- 博客(51)
- 资源 (1)
- 收藏
- 关注
RSS订阅翻译 An Industry Evaluation of Embedding-based Entity Alignment
在行业背景下评估了这些最先进的方法，探索了不同规模和偏差的种子映射的影响。除了来自 DBpedia 和 Wikidata 的流行基准之外，我们还贡献和评估了一个新的行业基准，该基准是从两个异构知识图谱 (KG) 中抽取的，用于医疗应用的部署。...
2022-06-25 22:32:09
757
2
翻译 [实体对齐综述]A benchmark and comprehensive survey on knowledge graph entity alignment via representation
过去几年里，由于知识库在人工智能应用中的重要作用，学术界和工业界对知识库的兴趣呈指数级增长。实体对齐是丰富知识库的一项重要任务。本文提供了使用表示学习新方法的代表性实体对齐技术的综合教程式综述。......
2022-06-18 21:55:32
1417
翻译 【实体对齐综述】A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs
实体对齐试图在不同的知识图谱 (KG) 中找到指向同一现实世界对象的实体。KG 嵌入的最新进展推动了基于嵌入的实体对齐方法的出现，它将实体编码到连续嵌入空间中，并根据学习到的嵌入来度量实体的相似性。在本文中，我们对这一新兴领域进行了全面的实验研究。......
2022-06-07 20:12:56
2100
2
翻译 最先进的实体对齐方法的实验研究综述 An Experimental Study of State-of-the-Art Entity Alignment Approaches
实体对齐 (EA) 寻找位于不同知识图谱 (KG) 中的等价实体，这是提高 KG 质量的重要步骤，因此对下游应用程序（例如，问答和推荐）具有重要意义。本研究力求清晰地展示当前 EA 方法的优缺点，以激发高质量的后续研究。......
2022-06-01 11:09:34
1670
转载 loss function, cost function, and objective function
https://stats.stackexchange.com/questions/179026/objective-function-cost-function-loss-function-are-they-the-same-thingThese are not very strict terms and they are highly related. However:Loss function is usually a function defined on a data point, predi
2020-12-31 20:55:19
222
原创 PIQA: Reasoning about Physical Commonsense in Natural Language 笔记+翻译
PIQA: Reasoning about Physical Commonsense in Natural LanguageAAAI 2020Abstractcurrent status: In more physical domains, text is inherently limited due to reporting bias.question to be solved: Ca...
2020-04-17 23:01:28
1465
原创 WINOGRANDE: An Adversarial Winograd Schema Challenge at Scale 笔记+翻译
WINOGRANDE: An Adversarial Winograd Schema Challenge at ScaleAAAI 2020 Best Paper AwardAbstractBefore: WSC (Winograd Schema Challenge) 2011, designed to be unsolvable by statistical models that re...
2020-04-17 22:56:13
3343
1
原创 ConceptNet 5.5：一个开放多语言常识知识图谱 翻译和笔记
2017-AAAI-ConceptNet 5.5: An Open Multilingual Graph of General Knowledgehttps://www.aaai.org/ocs/index.php/AAAI/AAAI17/paper/download/14972/14051摘要： ConceptNet是一个知识图谱，其中自然语言单词和短语通过带标签（表示边的类型）和权重（表示...
2020-01-15 07:16:18
16982
原创 自然语言推理综述 翻译及笔记
Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approacheshttps://www.researchgate.net/profile/Shane_Storks/publication/332169673_Recent_Advances_in_Natural_Lang...
2020-01-13 04:16:00
3741
原创 图神经网络全面综述 阅读笔记+翻译
https://arxiv.org/abs/1901.00596arXiv:1901.00596v3 [cs.LG] 8 Aug 2019A Comprehensive Survey on Graph Neural NetworksZonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, Philip S. Yu摘...
2020-01-10 02:40:21
2016
原创 基于神经网络的知识图谱问答方法 阅读笔记+翻译
2019-arXiv-Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs阅读笔记+翻译摘要：介绍KGQA的挑战、现有方法、进展和趋势。1 IntroductionKGQA（Knowledge Graph Query Answering）：系统提供接口，接受用...
2019-11-23 11:44:39
2902
翻译 Bridging the Gap between Training and Inference for Neural Machine Translation翻译
Bridging the Gap between Training and Inference for Neural Machine Translation 翻译摘要 神经机器翻译（NMT）以根据上下文词生成下一个词的方式顺序生成目标词序列。在训练时，它根据真实（这里及下文的真实都是指训练集中真实的译文句子）上下文进行预测，而在推理时，它必须从头开始生成整个词序列。这种（向模型）送入的上下文的差...
