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Generative Topic Embedding: a Continuous Representation of Documents
Shaohua Li
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Tat-Seng Chua
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Jun Zhu
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Chunyan Miao
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Paper Details:
Month: August
Year: 2016
Location: Berlin, Germany
Venue:
ACL |
Citations
URL
Integrating Topic Modeling with Word Embeddings by Mixtures of vMFs
Ximing Li
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Jinjin Chi
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Changchun Li
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Jihong Ouyang
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Bo Fu
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Latent Topic Embedding
Di Jiang
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Lei Shi
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Rongzhong Lian
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Hua Wu
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Rotated Word Vector Representations and their Interpretability
Sungjoon Park
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JinYeong Bak
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Alice Oh
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SCDV : Sparse Composite Document Vectors using soft clustering over distributional representations
Dheeraj Mekala
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Vivek Gupta
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Bhargavi Paranjape
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Harish Karnick
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attr2vec: Jointly Learning Word and Contextual Attribute Embeddings with Factorization Machines
Fabio Petroni
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Vassilis Plachouras
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Timothy Nugent
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Jochen L. Leidner
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Neural Sparse Topical Coding
Min Peng
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Qianqian Xie
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Yanchun Zhang
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Hua Wang
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Xiuzhen Zhang
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Jimin Huang
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Gang Tian
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https://github.com/askerlee/topicvec
https://github.com/datquocnguyen/LFTM/
https://radimrehurek.com/gensim/models/ldamodel.html
http://www.cs.cmu.edu/chongw/slda/
https://github.com/datquocnguyen/LFTM/
https://radimrehurek.com/gensim/models/doc2vec.html
https://github.com/largelymfs/topical
https://github.com/rajarshd/Gaussian
http://qwone.com/jason/20Newsgroups/
http://www.nltk.org/book/ch02.html
http://scikit-learn.org/stable/modules/svm.html
http://www.nytimes.com/2015/09/21/business/a-huge-
https://github.com/askerlee/topicvec/blob/
Field Of Study
Linguistic Trends
Embeddings
Task
Summarization
Approach
Topic Modeling
Generative Model
Dataset
News
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