咨询与建议

限定检索结果

文献类型

  • 588 篇 会议
  • 509 篇 期刊文献
  • 17 册 图书

馆藏范围

  • 1,114 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 731 篇 工学
    • 597 篇 计算机科学与技术...
    • 505 篇 软件工程
    • 155 篇 信息与通信工程
    • 104 篇 生物工程
    • 77 篇 电气工程
    • 69 篇 控制科学与工程
    • 53 篇 生物医学工程(可授...
    • 48 篇 建筑学
    • 46 篇 光学工程
    • 44 篇 电子科学与技术(可...
    • 43 篇 土木工程
    • 36 篇 化学工程与技术
    • 29 篇 机械工程
    • 18 篇 动力工程及工程热...
    • 18 篇 航空宇航科学与技...
    • 15 篇 交通运输工程
  • 400 篇 理学
    • 239 篇 数学
    • 110 篇 生物学
    • 95 篇 统计学(可授理学、...
    • 90 篇 物理学
    • 39 篇 化学
    • 38 篇 系统科学
    • 16 篇 大气科学
  • 263 篇 管理学
    • 169 篇 图书情报与档案管...
    • 107 篇 管理科学与工程(可...
    • 39 篇 工商管理
  • 64 篇 医学
    • 57 篇 临床医学
    • 44 篇 基础医学(可授医学...
    • 33 篇 药学(可授医学、理...
  • 35 篇 法学
    • 33 篇 社会学
  • 10 篇 经济学
  • 9 篇 农学
  • 8 篇 教育学
  • 3 篇 文学
  • 1 篇 哲学
  • 1 篇 历史学
  • 1 篇 军事学

主题

  • 50 篇 semantics
  • 37 篇 training
  • 36 篇 data mining
  • 23 篇 knowledge engine...
  • 23 篇 feature extracti...
  • 22 篇 computer science
  • 22 篇 machine learning
  • 22 篇 artificial intel...
  • 21 篇 task analysis
  • 20 篇 computational mo...
  • 19 篇 visualization
  • 17 篇 data engineering
  • 17 篇 knowledge graph
  • 16 篇 ontologies
  • 15 篇 deep learning
  • 15 篇 knowledge manage...
  • 14 篇 conferences
  • 14 篇 convolution
  • 13 篇 ontology
  • 12 篇 forecasting

机构

  • 105 篇 school of comput...
  • 56 篇 department of da...
  • 56 篇 department of da...
  • 43 篇 key laboratory o...
  • 34 篇 school of inform...
  • 29 篇 college of compu...
  • 27 篇 department of ma...
  • 25 篇 key laboratory o...
  • 24 篇 key laboratory o...
  • 22 篇 knowledge and da...
  • 21 篇 school of econom...
  • 21 篇 key laboratory o...
  • 17 篇 key laboratory o...
  • 17 篇 key laboratory o...
  • 16 篇 data and knowled...
  • 15 篇 institute of dat...
  • 15 篇 school of cyber ...
  • 15 篇 faculty of compu...
  • 14 篇 school of comput...
  • 14 篇 college of compu...

作者

  • 50 篇 nürnberger andre...
  • 31 篇 wu xindong
  • 31 篇 wang meng
  • 27 篇 chatterjee soumi...
  • 26 篇 he jun
  • 25 篇 liu hongyan
  • 23 篇 sun geng
  • 23 篇 du xiaoyong
  • 22 篇 speck oliver
  • 21 篇 spanakis gerasim...
  • 21 篇 xindong wu
  • 20 篇 niyato dusit
  • 19 篇 hong richang
  • 19 篇 mehrkanoon siama...
  • 18 篇 browne cameron
  • 18 篇 liu jun
  • 18 篇 o'sullivan decla...
  • 18 篇 wade vincent
  • 17 篇 soemers dennis j...
  • 17 篇 huang qingming