2019-11-05 07:52:33
2896
20
原创 HellaSwag: Can a Machine Really Finish Your Sentence阅读笔记
2019-alc-HellaSwag_Can a Machine Really Finish Your Sentence原文地址：https://arxiv.org/abs/1905.07830swag提出了NLP新任务：commonsense nlp inference。实际上是nlu的一种特例。BERT解决了。于是提出个新数据集，难为BERT，就是HellaSwag。HellaSwag使...
2019-10-19 05:08:06
3306
转载 CHAPTER 25 Advanced Dialog Systems
CHAPTER 25 Advanced Dialog SystemsSpeech and Language Processing ed3 读书笔记In this chapter we describe the dialog-state architecture, also called the belief-state or information-state architecture. Li...
2019-08-19 11:45:25
381
转载 CHAPTER 24 Dialog Systems and Chatbots
CHAPTER 24 Dialog Systems and ChatbotsSpeech and Language Processing ed3 读书笔记Language is the mark conversation of humanity and sentience, and conversation or dialog is the most fundamental and speci...
2019-07-23 18:19:53
408
转载 CHAPTER 23 Question Answering
CHAPTER 23 Question AnsweringSpeech and Language Processing ed3 读书笔记Two major paradigms of question answering—information retrieval-based and knowledge-based.Most question answering systems focus o...
2019-07-21 22:26:35
781
转载 CHAPTER 19 Lexicons for Sentiment, Affect, and Connotation
CHAPTER 19 Lexicons for Sentiment, Affect, and ConnotationSpeech and Language Processing ed3 读书笔记[外链图片转存失败(img-UAOqdFAS-1563455821316)(19.1.png)]We can design extractors for each of these kinds of ...
2019-07-18 21:17:31
1189
转载 CHAPTER 18 Semantic Role Labeling
CHAPTER 18 Semantic Role LabelingSpeech and Language Processing ed3 读书笔记The task of understanding participants and their relationship to events—being able to answer the question “Who did what to who...
2019-07-07 13:42:59
1496
转载 CHAPTER 17 Information Extraction
CHAPTER 17 Information ExtractionSpeech and Language Processing ed3 读书笔记This chapter presents techniques for extracting limited kinds of semantic content from text. This process of information extra...
2019-07-04 21:38:13
1739
转载 CHAPTER 14 The Representation of Sentence Meaning
CHAPTER 14 The Representation of Sentence MeaningSpeech and Language Processing ed3 读书笔记The meaning of linguistic expressions can be captured in formal structures called meaning representations. Cor...
2019-06-23 12:58:01
818
转载 CHAPTER 13 Dependency Parsing
CHAPTER 13 Dependency ParsingSpeech and Language Processing ed3 读书笔记dependency grammars: the syntactic structure of a sentence is described solely in terms of the words (or lemmas) in a sentence an...
2019-06-21 23:05:36
1463
转载 CHAPTER 12 Statistical Parsing
CHAPTER 12 Statistical ParsingSpeech and Language Processing ed3 读书笔记It is possible to build probabilistic models of syntactic knowledge and use some of this probabilistic knowledge tobuild efficie...
2019-06-17 16:26:58
835
1
原创 CHAPTER 11 Syntactic Parsing
CHAPTER 11 Syntactic ParsingSpeech and Language Processing ed3 读书笔记Syntactic parsing is the task of recognizing a sentence and assigning a syntactic structure to it. Parse trees are directly useful...
2019-05-30 19:44:30
985
原创 CHAPTER 10 Formal Grammars of English
CHAPTER 10 Formal Grammars of EnglishSpeech and Language Processing ed3 读书笔记This chapter is hard to be condensed. Just read through it.The word syntax comes from the Greek syˊntaxiss\acute{y}ntaxis...
2019-05-25 22:19:00
1248
原创 CHAPTER 9 Sequence Processing with Recurrent Networks
CHAPTER 9 Sequence Processing with Recurrent NetworksSpeech and Language Processing ed3 读书笔记The weakness of sliding window approach. Distant information are not accessible. Single constituent may ge...
2019-05-19 20:21:06
440
原创 Chapter 8 Part-of-Speech Tagging
Chapter 8 Part-of-Speech TaggingSpeech and Language Processing ed3 读书笔记parts-of-speech: noun, verb, pronoun, preposition, adverb, conjunction, participle, and article.Parts-of-speech (also known as...
