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Youtube Comment Summarizer and Post Content Analysis

Youtube Comment Summarizer and Post Content Analysis

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international conference on Computation System and information technology for Sustainable Solutions (CSITSS)

作者： Aneesh Adiga S Anish S Chaithanya Ganesh Abhin Divakar RV College of Engineering

ISBN: (数字)9798331505462

ISBN: (纸本)9798331505479

this paper presents a unified approach to analyzing online discourse by leveraging advanced natural language processing techniques, focusing on both YouTube comments and Amazon reviews. We introduce a YouTube Comment Analyzer and an Amazon Review Summarizer, both employing bag-of-words analysis to unveil sentiment trends, topic dynamics, and actionable insights within user-generated content. through the utilization of state-of-the-art machine learning algorithms, our tools categorize comments and reviews, extract key sentiments, and identify prevalent topics. By synthesizing salient features from both platforms, we offer a comprehensive understanding of user engagement, content reception, and product performance. Our findings contribute to a deeper comprehension of online discourse dynamics and provide valuable insights for content creators, marketers, businesses, and platform administrators in navigating the digital landscape effectively.

关键词： Video on demand Machine learning algorithms Reviews Navigation User-generated content Focusing Market research Natural language processing web sites information technology

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iGrade: an automated short answer grading system 6

iGrade: an automated short answer grading system

引用

6th international conference on Natural language processing and information Retrieval, NLPIR 2022

作者： Alhamed, Dina Hamed Alajmi, Aljawharah Mohammad Alqahtani, Tayma Abdulrahman Alali, Yasminah Hani Alnassar, Maryam Riyadh Alabbad, Dina Abdullah Department of Computer Engineering College of Computer Science and Information Technology Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia Department of Computer Information Systems College of Computer Science and Information Technology Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia

ISBN: (纸本)9781450397629

During the COVID-19 pandemic, most countries rely on E-Learning to apply social distance policy which affects the exams evaluation process. this project aimed to assist instructors in grading the short answer questions for CCSIT courses. By implanting a website application that the instructors could use to upload the students' answers and the ĝiGrade"software model will grade it. Moreover, the system will reduce the workload on the facilities members by saving time and effort as well as guarantee an objective grading for students. the model used in this project is a state-of-the-art BERT Neural Network model along with layers of BiLSTM that was trained using a dataset that has been collected from previous midterm and final exams of the CIS 211 course. the dataset consists of three categories which are (0, 0.5, 1) with around 1,128 instances. the "iGrade"test obtained an accuracy score of 85,4%, demonstrating BERT's superiority and independence from features during short answer grading as a default method in NLP. CCS CONCEPTS •Computing methodologies •Artificial intelligence •Natural language processing © 2022 ACM.

关键词： Grading

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SQL Injection Vulnerability Detection Based on Pissa-Tuned Llama 3 Large language Model

SQL Injection Vulnerability Detection Based on Pissa-Tuned L...

引用

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

作者： Zonghang Tian Yingying Zhang Shuting Lou Zhengdan Jiang Xingkai Cheng Guangdong Branch of National Computer Network Emergency Response Technical Team/Coordination Center of China Guangzhou Guangdong China

ISBN: (数字)9798331541750

ISBN: (纸本)9798331541767

SQL injection vulnerability is a common cyber security vulnerability. the existing SQL injection attack detection methods have problems such as high false positive rate and insufficient migration. In view of the powerful natural language processing ability of large language models, this paper proposes a SQL injection vulnerability detection method based on PiSSA fine-tuning of Llama3 large language models. the experimental results show that the proposed method achieves 99.81% accuracy and 0.19% false positive rate on the common benchmark data set, which verifies the good performance of the large language model in the field of SQL injection attack detection.

关键词： Performance evaluation Accuracy Large language models Data preprocessing SQL injection Benchmark testing Data models Natural language processing Prompt engineering

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Automatic generation of SysML requirement models based on Chinese natural language requirements 6

Automatic generation of SysML requirement models based on Ch...

