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https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4179Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ubewikkrama, P.T.R. | - |
| dc.date.accessioned | 2021-07-22T06:24:19Z | - |
| dc.date.available | 2021-07-22T06:24:19Z | - |
| dc.date.issued | 2021-07-22 | - |
| dc.identifier.uri | http://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4179 | - |
| dc.description.abstract | Mobile phones became a common device to everyone. There are 6 billion smartphone users in 2019. Because of that most of the time people tend to buy items through the mobile phone. Billions of online transactions happen each and every day.All generate e-invoices. People tend to use e-invoices rather than paper-based invoices. However the processing of those e-invoices is very hard. Most of the time need to enter the e-invoice data into computers manually.Because no relationship between text elements makes automatic analysing PDF is very hard.To handle billions of invoices industry spend billions of money. By this research we introduce novel algorithm which was language independent and can be used to identify ”Key-word , Value” pair data automatically | en_US |
| dc.language.iso | en | en_US |
| dc.subject | e-invoices | en_US |
| dc.subject | Algorithms | en_US |
| dc.subject | Automatic invoice data | en_US |
| dc.subject | Identification of keyword and value | en_US |
| dc.title | Automatic invoice Data identification with relations | en_US |
| dc.type | Thesis | en_US |
| Appears in Collections: | 2019 | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2015 CS 136.pdf | 681.62 kB | Adobe PDF | View/Open |
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