语言

  • 1,059 篇 英文
  • 43 篇 其他
  • 12 篇 中文
检索条件"机构=Data Science and Knowledge Engineering"
1114 条 记 录,以下是51-60 订阅
排序:
Learning-based diagnosis and repair  1
收藏 引用
29th Benelux Conference on Artificial Intelligence, BNAIC 2017
作者: Roos, Nico Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands
This paper proposes a new form of diagnosis and repair based on reinforcement learning. Self-interested agents learn locally which agents may provide a low quality of service for a task. The correctness of learned ass... 详细信息
来源: 评论
Cross-domain neural-kernel networks  31
Cross-domain neural-kernel networks
收藏 引用
31st Benelux Conference on Artificial Intelligence and the 28th Belgian Dutch Conference on Machine Learning, BNAIC/BENELEARN 2019
作者: Mehrkanoon, Siamak Department of Data Science and Knowledge Engineering Maastricht University Netherlands
A novel cross-domain neural-kernel networks architecture for semi-supervised domain adaption problem is introduced. The proposed model consists of two stream neural-kernel networks corresponding to the source and targ... 详细信息
来源: 评论
Grouping abstraction and authority control in policy-based spectrum management
Grouping abstraction and authority control in policy-based s...
收藏 引用
2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks
作者: Feeney, Kevin Lewis, David Argyroudis, Patroklos Nolan, Keith O'Sullivan, Declan Knowledge and Data Engineering Group (KDEG) Department of Computer Science and Statistics TCD Ireland CTVR Ireland Knowledge and Data Engineering Group Department of Computer Science and Statistics Ireland CTVR TCD Ireland
The management of dynamic spectrum access requires the coordination of administrative functions across multiple organizations, from regulators to secondary market operators and commons cooperatives. Policy-based manag... 详细信息
来源: 评论
Maastricht University's Large-Scale Multilingual Machine Translation System for WMT 2021  6
Maastricht University's Large-Scale Multilingual Machine Tra...
收藏 引用
6th Conference on Machine Translation, WMT 2021
作者: Liu, Danni Niehues, Jan Department of Data Science and Knowledge Engineering Maastricht University Netherlands
We present our development of the multilingual machine translation system for the large-scale multilingual machine translation task at WMT 2021. Starting form the provided baseline system, we investigated several tech... 详细信息
来源: 评论
Bridging face and sound modalities through domain adaptation metric learning  27
Bridging face and sound modalities through domain adaptation...
收藏 引用
27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2019
作者: Athanasiadis, Christos Hortal, Enrique Asteriadis, Stylianos Department of Data Science and Knowledge Engineering Maastricht University Netherlands
Robust emotion recognition systems require extensive training by employing huge number of training samples with purpose of generating sophisticated models. Furthermore, research is mostly focused on facial expression ... 详细信息
来源: 评论
Detecting anomalous events over time using RDF triple extraction and a dynamic implementation of oddball  30
Detecting anomalous events over time using RDF triple extrac...
收藏 引用
30th Benelux Conference on Artificial Intelligence, BNAIC 2018
作者: Heinrichs, Benedikt Scholtes, Jan C. Department of Data Science and Knowledge Engineering Maastricht University Netherlands
This paper shows a new approach for anomaly detection by combining the extraction of so-called triples consisting of a subject, predicate, and object using dynamic anomaly-detection. First, the methods used to extract... 详细信息
来源: 评论
Enhancing brain decoding using attention augmented deep neural networks  29
Enhancing brain decoding using attention augmented deep neur...
收藏 引用
29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2021
作者: Abdellaoui, Ismail Alaoui Fernández, Jesús García Sahinli, Caner Mehrkanoon, Siamak Department of Data Science and Knowledge Engineering Maastricht University Netherlands
Neuroimaging techniques have shown to be valuable when studying brain activity. This paper uses Magnetoencephalography (MEG) data, provided by the Human Connectome Project (HCP), and different deep learning models to ... 详细信息
来源: 评论
Synthesizing personality-dependent body postures using generative adversarial networks  31
Synthesizing personality-dependent body postures using gener...
收藏 引用
31st Benelux Conference on Artificial Intelligence and the 28th Belgian Dutch Conference on Machine Learning, BNAIC/BENELEARN 2019
作者: Calsius, Frederik Asteriadis, Stylianos Department of Data Science and Knowledge Engineering Maastricht University Netherlands
In Personality Computing, one of the major goals is to estimate the personality of an individual by making use of computational techniques. Among the existing models that classify personality traits, the Big-5 factor ... 详细信息
来源: 评论
A Semantic Tableau Method for Argument Construction  1
收藏 引用
32nd Benelux Conference on Artificial Intelligence and Belgian-Dutch Conference on Machine Learning, BNAIC/Benelearn 2020
作者: Roos, Nico Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands
A semantic tableau method, called an argumentation tableau, that enables the derivation of arguments, is proposed. First, the derivation of arguments for standard propositional and predicate logic is addressed. Next, ... 详细信息
来源: 评论
Unsupervised Machine Translation On Dravidian Languages  1
Unsupervised Machine Translation On Dravidian Languages
收藏 引用
1st Workshop on Speech and Language Technologies for Dravidian Languages, DravidianLangTech 2021 at 16th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2021
作者: Koneru, Sai Liu, Danni Niehues, Jan Department of Data Science and Knowledge Engineering Maastricht University Netherlands
Unsupervised neural machine translation (UNMT) is beneficial especially for low resource languages such as those from the Dravidian family. However, UNMT systems tend to fail in realistic scenarios involving actual lo... 详细信息
来源: 评论