R-universe search: needs:antiword

Showing 7 of total 7 results (show query)

quanteda

readtext:Import and Handling for Plain and Formatted Text Files

Functions for importing and handling text files and formatted text files with additional meta-data, such including '.csv', '.tab', '.json', '.xml', '.html', '.pdf', '.doc', '.docx', '.rtf', '.xls', '.xlsx', and others.

Maintained by Kenneth Benoit. Last updated 4 months ago.

encoding quanteda text

122 stars 10.66 score 1.2k scripts 5 dependents

hegghammer

daiR:Interface with Google Cloud Document AI API

R interface for the Google Cloud Services 'Document AI API' <https://cloud.google.com/document-ai/> with additional tools for output file parsing and text reconstruction. 'Document AI' is a powerful server-based OCR service that extracts text and tables from images and PDF files with high accuracy. 'daiR' gives R users programmatic access to this service and additional tools to handle and visualize the output. See the package website <https://dair.info/> for more information and examples.

Maintained by Thomas Hegghammer. Last updated 5 months ago.

google-cloud ocr

42 stars 6.77 score 40 scripts

michalovadek

eurlex:Retrieve Data on European Union Law

Access to data on European Union laws and court decisions made easy with pre-defined 'SPARQL' queries and 'GET' requests. See Ovadek (2021) <doi:10.1080/2474736X.2020.1870150> .

Maintained by Michal Ovadek. Last updated 7 months ago.

courts eurlex european-union law legislation sparql

36 stars 6.05 score 21 scripts

massimoaria

tall:Text Analysis for All

An R 'shiny' app designed for diverse text analysis tasks, offering a wide range of methodologies tailored to Natural Language Processing (NLP) needs. It is a versatile, general-purpose tool for analyzing textual data. 'tall' features a comprehensive workflow, including data cleaning, preprocessing, statistical analysis, and visualization, all integrated for effective text analysis.

Maintained by Massimo Aria. Last updated 10 days ago.

r-shiny text-analysis-and-sentiment-analysis text-classification text-mining textual-analysis cpp

15 stars 5.15 score

chaoliu-cl

textAnnotatoR:Interactive Text Annotation Tool with 'shiny' GUI

A comprehensive text annotation tool built with 'shiny'. Provides an interactive graphical user interface for coding text documents, managing code hierarchies, creating memos, and analyzing coding patterns. Features include code co-occurrence analysis, visualization of coding patterns, comparison of multiple coding sets, and export capabilities. Supports collaborative qualitative research through standardized annotation formats and analysis tools.

Maintained by Chao Liu. Last updated 5 days ago.

4.48 score 5 scripts

albgarre

FSK2R:An Interface Between the 'FSKX' Standard and 'R'

Functions for importing, creating, editing and exporting 'FSK' files <https://foodrisklabs.bfr.bund.de/fskx-food-safety-knowledge-exchange-format/> using the 'R' programming environment. Furthermore, it enables users to run simulations contained in the 'FSK' files and visualize the results.

Maintained by Alberto Garre. Last updated 3 years ago.

2.70 score 6 scripts

harry-maan

warabandi:Roster Generation of Turn for Weekdays:'warabandi'

It generates the roster of turn for an outlet which is flowing (water) 24X7 or 168 hours towards the area under command or agricutural area (to be irrigated). The area under command is differentially owned by different individual farmers. The Outlet runs for free of cost to irrigate the area under command 24X7. So, flow time of the outlet has to be divided based on an area owned by an individual farmer and the location of his land or farm. This roster is known as 'warabandi' and its generation in agriculture practices is a very tedious task. Calculations of time in microseconds are more error-prone, especially whenever it is performed by hands. That division of flow time for an individual farmer can be calculated by 'warabandi'. However, it generates a full publishable report for an outlet and all the farmers who have farms subjected to be irrigated. It reduces error risk and makes a more reproducible roster. For more details about warabandi system you can found elsewhere in Bandaragoda DJ(1995) <https://publications.iwmi.org/pdf/H_17571i.pdf>.

Maintained by Harvinder Singh. Last updated 4 years ago.

2.00 score 2 scripts