You searched for text summarization
Text summarization is the task of creating short, accurate, and fluent summaries from larger text documents. Recently deep learning methods have proven effective at the abstractive approach to text summarization. In this post, you will discover three different models that build on top of the effective Encoder-Decoder architecture developed for sequence-to-sequence prediction in machine translation. […]
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You searched for text summarization
Text summarization is the task of creating short, accurate, and fluent summaries from larger text documents. Recently deep learning methods have pro
You searched for summarization
Text summarization is the task of creating short, accurate, and fluent summaries from larger text documents. Recently deep learning methods have pro
RBM-An approach for text summarization using deep learning algorithm
Padmapriya G, Duraiswamy K. AN APPROACH FOR TEXT SUMMARIZATION USING DEEP LEARNING ALGORITHM[J]. Journal of Computer Science, 2014, 10(1):1-9. ##A
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Language modeling is central to many important natural language processing tasks. Recently, neural-network-based language models have demonstrated b
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The encoder-decoder model provides a pattern for using recurrent neural networks to address challenging sequence-to-sequence prediction problems suc
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Develop a Deep Learning Model to Automatically Translate from German to English in Python with Keras, Step-by-Step. Machine translation is a challen
A Hierarchical End-to-End Model for Jointly Improving Text Summarization and Sentiment Classificatio
abstract 文字摘要和情感分類都是要捕獲文字的重要資訊，但是在不同的水平上的。文字摘要是用一些句子表示原始文件，情感分類是給文字貼標籤。 提出層次級的端到端模型進行摘要抽取和情感分類的聯合學習，標籤是作為文字摘要抽取的輸出，情感分類依賴於摘要抽取， 情感分類放在摘要
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Learning Structured Representation for Text Classification via Reinforcement Learning 學習筆記
ctu recursive fec 註釋 css 進攻 imp column converge Representation learning ： 表征學習，端到端的學習 pre-specified 預先指定的 demonstrate 論證;證明，證實;顯示
Framework of Automatic Text Summarization Using Reinforcement Learning
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A Survey on Automatic Text Summarization
#A Survey on Automatic Text Summarization ##1.自動文字摘要的定義 Text summarization is compress the source text into a diminished version conserving it
論文閱讀 | MIX: Multi-Channel Information Crossing for Text Matching
MIX: Multi-Channel Information Crossing for Text Matching （騰訊2018 KDD） 主要特點： 1.本文中對於句子匹配，考慮了很多不同層面的：詞，短語，句法，詞頻和權重，語法信心等資訊 2.通過多通道將所有資
[Bash] Search for Text with `grep`
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Investigating Capsule Networks with Dynamic Routing for Text Classification
探索使用動態路由的膠囊網路進行文字分類，提出三種策略穩定動態路由來減輕噪音膠囊的分佈，這些膠囊可能包含背景資訊，或是訓練不好。膠囊網路獲得很好的分類效果，而且訓練多標籤的效果好於單標籤 1 Introduction 文章或是句子建模是NLP的基礎問題，如果組成，層次，結構都考慮的話，很是複雜
Understanding Feature Engineering (Part 3) — Traditional Methods for Text Data
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《Character-level convolutional networks for text classification》論文網路結構解讀
1.資料 比如有一條資料【x=“Simultaneous Tropical Storms are Very Rare”】.則把該句子的大寫字母全部表示成小寫，構建char字符集的詞彙表如下（這裡詞彙表長度為70（69+1，即其他的不在詞彙表的表示為0））： 資料可以表示為x=70X
Recurrent Neural Network for Text Classification with Multi-Task Learning
引言 Pengfei Liu等人在2016年的IJCAI上發表的論文，論文提到已存在的網路都是針對單一任務進行訓練，但是這種模型都存在問題，即缺少標註資料，當然這是任何機器學習任務都面臨的問題。 為了應對資料量少，常用的方法是使用一個無監督的預訓練模型，比如詞向量，實驗中也取得了不錯
Week1.3 Simple deep learning for text classification
Neural networks for words（and characters) 在本節中我們將學習如何將神經網路用於文字分類，還將學習卷積神經網路相關的原理. 回顧–Bag of words way 在前面課程中，我們學習瞭如何將一段文本當作一系列word
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