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Extractive Summarization using Continuous Vector Space Models
Mikael Kågebäck
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Olof Mogren
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Nina Tahmasebi
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Devdatt Dubhashi
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Paper Details:
Month: April
Year: 2014
Location: Gothenburg, Sweden
Venue:
CVSC |
WS |
Citations
URL
Learning to Distill: The Essence Vector Modeling Framework
Kuan-Yu Chen
|
Shih-Hung Liu
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Berlin Chen
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Hsin-Min Wang
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AttSum: Joint Learning of Focusing and Summarization with Neural Attention
Ziqiang Cao
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Wenjie Li
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Sujian Li
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Furu Wei
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Yanran Li
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Extractive Summarization Using Multi-Task Learning with Document Classification
Masaru Isonuma
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Toru Fujino
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Junichiro Mori
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Yutaka Matsuo
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Ichiro Sakata
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BanditSum: Extractive Summarization as a Contextual Bandit
Yue Dong
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Yikang Shen
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Eric Crawford
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Herke van Hoof
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Jackie Chi Kit Cheung
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Evolutionary Data Measures: Understanding the Difficulty of Text Classification Tasks
Edward Collins
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Nikolai Rozanov
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Bingbing Zhang
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A Repository of Corpora for Summarization
Franck Dernoncourt
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Mohammad Ghassemi
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Walter Chang
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Ranking Sentences for Extractive Summarization with Reinforcement Learning
Shashi Narayan
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Shay B. Cohen
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Mirella Lapata
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Abstractive Multi-Document Summarization via Phrase Selection and Merging
Lidong Bing
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Piji Li
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Yi Liao
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Wai Lam
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Weiwei Guo
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Rebecca Passonneau
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Optimizing an Approximation of ROUGE - a Problem-Reduction Approach to Extractive Multi-Document Summarization
Maxime Peyrard
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Judith Eckle-Kohler
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A Unified Model for Extractive and Abstractive Summarization using Inconsistency Loss
Wan-Ting Hsu
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Chieh-Kai Lin
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Ming-Ying Lee
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Kerui Min
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Jing Tang
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Min Sun
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Towards Opinion Summarization from Online Forums
Ying Ding
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Jing Jiang
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Extractive Summarization by Aggregating Multiple Similarities
Olof Mogren
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Mikael Kågebäck
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Devdatt Dubhashi
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Multi-Document Summarization of Persian Text using Paragraph Vectors
Morteza Rohanian
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ExB Text Summarizer
Stefan Thomas
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Christian Beutenmüller
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Xose de la Puente
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Robert Remus
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Stefan Bordag
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Centroid-based Text Summarization through Compositionality of Word Embeddings
Gaetano Rossiello
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Pierpaolo Basile
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Giovanni Semeraro
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Macquarie University at BioASQ 5b – Query-based Summarisation Techniques for Selecting the Ideal Answers
Diego Mollá
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DocTag2Vec: An Embedding Based Multi-label Learning Approach for Document Tagging
Sheng Chen
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Akshay Soni
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Aasish Pappu
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Yashar Mehdad
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http://metaoptimize.com/projects/wordreprs/
https://code.google.com/p/word2vec/
http://nlp.stanford.edu/
http://nlp.stanford.edu/software/lex-parser.shtml
Field Of Study
Linguistic Trends
Embeddings
Task
Syntactic Parsing
Summarization
Approach
Deep Learning
Language
English
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