检索结果-内蒙古大学图书馆

NLP4KGC 2024 - Proceedings of the 3rd international Workshop on natural language processing for knowledge Graph Creation, co-located with 20th international conference on Semantic Systems, SEMANTiCS 2024

NLP4KGC 2024 - Proceedings of the 3rd International Workshop...

引用

3rd international Workshop on natural language processing for knowledge Graph Creation, NLP4KGC 2024

The proceedings contain 11 papers. The topics discussed include: on the pertinence of LLMs for ontology learning;towards the automation of knowledge graph construction using large language models;assessing SPARQL capabilities of large language models;breaking down financial news impact: a novel ai approach with geometric hypergraphs;ontology learning from text: an analysis on LLM performance;accessing the capabilities of KGs and LLMs in mapping indicators within sustainability reporting standards;converting fire safety regulations to SHACL shapes using natural language processing;ontology-based dataset discovery in the BUILDSPACE data management platform;pruning cycles in UMLS Metathesaurus: a neuro symbolic ai approach;and automated generation of competency questions using large language models and knowledge graphs.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Joint Workshop Proceedings of the 5th international Workshop on a Semantic Data Space for Transport, Sem4Tra 2023 and 2nd NLP4KGC: natural language processing for knowledge Graph Construction, co-located with the 19th international conference on Semantic Systems, SEMANTiCS 2023

Joint Workshop Proceedings of the 5th International Workshop...

引用

Joint Workshop of the 5th international Workshop on a Semantic Data Space for Transport, Sem4Tra 2023 and 2nd natural language processing for knowledge Graph Construction, NLP4KGC 2023

The proceedings contain 9 papers. The topics discussed include: policy patterns for usage control in data spaces;an interaction pattern ontology for data sharing about logistics activities;mobility profiles: a taxonomy for the standardization of mobility data spaces;towards aligning IoT data with domain-specific ontologies through semantic web technologies and NLP;probing large language models for scientific synonyms;effects of pretraining corpora on scientific relation extraction using BERT and SciBERT;framing few-shot knowledge graph completion with large language models;similar papers recommendation for research comparisons;and challenges of entity linking in KGQA datasets.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Data-Product Catalogues: Envisioning with knowledge-aware natural language processing

Data-Product Catalogues: Envisioning with Knowledge-aware Na...

引用

IEEE international conference on Web Services (IEEE ICWS)

作者： Qu, Yutong Yang, Jian Zhang, Wei Emma Chen, Weitong Yu, Hong Qing Univ Adelaide Adelaide SA Australia Macquarie Univ Sydney NSW Australia Univ Derby Derby England

ISBN: (纸本)9798350368567;9798350368550

With the prompt growth of digital data, a newly evolving economy has shown its development trend in today's data-driven world, which is known as the data economy. Stimulating this data economy and seizing benefits from it remains an open question. This paper delves into feasible breakthroughs prompting this emerging data economy in supplying data catalogue services for data products. Accordingly, the opportunities and potential for the application of natural language processing technology in data catalogues are envisaged, corresponding to challenges posed by various types of data assets. By exploring the state-of-the-art natural language processing fields, this paper introduces the latest advancements in knowledge-aware natural language processing for contributing to data catalogues.

关键词： Data Catalogue Data Product Date Economy natural language processing knowledge

来源：评论

学校读者我要写书评

暂无评论

Querying knowledge Graphs in Greek language 17

Querying Knowledge Graphs in Greek Language

引用

17th international conference on PErvasive Technologies Related to Assistive Environments (PETRA)

作者： Tsampos, Ioannis Marakakis, Emmanouil Hellen Mediterranean Univ Dept Elect & Comp Engn Khania Greece

ISBN: (纸本)9798400717604

We present a method for querying knowledge graphs through natural language, emphasizing its application to the Greek language. It integrates NLP techniques with the capabilities of graph databases to enable seamless interaction with knowledge graphs through natural language queries. Upon receiving a user's question in Greek language, we use linguistic analysis tools to convert it into a graph structure by employing predefined rules and adhering to a graph database schema. This methodology enables the handling of different question types and the efficient extraction of relations, ensuring accurate mapping of linguistic structures to database queries. The representation of a question as a knowledge graph enables its direct translation to a Cypher query, facilitating the extraction of related answers. The approach can handle complex questions and is language independent.