引用

6th international conference on Electronic information technology and Computer Engineering, EITCE 2022

作者： Chen, Jialu Hu, Baokun Diao, Wanwan Huang, Yuqian Hangzhou Normal University Zhejiang Hangzhou China

ISBN: (纸本)9781450397148

In the face of increasingly complex systems engineering R&D, Model-Based Systems Engineering (MBSE) is gradually replacing Traditional Systems Engineering, producing a significant shift in modelling language, modelling thinking and modelling tools. And SysML, as a common modelling language for MBSE practitioners, has many irreplaceable advantages. Requirements diagrams are the primary medium of SysML for conveying traceability between requirements and from requirements to structure and behaviour in a system model. Today, how to automate the construction of SysML requirements models is a significant challenge. this paper proposes an automatic SysML model generation method based on Chinese free-text requirements using natural language processing. Firstly, perform word segmentation and POS Tagging on the requirement text to construct a domain lexicon, extract effective requirements by combining the domain lexicon and regular expressions, and then mark the effective requirements with semantic roles, and determine the requirements elements through established rules, which are ultimately converted into SysML requirements diagrams. © 2022 Association for Computing Machinery.

关键词： Modeling languages

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the Improvement of Stock Trade Policies: the Role of Quality Characteristics

The Improvement of Stock Trade Policies: The Role of Quality...

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Natural language processing (ICNLP), international conference on

作者： Huiming Liu Su Wu Chongwen Zhong Ying Liu Postdoctoral Research Center Industrial and Commercial Bank of China Beijing China Department of Industrial Engineering Tsinghua University Beijing China School of Economics and Management Beijing Institute of Petrochemical Technology Beijing China School of Economics and Management Beijing Information Science and Technology University Beijing China

ISBN: (数字)9798350349115

ISBN: (纸本)9798350349122

Products’ quality could significantly influence user experience thus companies’ performance in capital market would be affected. this paper explores the impact of products’ quality characteristics on stock performance by discussing the stock trade policies. the research samples are comprised of Apple corporation’s main type of products with their customer online reviews. Our study demonstrates that products’ quality characteristics could improve annualized return, Sharpe ratio and maximum drawdown in basic stock trade policies. We provide new evidence of the improvement of quality characteristics on stock trade policies.

关键词： Fluctuations Reviews User experience Natural language processing

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Siamese Network Tracking Algorithm Based on 3D Attention and Fusion Cross correlation

Siamese Network Tracking Algorithm Based on 3D Attention and...

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Natural language processing (ICNLP), international conference on

作者： Panshuai Tian Haibo Ge Yu An Sai Ma School of Electrical Engineering Xi'an University of Posts and Telecommunications Xi’an China

ISBN: (数字)9798350349115

ISBN: (纸本)9798350349122

Siamese network is a research direction that has attracted much attention in the field of target tracking and is one of the current mainstream target tracking algorithms. Aiming at the problem that the number of network model parameters continues to increase and existing similarity matching methods ignore local information of the target, a target tracking algorithm FCM-Siam based on 3D attention and fusion cross correlation is proposed. the SimAM attention module is added after the backbone network to enhance the feature extraction capability of the network; then, the feature map is input into the fusion cross-correlation module (FCM) to effectively suppress the influence of background and interference information, and make the similarity matching of target template and search image more accurate; finally, tracking via a classification regression network. the tracker was tested on the OTB100 and VOT2018 data sets and compared with advanced trackers. Experiments show that the tracker in this paper has better tracking performance.

关键词： Solid modeling Target tracking Correlation three-dimensional displays Attention mechanisms Accuracy Interference Feature extraction Natural language processing Classification algorithms

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Leveraging Slot-Aware Enhancements for Improved Zero-Shot Dialogue State Tracking

Leveraging Slot-Aware Enhancements for Improved Zero-Shot Di...

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

作者： Tianhang Song Haolei Hu Xinxin Chen Kangli Zi Henan Institute of Advanced Technology Zhengzhou University Zhengzhou China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Beijing China

ISBN: (数字)9798331541750

ISBN: (纸本)9798331541767

Task-oriented dialogue systems (TOD) aim to help users complete specific tasks through multiple rounds of dialogue, in which Dialogue State Tracking (DST) is a key component. the training of DST models typically necessitates the availability of a substantial corpus of dialogue data with turn-level annotations. However, the collection of such data is both costly and inefficient. Despite the impressive performance of systems based on advanced large language models (LLMs), their closed-source nature restricts the potential for local deployment. To address this challenge, this paper proposes a new zero-shot slot-aware enhanced model (SAE), which introduces a novel coded prompting framework to enhance the DST capability of small parameter models in new domains and task scenarios. In particular, we have devised a prompting framework that employs code to refine task instructions. Furthermore, we have proposed a slot-aware question generation mechanism that generates slot-aware questions based on contextual details in accordance with the dialogue context, thereby enhancing the model's perception and matching capabilities for slots. In order to verify the effectiveness of the model, we conducted experiments on the MultiWOZ dataset. the results show that the SAE model has achieved significant performance improvements in zero-shot DST tasks.

