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A Novel Hindi Voice-Based Assistant System Architecture For E-Commerce 6th

A Novel Hindi Voice-Based Assistant System Architecture For ...

引用

6th international conference on Computational Intelligence in Communications and Business Analytics, CICBA 2024

作者： Kujur, Avinash Paul Fahad, Md Shah Birla Institute of Technology Mesra Jharkhand Ranchi835215 India

ISBN: (纸本)9783031813412

this paper presents a novel architecture for a Hindi voice-based assistant system tailored for e-commerce applications. the architecture integrates key components including speech recognition, machine translation, keyword extraction, intent classification, a dictionary-based question-answering model, and speech synthesis. the system efficiently converts spoken Hindi queries into text, translates across languages, identifies intent, extracts keywords, generates relevant database queries, and provides accurate responses through synthesized speech. this holistic approach enhances user interaction, accessibility, and convenience within the e-commerce domain. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Natural language processing systems

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Data Driven Resume Analyzer for Student Career Optimization

Data Driven Resume Analyzer for Student Career Optimization

引用

Mobile Computing and Sustainable Informatics (ICMCSI), international conference on

作者： S. Sarumathi Bhavatharany E Sanjaiy R Mathinesan P Department of Artificial Intelligence and Data Science K.S. Rangasamy College of Technology Tiruchengode India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

the proposed Resume Analyzer System is a machine-learning-powered program that helps job searchers improve their resumes by aligning them with particular job criteria and current industry norms. the system has secure registration and login capabilities, and it uses a MongoDB database to protect sensitive data such as resumes, application histories, and personal information. the system assesses resumes using sophisticated natural language processing (NLP) and machine learning (ML) methods, taking into account crucial variables including language quality, structural organization, skill gaps, and keyword optimization. It makes targeted, actionable suggestions to assist users improve their resumes by highlighting missing parts, underrepresented abilities, and poor keyword use. Unlike standard resume screening systems, which often depend on static and generic models, this system uses dynamic learning capabilities to react to changing hiring patterns by constantly updating its database of resumes and job descriptions. this flexibility enables the system to provide targeted, context-relevant feedback, ensuring that resumes satisfy the sophisticated requirements of current recruiting procedures. the Resume Analyzer's comprehensive architecture allows it to accommodate a broad range of resume formats while also providing real-time, job-specific information to assist job seekers polish their applications and improve their visibility in applicant tracking systems. By addressing existing models' limitations, such as insufficient contextual skill analysis, a lack of format versatility, and generic feedback, the Resume Analyzer System enables candidates to stand out in an increasingly competitive job market, making it an invaluable tool for improving career prospects.

关键词： Target tracking Engineering profession Databases Resumes Standards organizations Refining Organizations Natural language processing Real-time systems Optimization

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Fake News Detection and Classification Using Deep Learning Techniques for Social Media Text 6th

Fake News Detection and Classification Using Deep Learning T...

引用

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

作者： Kumari Shalini, A. Saxena, Sameer Suresh Kumar, B. AMITY Institute of Information Technology Amity University Rajasthan Jaipur India School of Computer Science and Engineering Sanjay Ghodawat University Kolhapur India

ISBN: (纸本)9783031840616

the rise of social media networks has become a critical component of modern human living due to recent developments and advances in computer technology. the present context has evolved into a widely recognized medium for the distribution of information and news pertaining to a wide range of topics, including daily reports. this timeframe serves as the main period for data collecting and information transmission. this environment has a multitude of advantages;yet, it also entails a significant amount of misinformation and material that may potentially perplex both readers and users seeking accurate information. A significant concern associated with this system is to the limited availability of reliable information and real-world news pertaining to social media. An integrated system has been built that leverages several components of chain type of technology and natural language processing (NLP) to use machine learning techniques for the purpose of detecting false news and enhancing the accuracy of identifying fraudulent user accounts and postings. Various methodologies have been used to extract and choose features in order to provide effective training rules and appropriately assess the test classifier. A comprehensive empirical investigation demonstrates that the Twitter dataset is a useful resource for assessing the precision of fake news detection in classification tasks. the deep learning based RNN system demonstrates a high accuracy rate of 98.80% throughout both training and testing phases. this accuracy surpasses that attained by traditional machine learning methods such as SVM, ANN, and NB. Furthermore, the proposed methodology has the capability to detect superfluous information, a phenomenon that may be corroborated via several sources or by referencing current events. the prime purpose of this approach is to enhance the eminence of the material, identify any problematic sections within the text, and generate the original versions of those sections, all whi

关键词： Tweets

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Word Sense Disambiguation for BODO language Using Simplified LESK 6th

Word Sense Disambiguation for BODO Language Using Simplified...

