big Data by Guided Map Reduce;multi-layer Parallelization in Transportation Management Software;Multipath TCP Security Issues, Challenges and Solutions;story Generation from Images Using Deep Learning;preface;comparative Analysis of Security Protocols in IoT;Minimize Penalty Fees During Reconfiguration of a Set of Light-Tree Pairs in an All-Optical WDM Network;secure Data Transmission Techniques for Privacy Preserving Computation Offloading Between Fog Computing Nodes.

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