关键词： knowledge Graph Construction natural language processing knowledge Representation Question Answering Greek language Graph Databases Query languages

来源：评论

学校读者我要写书评

暂无评论

Distilled BERT Model In natural language processing 14

Distilled BERT Model In Natural Language Processing

引用

14th international conference on Computer and knowledge engineering, ICCKE 2024

作者： Vakili, Yazdan Zandiye Fallah, Avisa Sajedi, Hedieh School of Mathematics Statistics and Computer Science University of Tehran Tehran Iran

ISBN: (纸本)9798331511272

This paper reviews the evolution of natural language processing (NLP) models, concentrating on the distillation techniques used to create efficient and compact versions of large models. Traditional NLP models laid the foundation but had limitations in scalability and contextual understanding. Transformer models like BERT revolutionized NLP but required significant computational resources. This review examines TinyBERT, DistilBERT, MobileBERT, and MiniLM, which balance size and performance through knowledge distillation. These distilled models deliver robust performance while being optimized for use on devices with limited computational resources, enabling the application of advanced NLP features in practical scenarios. ©2024 IEEE.

关键词： natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Research on Computer Intelligent ChatGPT natural language processing System Based on Scientific knowledge Graph 24

Research on Computer Intelligent ChatGPT Natural Language Pr...

引用

international conference on Machine Intelligence and Digital Applications (MIDA)

作者： Zhan, Liuchun Huang, Changjiang Guangzhou Coll Appl Sci & Technol Coll Comp Sci Guangzhou Peoples R China Guangzhou Coll Appl Sci & Technol Res Base Guangdong Social Sci Federat Urban & Rur Guangzhou Peoples R China

ISBN: (纸本)9798400718144

A synonym mining method is proposed by combining the character vector graph and noise robust learning method. The model uses paired word vectors pre-trained by ChatGPT to enhance entity semantic representation. Classify marks with noise. Then the cross optimal processing is carried out to identify the true and false marks. The two-layer construction system of knowledge extraction and knowledge fusion is constructed to realize the independent construction and answer of software engineering questions. The system effectively improves the efficiency of software project understanding and software reuse.

关键词： Software knowledge graph ChatGPT Software knowledge extraction natural language processing system

来源：评论

学校读者我要写书评

暂无评论

Predicting challenge moments from students′ discourse: A comparison of GPT-4 to two traditional natural language processing approaches 24

Predicting challenge moments from students′ discourse: A co...

引用

14th Annual international conference on Learning Analytics and knowledge (LAK) - Learning Analytics in the Age of Artificial Intelligence

作者： Suraworachet, Wannapon Seon, Jennifer Cukurova, Mutlu UCL London England

ISBN: (纸本)9798400716188

Effective collaboration requires groups to strategically regulate themselves to overcome challenges. Research has shown that groups may fail to regulate due to differences in members ' perceptions of challenges which may benefit from external support. In this study, we investigated the potential of leveraging three distinct natural language processing models: an expert knowledge rule-based model, a supervised machine learning (ML) model and a Large language model (LLM), in challenge detection and challenge dimension identification (cognitive, metacognitive, emotional and technical/other challenges) from student discourse, was investigated. The results show that the supervised ML and the LLM approaches performed considerably well in both tasks, in contrast to the rule-based approach, whose efficacy heavily relies on the engineered features by experts. The paper provides an extensive discussion of the three approaches ' performance for automated detection and support of students' challenge moments in collaborative learning activities. It argues that, although LLMs provide many advantages, they are unlikely to be the panacea to issues of the detection and feedback provision of socially shared regulation of learning due to their lack of reliability, as well as issues of validity evaluation, privacy and confabulation. We conclude the paper with a discussion on additional considerations, including model transparency to explore feasible and meaningful analytical feedback for students and educators using LLMs.

关键词： Collaborative learning Discourse analysis natural language processing Challenge moments

来源：评论

学校读者我要写书评

暂无评论

Enhancing knowledge Sharing Workshops with natural language processing in Maintenance Work

Enhancing Knowledge Sharing Workshops with Natural Language ...

引用

international Technical conference on Circuits/Systems, Computers, and Communications (ITC-CSCC)

作者： Ogawa, Riku Inoue, Moritaro Uchihira, Naoshi Japan Adv Inst Sci & Technol 1-1 Asahidai Nomi Ishikawa 9231292 Japan

ISBN: (纸本)9798350379068;9798350379051

In maintenance and inspection work, sharing and leveraging latent and tacit knowledge possessed by field inspectors are crucial for efficient maintenance and skill enhancement. We have developed the smart voice messaging system, which was designed to accumulate and utilize this latent and tacit knowledge, known as "Gen-Ba knowledge," which is difficult to describe as explicit knowledge (e.g. manuals). An effective approach for knowledge sharing is conducting workshops by inspectors using voice messages containing "Gen-Ba knowledge" recorded in the field by smart voice messaging system. Here, it is important that workshops are conducted efficiently and effectively. This study proposes a method to enhance workshop activation using natural language processing technologies. We applied the proposed method to electrical maintenance work and evaluated its effectiveness. A technical contribution elucidates how various large language models can enhance knowledge sharing workshops.

