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Decomposition

In text analysis and document processing tasks, decomposition refers to breaking down a document or dataset into smaller, more manageable units for analysis or extraction. This markdown file explores different approaches to decomposition based on various factors such as file type, line granularity, document level, and document specificity.

Per Filetype

Decomposing documents based on their file types can be an effective approach to handle different formats and extract relevant information. Here are some examples of file types and their associated decomposition approaches:

  • PDF: PDF documents require specialized parsing libraries to handle their complex structure and extract text, images, tables, and other components.
  • XML: XML documents have a hierarchical structure that can be parsed to extract specific elements or attributes based on analysis or information retrieval needs.
  • DOCX, DOC: Word documents (DOCX and DOC) have unique structures, and parsing them allows the extraction of text, formatting, tables, and other document-specific elements.
  • CSV, TXT: CSV and TXT files contain structured or plain text data, which can be extracted by parsing the content line by line or using delimiter-based approaches.
  • HTML, XLS: HTML and XLS files require parsing techniques to extract text, tables, links, or other relevant information embedded within their specific file formats.
  • PPTX, PNG: Presentation files (PPTX) and image files (PNG) have distinct structures, and decomposing them allows the extraction of slides, images, text content, and other elements.

Each file type requires specific techniques and libraries for effective decomposition and extraction. Understanding the characteristics of the file type is crucial for performing accurate and meaningful analysis.

Per Line

Decomposing documents at the line level provides a granular approach for text analysis or processing. It allows processing line by line or page by page, depending on the specific requirements. This level of decomposition is useful when fine-grained analysis or extraction is necessary. It enables detailed examination of each line or page of the document.

Per Document

Sometimes it is necessary to process an entire document or website as a single unit. Decomposing at the document level can provide a broader context and allow for a comprehensive analysis. This approach is particularly useful when analyzing the overall structure, themes, or patterns within the document or website. The document-level decomposition facilitates a holistic understanding of the text.

Document Specific

In certain cases, it is beneficial to perform decomposition specifically tailored to certain document types. Each document type may have its own specific document structure, context and key elements. By employing document-specific decomposition techniques, we can effectively extract the desired information from these documents, providing insights for document-specific use cases.

OCR

Many documents have different formats, be it unstructured data, structured data, or semi-structured data. Documents contain tables, handwriting, buttons, checkboxes, and each document may contain key information that a user would like to extract. We leverage OCR (Optical Character Recognition) capabilities to convert many of these raw documents into a CSV, with labels in required areas.

OCR technology allows the extraction of text from scanned documents, images, or even handwritten notes. By applying OCR to these documents, we can extract the textual information and convert it into a structured format like a CSV. By leveraging OCR alongside other decomposition techniques, we can effectively handle a wide range of document formats and extract valuable information in a structured manner.