Please use this identifier to cite or link to this item:
http://drsr.daiict.ac.in//handle/123456789/985
Title: | Recognic console |
Authors: | Sasidhar, P S Kalyan Mehta, Kavisha |
Keywords: | Vision OCR Analytics Data Pipeline API Database Connectors |
Issue Date: | 2020 |
Citation: | Mehta, Kavisha (2020). Recognic console. Dhirubhai Ambani Institute of Information and Communication Technology. vii, 34 p. (Acc.No: T00900) |
Abstract: | Users leave behind a large amount of data in digital footprints across different channels of engagement & consumption of products & services. Enterprises & governments are investing to adopt technology for efficiently extracting meaningful information from documents that are collected at the source. Traditionally this has been back-office operations & the turnaround time has been spread from a few days to several weeks for absorbing this information & performing certain logical analysis. Recognic identifies, understands & validates the information in various formats from complex document structures&simplifies digital document processing. Recognic is the future of indexing, organizing, storing & extracting intelligence from the documents. The product is designed to understand and extract useful information from complex document structures & parse the information in an easy to ingest JSON, XML, CSV format, or any other legacy databases. It also comes bundled with a smart analytics component to give extraction confidence insights on the documents parsed through it. Hence this M-Tech Project is focused to build a smart analytics dashboard that helps in providing a connected user-experience on top of the core API Product. |
URI: | http://drsr.daiict.ac.in//handle/123456789/985 |
Appears in Collections: | M Tech Dissertations |
Files in This Item:
File | Description | Size | Format | |
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201811080.pdf Restricted Access | 464.49 kB | Adobe PDF | View/Open Request a copy |
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