关键词： natural language processing Smart Voice Messaging System knowledge Management System

来源：评论

学校读者我要写书评

暂无评论

A Seamless ChatGPT knowledge Plug-in for the Labour Market

引用

IEEE ACCESS 2024年 12卷 155821-155837页

作者： Alonso, Ruben Dessi, Danilo Meloni, Antonello Murgia, Marco Recupero, Diego Reforgiato Scarpi, Giuseppe R2M Solut Srl I-27100 Pavia Italy Univ Politecn Madrid Ctr Automat & Robot CSIC Programa Doctorado Madrid 28500 Spain Univ Sharjah Coll Comp & Informat Dept Comp Sci Sharjah U Arab Emirates Univ Cagliari Dept Math & Comp Sci I-09124 Cagliari Italy

In today's rapidly evolving labor market, the emergence of new roles and the decline of traditional ones have led to a complex landscape of job titles and skill requirements. This complexity often causes ambiguity and confusion, affecting both novices and experienced professionals. To address this, extensive international efforts have produced reference databases of jobs and skills, such as ESCO and O*NET. However, the challenge remains to make this information easily accessible and interpretable for users with varying levels of expertise. To address the challenge above, this paper introduces a knowledge Plug-in for ChatGPT, designed to serve as an intuitive, user-friendly interface between workers and these authoritative databases. By harnessing the power of natural language processing (NLP), the plug-in enables a seamless question-answering experience, effectively masking the underlying complexity with a carefully engineered architecture. Furthermore, generative AI enhances the user experience by providing relevant information in domains extending beyond the traditional scope of employment. An initial user study demonstrates the plug-in's effectiveness in improving the usability and accuracy of job-related queries. We detail the development, architecture, and validation of this innovative tool, highlighting its potential impact on the future of employment search and career development.

关键词： Chatbots Databases Semantics Recruitment engineering profession Taxonomy Structured Query language Social networking (online) Resumes Employment Large language models natural language processing knowledge based systems Professional aspects Question answering (information retrieval) Query processing Conversational agents labor market large language models natural language processing occupational databases

来源：评论

学校读者我要写书评

暂无评论

Providing a natural language processing App for language Teachers 26th

Providing a Natural Language Processing App for Language Tea...

引用

26th international conference on Interactive Collaborative Learning (ICL) - Towards a Hybrid, Flexible and Socially Engaged Higher Education / 52nd IGIP international conference on engineering Pedagogy

作者： Posekany, Alexandra Dolezal, Dominik TU Vienna Univ Technol Vienna Austria TGM Vienna Inst Technol Vienna Austria Univ Vienna Vienna Austria

ISBN: (纸本)9783031519789;9783031519796

natural language processing (NLP) is a common application for Artificial Intelligence. The goal is to provide language teachers with a simple to apply tool for topic model analyses to integrate into their classroom. The project also involves project based learning for students programming the actual AI web application. The original notion is to provide language teacher with AI methodology without requiring any technical knowledge in AI or any programming skills. natural language processing provides various tools for word frequencies, but also topic modelling, allowing to track the relevance of topics over time in the media or in the literature. In collaboration with University of Technology linguistics, we intend to provide a corpus of classical English and German literature, as well as the option of uploading your own corpus which can be obtained from webscraping or other sources. A team of students of the vocational high school TGM Wien specialised in IT and Software Development is working on the design of the interactive GUI for this NLP application, learning in this way the methods of natural language processing and Artrificial Intelligence in a project based setting. For this the statistical programming language R is utilized which already provides packages with implementation for natural language processing and in addition the shiny package which allows to develop interactie web apps without additional web and app programming. A team of teachers supervises and supports the students during the development process, providing expertise in AI and NLP, in web and app programming, as well as server management. Two intended outcomes exist. Ont the one hand, we want our students to learn natural language processing first hand through development of this application. On the other hand, we intend to obtain an interactive AI tool which can assist language teachers and their students on the long term in the classroom. In times of GPT3 and GPT4 dominating the media and per

关键词： Artificial intelligence natural language processing Interactive web application Project based learning Software development

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：