Shypd.aiThe largest open index of AI toolsETM is an academic research tool for topic modeling in embedding spaces. It defines words and topics within the same embedding space, offering a robust approach to natural language processing tasks.
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ETM (Topic Modeling in Embedding Spaces) is a research tool designed to perform topic modeling by representing words and topics within a unified embedding space. This approach allows for the likelihood of a word under ETM to be modeled as a Categorical distribution, derived from the dot product between the word embedding and its assigned topic's embedding. ETM is particularly effective as a document model, capable of learning interpretable topics and word embeddings. Its design makes it robust against large vocabularies, including those with rare words and stop words, which is a significant advantage in natural language processing. The tool provides scripts for data preprocessing, training, and evaluation, supporting various datasets like 20NewsGroup and New York Times.
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