引用

6th international conference on Computational Intelligence in Communications and Business Analytics, CICBA 2024

作者： Basumatary, Subungshri Barman, Manas Narzary, Puja Barman, Anup Kumar Nag, Amitava Department of Computer Science and Engineering Central Institute of Technology Assam Kokrajhar783370 India

ISBN: (纸本)9783031813412

Word sense disambiguation (WSD) is the computational process of identifying a word's most appropriate sense in a given context, especially when words have many meanings. Word sense disambiguation (WSD) is a challenging task in natural language processing, partially because of the intrinsic complexity of both computer-based reasoning and human cognition. the main goals of Word Sense Disambiguation (WSD) techniques are the various methodologies that academics have devised to address this challenge and ascertain the precise meaning of a word in a given context. We came across a situation in which most of the words in our experimental sentences were not found in the Bodo Wordnet during our inquiry. As a result, we decided to use the condensed LESK method. the simplified LESK approach involves determining the intended meaning of a target word by identifying the sense gloss in Wordnet that has the greatest degree of overlap with the context word being considered. this is the essence of how the simplified LESK algorithm is employed for disambiguation. To the best of our current understanding, this study signifies the initial attempt in employing the LESK algorithm for the purpose of disambiguating word senses in the Bodo language. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Ambiguity Bodo language LESK Natural language processing (NLP) Word sense disambiguation (WSD)

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Natural language processing Techniques to Identify Work Profiles from Online Job Postings 4th

Natural Language Processing Techniques to Identify Work Pro...

引用

4th international conference on advanced Research in Technologies, information, Innovation and Sustainability 2024, ARTIIS 2024

作者： Ferreira, Alejandro Gómez, Walter Grünewald, Ingrid Departament of Industrial Processes Universidad Católica de Temuco Temuco Chile Departament of Mathematical Engineering Universidad de la Frontera Temuco Chile Consorcio de Universidades del Estado de Chile Santiago Chile

ISBN: (纸本)9783031832062

the present study generates a new methodology which allows us to study the job market in order to identify work profiles based on job openings published online. the methodology includes 5 stages: web scraping, Data pre-processing, Document filtering (job offers), Topic Modeling, and the Concept Grouping Stage and profile characterization. As a case study, we consider the Psychology profession, for which a corpus of 6,407 job listings was generated. In this case, document filtering was done based on Word2Vec and BERT, with the latter emerging as the better alternative. the corpus was thus reduced to 4,314. For the case study, we also constructed a graphic schema in order to visualize the job offers’ location and the graduation profiles with regards to the work profiles identified. the results from the Topic Modeling stage and the graphic projection are presented on dashboards, allowing for user interaction. the methodology developed has potential to help Higher Education Institutions redesign their curricula and review their graduation profiles, both fundamental aspects needed in their Accreditation processes, their continuous improvement and quality assurance processes © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Natural language processing systems

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CipherCraft: An Integrated Approach to Cryptographic Data Security in Modern Computing Environments 6th

CipherCraft: An Integrated Approach to Cryptographic Data S...

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6th international conference on Computational Intelligence in Communications and Business Analytics, CICBA 2024

作者： Rai, Deepak Ahmad, Tanzeel Talan, Arnav Reddy, Bogulla Rana Pratap Gola, Vishal School of Computer Science Engineering and Technology Bennett University UP Greater Noida India

ISBN: (纸本)9783031813351

this research study conducts an in-depth examination of the relationship between soft computing and the complex world of encryption and decryption, integrating a wide range of Cryptographic algorithms and various cryptographic concepts. the study broadens its scope to include chapters devoted to combinatorics and beyond, providing profound insights into the synthesis of mathematical ideas, intricate formulas, elaborate flowcharts, and sophisticated algorithms. In today’s data security world, the study focuses on addressing complicated challenges and encouraging developments in developing domains, including quantum computing, cryptology, artificial intelligence, natural language processing, machine learning, automata theory, computer networks, information management systems, data structures, and algorithms. this broad investigation highlights soft computing’s adaptability and versatility in addressing the various difficulties that plague modern data security. A key aspect of this study is devoted to the delicate art of cryptographic key management, emphasizing the production and secure handling of cryptographic keys, which is a crucial focal point in data security and privacy. It is the keystone that permits secure data encryption and decryption, representing one of the most crucial components of the research. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： information management

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Using LLMs and websearch in Order to Perform Fact Checking on Texts Generated by LLMs

Using LLMs and Websearch in Order to Perform Fact Checkin...

