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Found 4 papers, 1 papers with code
Diachronic word embeddings and semantic shifts: a survey
Recent years have witnessed a surge of publications aimed at tracing temporal changes in lexical semantics using distributional methods, particularly prediction-based word embedding models.
Temporal Word Analogies: Identifying Lexical Replacement with Diachronic Word Embeddings
One well-known property of word embeddings is that they are able to effectively model traditional word analogies ({``}word $w_1$ is to word $w_2$ as word $w_3$ is to word $w_4${''}) through vector addition.
Helping News Editors Write Better Headlines: A Recommender to Improve the Keyword Contents & Shareability of News Headlines
We present a software tool that employs state-of-the-art natural language processing (NLP) and machine learning techniques to help newspaper editors compose effective headlines for online publication.
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