原创 實體-關係聯合抽取:Incorporating Copying Mechanism in Sequence-to-Sequence Learning
文章標題:https://www.aclweb.org/anthology/P16-1154.pdf 文章題目:Incorporating Copying Mechanism in Sequence-to-Sequence Lea
原创 多標籤分類:Multi-label Text Categorization with Joint Learning Predictions-as-Features Method
文章地址:https://www.aclweb.org/anthology/D15-1099.pdf 文章標題:Multi-label Text Categorization with Joint Learning Predict
原创 實體-關係聯合抽取:CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases
文章地址:https://arxiv.org/pdf/1610.08763.pdf 文章標題:CoType: Joint Extraction of Typed Entities and Relations with Knowle
原创 Java學習手冊:(數據結構與算法-數組)如何求解最小三元組的距離?
問題描述: 已知3個升序整數數組a[l]、b[m]、c[n]。請在3個數組中各找一個元素,使得組成的三元組距離最小。 三元組距離的定義是:假設a[i]、b[j]和c[k]是一個三元組,那麼距離爲Distance=max(|a[i]-b[j
原创 多標籤分類:NEURAL MACHINE TRANSLATION BY JOINTLY LEARNING TO ALIGN AND TRANSLATE
文章地址:https://arxiv.org/pdf/1409.0473.pdf 文章標題:NEURAL MACHINE TRANSLATION BY JOINTLY LEARNING TO ALIGN AND TRANSLATE
原创 實體-關係聯合抽取:Neural Architectures for Named Entity Recognition
文章地址:https://arxiv.org/pdf/1603.01360.pdf 文章標題:Neural Architectures for Named Entity Recognition(命名實體識別的神經結構)NNACL2
原创 Android學習筆記:Material Design
Material Design於2014年的Google I/O 大會上推出,是由谷歌的設計工程師們基於傳統優秀的設計原則,結合豐富的創意和科學技術所發明的一套全新的界面設計語言。在2015年的Google I/O 大會上推出了一
原创 多標籤分類:Google‘s Neural Machine Translation System
文章地址:https://arxiv.org/pdf/1609.08144.pdf 文章標題:Google‘s Neural Machine Translation System: Bridging the Gap between
原创 多標籤分類:Global Encoding for Abstractive Summarization
文章地址:https://arxiv.org/pdf/1805.03989.pdf 代碼地址:https://github.com/lancopku/Global-Encoding 文章標題:Global Encoding for
原创 實體-關係聯合抽取:Incremental Joint Extraction of Entity Mentions and Relations
論文地址:https://www.aclweb.org/anthology/P14-1038.pdf 文章標題:Incremental Joint Extraction of Entity Mentions and Relatio
原创 實體-關係聯合抽取:End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures
論文地址:https://arxiv.org/pdf/1601.00770.pdf 代碼地址:https://github.com/tticoin/LSTM-ER 文章標題:End-to-End Relation Extracti
原创 實體-關係聯合抽取:Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism
論文地址:https://www.aclweb.org/anthology/P18-1047.pdf 通訊作者主頁:http://people.ucas.ac.cn/~zhaojun 論文出處:中國科學院大學 代碼地址:https
原创 實體關係聯合抽取:Supertagging with LSTMs
文章地址:https://www.aclweb.org/anthology/N16-1027.pdf 文章標題:Supertagging with LSTMs(超標註LSTMs)NNACL2016 模型和超標籤代碼:https:/
原创 文本相似度:Bilateral Multi-Perspective Matching for Natural Language Sentences
文章地址:https://arxiv.org/pdf/1702.03814.pdf 文章標題:Bilateral Multi-Perspective Matching for Natural Language Sentences(
原创 實體-關係聯合抽取:Knowledge-Based Weak Supervision for Information Extraction of Overlapping Relations
論文地址:https://www.aclweb.org/anthology/P11-1055.pdf 文章標題:Knowledge-BasedWeak Supervision for Information Extraction