Aligning Gaussian-Topic with Embedding Network for Summarization Ranking
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Linjing Wei | Heyan Huang | Xiaochi Wei | Yang Gao | Chong Feng | Xiaochi Wei | Yang Gao | Heyan Huang | Chong Feng | Linjing Wei
[1] Larry P. Heck,et al. Contextual LSTM (CLSTM) models for Large scale NLP tasks , 2016, ArXiv.
[2] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[3] Franz Josef Och,et al. Minimum Error Rate Training in Statistical Machine Translation , 2003, ACL.
[4] Eduard H. Hovy,et al. The Automated Acquisition of Topic Signatures for Text Summarization , 2000, COLING.
[5] Dianne P. O'Leary,et al. Topic-Focused Multi-Document Summarization Using an Approximate Oracle Score , 2006, ACL.
[6] Daraksha Parveen,et al. Topical Coherence for Graph-based Extractive Summarization , 2015, EMNLP.
[7] Zhiyuan Liu,et al. Topical Word Embeddings , 2015, AAAI.
[8] Sanda M. Harabagiu,et al. Topic themes for multi-document summarization , 2005, SIGIR '05.
[9] Yan Liu,et al. Query-Oriented Multi-Document Summarization via Unsupervised Deep Learning , 2012, AAAI.
[10] Regina Barzilay,et al. Catching the Drift: Probabilistic Content Models, with Applications to Generation and Summarization , 2004, NAACL.
[11] Hsin-Hsi Chen,et al. Leveraging word embeddings for spoken document summarization , 2015, INTERSPEECH.
[12] Quoc V. Le,et al. Distributed Representations of Sentences and Documents , 2014, ICML.
[13] Min Yang,et al. Ordering-Sensitive and Semantic-Aware Topic Modeling , 2015, AAAI.
[14] Heng Ji,et al. A Novel Neural Topic Model and Its Supervised Extension , 2015, AAAI.
[15] Ani Nenkova,et al. A compositional context sensitive multi-document summarizer: exploring the factors that influence summarization , 2006, SIGIR.
[16] Chris H. Q. Ding,et al. Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization , 2008, SIGIR '08.
[17] Rajarshi Das,et al. Gaussian LDA for Topic Models with Word Embeddings , 2015, ACL.
[18] Ani Nenkova,et al. Measuring Importance and Query Relevance in Topic-focused Multi-document Summarization , 2007, ACL.
[19] Jie Tang,et al. Multi-topic Based Query-Oriented Summarization , 2009, SDM.
[20] Hayato Kobayashi,et al. Summarization Based on Embedding Distributions , 2015, EMNLP.
[21] Michel Galley,et al. A Skip-Chain Conditional Random Field for Ranking Meeting Utterances by Importance , 2006, EMNLP.
[22] Eduard H. Hovy,et al. Automatic Evaluation of Summaries Using N-gram Co-occurrence Statistics , 2003, NAACL.
[23] Jeffrey Dean,et al. Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.
[24] Devdatt P. Dubhashi,et al. Extractive Summarization using Continuous Vector Space Models , 2014, CVSC@EACL.
[25] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[26] Wenpeng Yin,et al. Optimizing Sentence Modeling and Selection for Document Summarization , 2015, IJCAI.
[27] Joshua Goodman,et al. Multi-Document Summarization by Maximizing Informative Content-Words , 2007, IJCAI.