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Big Unstructured Text Data Multipart/Form-Data Interaction with REST API

IP.com Disclosure Number: IPCOM000242955D
Publication Date: 2015-Sep-02
Document File: 2 page(s) / 81K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a program developed in R to improve user interaction with a web interface form user interface with a large amount of data. After the user compiles the text, the unstructured text is used with this solution to save cycles and increase productivity by analyzing hundreds or thousands of records through the web interface Application Programming Interface (API).

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 52% of the total text.

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-Data Interaction with REST API

Data Interaction with REST API

When interacting with a web interface form in a user interface (UI) with a large amount of data, a user must manually copy-and-paste information, as needed. This is a tedious and time-consuming process.

The novel solution is a program developed in the R programming language and software environment for statistical computing and graphics , to improve user interaction

/Form

Form-

Big Unstructured Text Data Multipart /

with a web interface form UI with a large amount of data . When a user mines unstructured text, the program enables the user to interact with the web interface

Application Programming Interface (API) and obtain the results back into the R console . The core components of the program are to :


• Load unstructured data to be able to post Multipart /Form-data on JavaScript* Object Notation (JSON) to PI from R

• Clean up JSON input from web interface UI • Reshape JSON input from web interface UI into *.CSV
• Reformat fields naming convention to make it readable and export to file for

analysis

Figure 1: High-Level Overview

To prepare for the process, the user has to compile the unstructured text for processing by the web interface API. Once compiled, the unstructured text is used with this solution to save cycles and increase productivity by analyzing hundreds or thousands of records through the web interface API. Using this solution is simple, because functions have been created by simplifying most of the steps that would need to be taken by the user.

To implement the solution in a preferred embodiment :

1. R package install (>= 2.15.0)

2. Automatically load and install necessary packages...