咨询与建议

限定检索结果

文献类型

  • 57,254 篇 会议
  • 184 册 图书

馆藏范围

  • 57,431 篇 电子文献
  • 7 种 纸本馆藏

日期分布

学科分类号

  • 57,042 篇 工学
    • 56,774 篇 计算机科学与技术...
    • 7,556 篇 控制科学与工程
    • 2,463 篇 软件工程
    • 2,057 篇 电气工程
    • 483 篇 信息与通信工程
    • 360 篇 生物医学工程(可授...
    • 67 篇 机械工程
    • 57 篇 土木工程
    • 23 篇 石油与天然气工程
    • 18 篇 生物工程
    • 15 篇 仪器科学与技术
  • 4,454 篇 理学
    • 3,698 篇 数学
    • 368 篇 物理学
    • 274 篇 生物学
    • 53 篇 科学技术史(分学科...
    • 52 篇 统计学(可授理学、...
    • 22 篇 系统科学
    • 18 篇 化学
  • 2,190 篇 医学
    • 1,233 篇 基础医学(可授医学...
    • 1,065 篇 临床医学
    • 36 篇 特种医学
  • 2,181 篇 文学
    • 2,178 篇 外国语言文学
  • 1,355 篇 管理学
    • 1,256 篇 管理科学与工程(可...
    • 84 篇 图书情报与档案管...
  • 1,231 篇 教育学
    • 709 篇 教育学
    • 507 篇 心理学(可授教育学...
    • 15 篇 体育学
  • 57 篇 法学
    • 56 篇 社会学
  • 36 篇 艺术学
    • 36 篇 音乐与舞蹈学
  • 35 篇 哲学
    • 35 篇 哲学
  • 13 篇 经济学
  • 1 篇 农学
  • 1 篇 军事学

主题

  • 1,258 篇 artificial intel...
  • 1,112 篇 machine learning
  • 978 篇 deep learning
  • 919 篇 data mining
  • 780 篇 multi agent syst...
  • 725 篇 semantics
  • 527 篇 classification
  • 510 篇 reinforcement le...
  • 474 篇 learning systems
  • 463 篇 clustering
  • 439 篇 neural networks
  • 415 篇 ontology
  • 353 篇 natural language...
  • 257 篇 computers
  • 249 篇 rough sets
  • 236 篇 fuzzy sets
  • 230 篇 feature selectio...
  • 219 篇 computer circuit...
  • 213 篇 knowledge repres...
  • 205 篇 logic programmin...

机构

  • 191 篇 univ chinese aca...
  • 107 篇 chinese acad sci...
  • 65 篇 harbin inst tech...
  • 63 篇 polish acad sci ...
  • 62 篇 wroclaw univ sci...
  • 59 篇 soochow univ sch...
  • 55 篇 delft univ techn...
  • 53 篇 carnegie mellon ...
  • 48 篇 beijing univ tec...
  • 44 篇 chinese acad sci...
  • 44 篇 shanghai jiao to...
  • 43 篇 tu wien austria
  • 42 篇 univ sci & techn...
  • 41 篇 czech tech univ ...
  • 40 篇 univ ulsan sch e...
  • 39 篇 beijing jiaotong...
  • 38 篇 tsinghua univ de...
  • 38 篇 north carolina s...
  • 37 篇 nanjing univ sta...
  • 36 篇 tsinghua univ sc...

作者

  • 47 篇 gelbukh alexande...
  • 42 篇 wang lei
  • 36 篇 reis luis paulo
  • 35 篇 pelachaud cather...
  • 35 篇 malerba donato
  • 34 篇 liu yang
  • 33 篇 novais paulo
  • 33 篇 cpalka krzysztof
  • 32 篇 li li
  • 30 篇 ricci alessandro
  • 27 篇 lau nuno
  • 26 篇 wang hui
  • 26 篇 napoli amedeo
  • 25 篇 boryczka urszula
  • 25 篇 rutkowski leszek
  • 25 篇 wang jing
  • 25 篇 pluhacek michal
  • 25 篇 bickmore timothy
  • 25 篇 calvo hiram
  • 24 篇 villasenor-pined...

