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Information Extraction

1 papers with code · Natural Language Processing

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textTOvec: Deep Contextualized Neural Autoregressive Topic Models of Language with Distributed Compositional Prior

ICLR 2019 pgcool/textTOvec

We address two challenges of probabilistic topic modelling in order to better estimate the probability of a word in a given context, i. e., P(word|context): (1) No Language Structure in Context: Probabilistic topic models ignore word order by summarizing a given context as a "bag-of-word" and consequently the semantics of words in the context is lost.

INFORMATION EXTRACTION INFORMATION RETRIEVAL LANGUAGE MODELLING TOPIC MODELS UNSUPERVISED REPRESENTATION LEARNING WORD EMBEDDINGS