AI & Machine Learning

Lit2Vec: A Reproducible Workflow for Building a Legally Screened Chemistry Corpus from S2ORC for Downstream Retrieval and Text Mining

Ali Nemati1 day ago30 sec read4 views0 listens

Lit2Vec introduces a reproducible workflow for creating a legally screened chemistry corpus from the Semantic Scholar Open Research Corpus, including full-text articles, paragraph-level embeddings, and metadata. This workflow is crucial for developers and researchers as it ensures compliance with licensing requirements while providing high-quality data for downstream text mining and retrieval tasks. Researchers can now easily replicate the process using provided code and resources, facilitating further advancements in chemical informatics and related fields.

Read the full article at arXiv cs.AI (Artificial Intelligence)

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