语言

  • 57,321 篇 英文
  • 116 篇 中文
  • 1 篇 丹麦文
检索条件"丛书名=Lecture notes in artificial intelligence,"
57438 条 记 录,以下是241-250 订阅
排序:
Cross-Lingual Summarization of Speech-to-Speech Translation: A Baseline  26th
Cross-Lingual Summarization of Speech-to-Speech Translation:...
收藏 引用
26th International Conference on Speech and Computer
作者: Karande, Pranav Sarkar, Balaram Maurya, Chandresh Kumar Indian Inst Technol Indore Indore India
Cross-lingual speech-to-speech translation, which enables spoken language conversion from one language to another, plays a pivotal role in overcoming language barriers and promoting cross-cultural communication. The p...
来源: 评论
Marking: Visual Grading with Highlighting Errors and Annotating Missing Bits  25th
Marking: Visual Grading with Highlighting Errors and Annotat...
收藏 引用
25th International Conference on artificial intelligence in Education (AIED)
作者: Sonkar, Shashank Liu, Naiming Mallick, Debshila B. Baraniuk, Richard G. Rice Univ Houston TX 77005 USA
In this paper, we introduce "Marking", a novel grading task that enhances automated grading systems by performing an in-depth analysis of student responses and providing students with visual highlights. Unli...
来源: 评论
Only One Relation Possible? Modeling the Ambiguity in Temporal Relation Extraction  13th
Only One Relation Possible? Modeling the Ambiguity in Tempor...
收藏 引用
13th International Conference on Natural Language Processing and Chinese Computing
作者: Hu, Yutong Huang, Quzhe Feng, Yansong Peking Univ Wangxuan Inst Comp Technol Beijing Peoples R China State Key Lab Gen Artificial Intelligence Beijing Peoples R China
Event Temporal Relation Extraction (ETRE) aims to identify the temporal relationship between two events. Most previous works follow a single-label classification paradigm, classifying an event pair into either a well-...
来源: 评论
Evaluating Human-Large Language Model Alignment in Group Process  13th
Evaluating Human-Large Language Model Alignment in Group Pro...
收藏 引用
13th International Conference on Natural Language Processing and Chinese Computing
作者: He, Yidong Liu, Yongbin Ouyang, Chunping Liu, Huan Han, Wenyong Gao, Yu Zhu, Chi Tang, Yi Zhong, Jin Zhou, Shuda Huang, Le Univ South China Sch Comp Hengyang Peoples R China
Exploring the alignment of multi-agent systems with human values during group process is an essential step towards the development of artificial general intelligence. In this work, we present a novel approach to syste... 详细信息
来源: 评论
Assessment of Children's Ability to Manifest Emotions in Facial Expressions, Voice and Speech by Humans, Automatic, and on a Likert Scale  26th
Assessment of Children's Ability to Manifest Emotions in Fac...
收藏 引用
26th International Conference on Speech and Computer
作者: Lyakso, Elena Frolova, Olga Matveev, Anton Nikolaev, Aleksandr Nersisson, Ruban St Petersburg State Univ Child Speech Res Grp St Petersburg Russia Vellore Inst Technol Sch Elect Engn Vellore Tamil Nadu India
The goal of the study was to assess children's ability to manifest emotions in facial expressions and speech by humans, automatic and using Likert scale scores. To achieve this goal, two studies were conducted. Th...
来源: 评论
Identifying and Mitigating Algorithmic Bias in Student Emotional Analysis  25th
Identifying and Mitigating Algorithmic Bias in Student Emoti...
收藏 引用
25th International Conference on artificial intelligence in Education (AIED)
作者: Ashwin, T. S. Biswas, Gautam Vanderbilt Univ 221 Kirkland Hall Nashville TN 37235 USA
Algorithmic bias in educational environments has garnered increasing scrutiny, with numerous studies highlighting its significant impacts. This research contributes to the field by investigating algorithmic biases, i....
来源: 评论
CEUS: Comment Emotion and User Stance Fusion Network for Fake News Detection  13th
CEUS: Comment Emotion and User Stance Fusion Network for Fak...
收藏 引用
13th International Conference on Natural Language Processing and Chinese Computing
作者: Geng, Ning Tan, Zhenhua Zhang, Tao Wu, Danke Northeastern Univ Software Engn Coll Shenyang 110004 Liaoning Peoples R China
Online social platforms provide people with a new way of communication and exchange, and also make the rapid spread of fake news possible. Therefore, automatic detection of fake news has become crucial. Most existing ...
来源: 评论
DuFCALF: Instilling Sentience in Computerized Song Analysis  26th
DuFCALF: Instilling Sentience in Computerized Song Analysis
收藏 引用
26th International Conference on Speech and Computer
作者: Mukherjee, Himadri Marciano, Matteo Dhar, Ankita Roy, Kaushik West Bengal State Univ Dept Comp Sci Barasat India New York Univ Abu Dhabi Dept Arts & Humanities Gazelien Records Lab Mus Program Abu Dhabi U Arab Emirates Sister Nivedita Univ Dept Comp Sci & Engn Chakpachuria India
Music recommendation systems have evolved significantly in the past couple of years and have become extremely popular with the advancement of artificial intelligence (AI). Such systems categorize songs based on dispar... 详细信息
来源: 评论
Enhancing Logical Rules Based on Self-Distillation for Document-Level Relation Extraction  13th
Enhancing Logical Rules Based on Self-Distillation for Docum...
收藏 引用
13th International Conference on Natural Language Processing and Chinese Computing
作者: Mao, Yanxu Cui, Tiehan Ding, Ying Henan Univ Sch Software Kaifeng Peoples R China Henan Inst Sci & Technol Sch Comp Sci & Technol Xinxiang Henan Peoples R China
Document-level Relation Extraction (DocRE) aims to identify and extract relations between entities from entire documents. Unlike sentence-level relation extraction, document-level relation extraction requires consider...
来源: 评论
Low-Resource Event Causality Identification With Global Consistency Constraints  13th
Low-Resource Event Causality Identification With Global Cons...
收藏 引用
13th International Conference on Natural Language Processing and Chinese Computing
作者: Ning, Kangyun Liu, Jian Xu, Jinan Beijing Jiaotong Univ Beijing Key Lab Traff Data Anal & Min Beijing Peoples R China
Event causality identification (ECI) primarily involves discerning causal relations between pairs of events within sentences. However, previous methods heavily rely on large volumes of high-quality annotated data, mak...
来源: 评论