2019-05-17 16:16:16
3441
原创 Chapter 7 Neural Networks and Neural Language Models
Chapter 7 Neural Networks and Neural Language ModelsSpeech and Language Processing ed3 读书笔记McCulloch-Pitts neuron (McCulloch and Pitts, 1943)feed-forward network: the computation proceeds iterative...
2019-05-13 06:29:50
513
原创 Chapter 6 Vector Semantics
Chapter 6 Vector SemanticsSpeech and Language Processing ed3 读书笔记Words that occur in similar contexts tend to have similar meanings. This link between similarity in how words are distributed and sim...
2019-05-10 22:12:56
1600
原创 chapter 5 Logistic Regression
chapter 5 Logistic RegressionSpeech and Language Processing ed3 读书笔记Generative and Discriminative Classifiers: The most important difference between naive Bayes and logistic regression is that logis...
2019-05-06 14:23:52
557
原创 Chapter 4 Naive Bayes and Sentiment Classification
Chapter 4 Naive Bayes and Sentiment ClassificationSpeech and Language Processing ed3 读书笔记Text categorization, the task of assigning a label or category to an entire text or document.We focus on one...
2019-05-02 10:51:43
819
原创 Chapter 3 N-gram Language Models
Chapter 3 N-gram Language ModelsSpeech and Language Processing ed3 读书笔记Probabilities are essential inany task in which we have to identify words in noisy, ambiguous input, like speech recognition ...
2019-04-28 13:34:27
850
原创 Chapter 2 Regular Expressions, Text Normalization, Edit Distance
Chapter 2 Regular Expressions, Text Normalization, Edit DistanceSpeech and Language Processing ed3读书笔记text normalization: converting text to a more convenient, standard form.tokenization: separate...
2019-04-24 11:24:31
1233
原创 Chapter 16 Reinforcement Learning
Chapter 16 Reinforcement LearningOReilly. Hands-On Machine Learning with Scikit-Learn and TensorFlow读书笔记This chapter has been revised largely since the book published. So see the jupyter notebook ve...
2019-04-15 19:11:11
4438
原创 Chapter 15 Autoencoders
Chapter 15 AutoencodersOReilly. Hands-On Machine Learning with Scikit-Learn and TensorFlow读书笔记Autoencoders are artificial neural networks capable of learning efficient representations of the input d...
2019-04-09 09:27:22
564
原创 Chapter 14 Recurrent Neural Networks
Chapter 14 Recurrent Neural NetworksOReilly. Hands-On Machine Learning with Scikit-Learn and TensorFlow读书笔记Recurrent Neural Networks (RNNs) is a class of nets that can predict the future.analyze t...
2019-03-31 14:05:24
471
原创 Chapter 13 Convolutional Neural Networks
Chapter 13 Convolutional Neural NetworksOReilly. Hands-On Machine Learning with Scikit-Learn and TensorFlow读书笔记13.1 The Architecture of the Visual CortexMany neurons in the visual cortex have a sma...
2019-03-22 20:27:54
739
原创 Chapter 12 Distributing TensorFlow Across Devices and Servers
Chapter 12 Distributing TensorFlow Across Devices and ServersOReilly. Hands-On Machine Learning with Scikit-Learn and TensorFlow读书笔记12.1 Multiple Devices on a Single Machine12.1.1 InstallationChec...
2019-03-16 10:44:40
668
原创 chapter 11 Training Deep Neural Nets
chapter 11 Training Deep Neural NetsOReilly. Hands-On Machine Learning with Scikit-Learn and TensorFlow读书笔记A chapter that you will never miss a single word. This note thus may miss some import conte...
2019-03-07 16:08:26
22495
原创 Chapter 10 Introduction to Artificial Neural Networks
Chapter 10 Introduction to Artificial Neural NetworksOReilly. Hands-On Machine Learning with Scikit-Learn and TensorFlow读书笔记10.1 From Biological to Artificial NeuronsA huge quantity of data availab...
2019-02-24 23:24:27
483
原创 Chapter 9 Up and Running with TensorFlow
Chapter 9 Up and Running with TensorFlowOReilly. Hands-On Machine Learning with Scikit-Learn and TensorFlow读书笔记TensorFlow first defines in Python a graph of computations to perform, and then takes t...
2019-02-22 20:39:03
319
Shakespeare play
2019-04-18
空空如也
TA创建的收藏夹 TA关注的收藏夹
TA关注的人