引用

19th international conference on Computer Aided Systems theory, EUROCAST 2024

作者： Sandler, Simone Krauss, Oliver Stöckl, Andreas University of Applied Sciences Upper Austria Campus Hagenberg Softwarepark 11 Hagenberg4232 Austria Advanced Information Systems and Technology Hagenberg Austria Digital Media Department Hagenberg Austria

ISBN: (纸本)9783031829598

Finding out if a given text contains any false information is not an easy task. On large corpora of data, such as the tremendous amount of texts generated by LLMs, fact checking is a prohibitively expensive task. To address this challenge, we propose a novel approach that combines fact checking by LLMs with web search. this method can be applied not only to single sentences by applying a true, false or unknown label. For whole text paragraphs, a 0..1 score representing the truthfulness from the sentence labels is calculated. the process begins by extracting claims from the text, which is done using GPT3. then, these claims are validated, with Google search results being used to supplement the GPT3 results. When validating our method against a corpus of 122 LLM-generated text samples, we achieve an accuracy of 0.79. To compare our work to other approaches, we also applied our fact checking to the FEVER dataset, achieving an accuracy of 0.78. Which is similar than the current best accuracy of 0.79 on the FEVER dataset. this demonstrates the potential of our proposed approach for automated fact checking. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Natural language processing systems

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An Empirical Study on the Performance of EVMs and Wasm VMs for Smart Contract Execution 6th

An Empirical Study on the Performance of EVMs and Wasm V...

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6th international conference on Blockchain and Trustworthy Systems, BlockSys 2024

作者： Song, Shuwei Liao, Zhou Chen, Ting Luo, Xiapu Zhang, Yongjie Wang, Guopeng University of Electronic Science and Technology of China Chengdu610000 China The Hong Kong Polytechnic University 999077 Hong Kong Zhejiang Ocean University Zhoushan316000 China The Open University of China Beijing100000 China

ISBN: (纸本)9789819614103

Blockchain and smart contract technology allow for the implementation of various decentralized applications. Smart contracts are typically developed in a high-level language, compiled into bytecode, and executed in a virtual machine (VM) on the blockchain client. Consequently, the VM’s performance significantly determines the execution speed of smart contracts, the clients’ resource overhead, and even the exploitable vulnerabilities. EVM is currently the most widely adopted VM, and several blockchains have developed customized EVMs to suit their specific requirements. However, the extent to which different EVM implementations exhibit performance differences has not been fully investigated. Moreover, the Wasm VM (WVM) has demonstrated satisfactory performance in the web domain, and it is regarded as a promising candidate for the next generation of smart contract VMs. However, it remains unclear whether WVMs offer superior functionality and performance compared to EVMs. To fill these gaps, this paper presents an empirical investigation of EVMs and WVMs. First, we compare the performance of EVMs implemented in Go, Rust, and C++ to provide blockchain nodes with suggestions on which EVM to adopt. Subsequently, we conduct a comparative analysis of EVMs and WVMs on three blockchain clients regarding five performance metrics. the results indicate that WVMs perform inferior to EVMs on all metrics. Furthermore, the findings and insights presented in this paper offer valuable recommendations for the evolution of WVMs. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： C++ (programming language)

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A unified approach to Chinese classifiers and the English number system

A unified approach to Chinese classifiers and the English nu...

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6th international conference on advanced language processing and web information technology

作者： Xiong Jianguo Bi Yude Luoyang Foreign Languages University Henan Province P.R. China

ISBN: (纸本)9780769529301

In this paper, we will try to provide a unified approach to Chinese classifiers and the number system in English. It is argued that the former and the latter are actually two different components of the same linguistic category, serving to divide inherently mass nouns selected from the lexicon into countable units. As a result, numerals can be merged to denote a number reading.

关键词： counting system English language English Dictionaries as Topic Numerals

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A template-based English-Chinese translation system using FOPA and UAMRT

A template-based English-Chinese translation system using FO...

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6th international conference on advanced language processing and web information technology

作者： Li Yujian Beijing Univ Technol Coll Comp Sci & Technol Beijing 100022 Peoples R China

ISBN: (纸本)9780769529301

this paper presents a template-based English-Chinese translation system characterized by two important features: Fast Optimal Parsing Algorithm (FOPA) and Universal Algorithm of Matching and Replacing Templates (UAAMT). First, the FOPA parses an English sentence into an optimal parse tree or template structure quickly. Second, the UAMRT matches each source template with the optimal structure and replaces it with the corresponding target template. the basic idea of the template-based system is to represent all translation knowledge in uniform templates which can be shown as context-free grammar rules. It then translates an English sentence into Chinese with FOPA and UAMRT System evaluation shows encouraging and promising results for quality and speed, and the system may perform better by adding more templates without any other changes.

关键词： jigs(templates) Translation systems parsing tree context-free grammars Translations Translation Translation Process generalized algorithm parsing algorithms English English language system evaluation

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