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Word Embeddings

In: Python for Accounting and Finance

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  • Sunil Kumar

Abstract

In recent years, there has been a significant increase in the amount of text data available for accounting research. This has led to a growing interest in using text analysis techniques to extract insights and patterns from large volumes of unstructured data. Word embeddings are a type of vector representation of words in a corpus that capture the semantic and syntactic relationships between them.

Suggested Citation

  • Sunil Kumar, 2024. "Word Embeddings," Springer Books, in: Python for Accounting and Finance, chapter 0, pages 243-248, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-54680-8_15
    DOI: 10.1007/978-3-031-54680-8_15
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