关键词： Training Adaptation models Codes Large language models Computational modeling Termination of employment Predictive models Question generation Data models Context modeling

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Vietnamese Text Summarization Based on Elementary Discourse Units 6

Vietnamese Text Summarization Based on Elementary Discourse ...

引用

6th international conference on Natural language processing and information Retrieval, NLPIR 2022

作者： Lam, Khang Nhut Nguyen, Tai Ngoc Kalita, Jugal Information Technology Can Tho University Can Tho Viet Nam Computer Science University of Colorado Colorado Springs United States

ISBN: (纸本)9781450397629

this paper presents text summarization models based on elementary discourse units (EDUs) to construct extractive and abstractive summarization for Vietnamese documents. First, we introduce algorithms using the POS information for constructing EDUs in Vietnamese. then, the EDUs created are fed into an extractive summarization model using a pointer network and an abstractive summarization model using a pointer generator model. A reinforcement learning method is used to improve the quality of the models. We perform experiments on the CTUNLPSUM dataset, including 1,053,702 Vietnamese documents extracted from online magazines. the extractive summarization models based on EDUs outperform other extractive summarization models based on words or sentences. the ROUGE-1, ROUGE-2, and ROUGE-L of the best extractive and abstractive summarization models are 0.567, 0.241, 0.461;and 0.530, 0.213, 0.394, respectively. © 2022 ACM.

关键词： Reinforcement learning

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NLP Based Word Predictor for Dementia Patients: A Systematic Review 6

NLP Based Word Predictor for Dementia Patients: A Systematic...

引用

6th international conference on Intelligent Computing and Control Systems, ICICCS 2022

作者： Shahapure, Nagamani H Poornima, N. Kulkarni, Spoorthi Shilpa, V. Singh, Rajiv Ranjan Kavan, Patel Jss Academy of Technical Education Department of Information Science and Engineering Bangalore India

ISBN: (纸本)9781665410359

Due to the increased number of people suffering with dementia and the obstacles faced in developing the assistive technologies to support the dementia clients;the use of eHealth for people with dementia has received significant attention in the recent years. Around the globe, around 35.6 million of the population has been suffering from dementia since 2010. this calculation has been expected to shoot up to 115.4 million by 2050. the disorder is diagnosed only for a minute fraction of patients. However, Dementia is still considered as an imminent part of aging, instead of taking it as a symptom of a regressing disease. Keeping all these survey numbers into consideration, it becomes the sole responsibility of the growing future to take care of its country and its people. Daily Routine Assistance like notification reminders of circumstances such as complications in health parameters and other essential alerts such as reminding the patient about medicine intake and doctor appointments is an important task. Use of technology like Internet of things (IoT) helps in monitoring the patients. Another important task is to help the patient in speaking;this includes completion of sentences by prompting of words. the existing techniques support the health and safety monitoring of Dementia patients. However, there is a technological gap to assist Dementia people with aphasia. Assisting the dementia patients to communicate and lead a quality life is a challenging task. this can be achieved by using Natural language processing (NLP). this paper gives the detailed review of the various techniques used in NLP. © 2022 IEEE.

关键词： Internet of things

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Automated Monitoring Method for Enterprise Microservices Network Operation Status Based on Database Knowledge Graph

Automated Monitoring Method for Enterprise Microservices Net...

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Electronics and Communication, Network and Computer technology (ECNCT), international conference on

作者： Qidi Hu Yujiang Long Ye Zhong Guangyi Zhang Wei Wei Information Center of Guizhou Power Grid Co. Ltd Guiyang Guizhou China

ISBN: (数字)9798350366143

ISBN: (纸本)9798350366150

this thesis presents an innovative method for automated monitoring of enterprise microservices networks using a database knowledge graph, addressing the challenges of traditional monitoring systems that often fail to effectively manage the complex dynamics of microservices architectures. By integrating advanced Natural language processing (NLP) and Long Short-Term Memory (LSTM) networks, this method processes vast amounts of real-time and historical data to proactively predict system failures and optimize resource allocation. the key innovation lies in the application of a knowledge graph that enhances predictive maintenance capabilities and facilitates performance optimization through intelligent data analysis and pattern recognition. this approach not only improves operational efficiency but also reduces downtime, thereby significantly enhancing network management in enterprise environments. Our research confirms that knowledge graphs can provide a scalable and dynamic solution to adapt to diverse enterprise requirements.

关键词： Technological innovation Databases Microservice architectures Knowledge graphs Aerodynamics Real-time systems Natural language processing Monitoring Long short term memory Predictive maintenance

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