Learn about the Kailing OCR intelligent data extraction platform: advantages and usage tips

In the era of the digital economy, the production and operating models of enterprises have undergone tremendous changes. In order to improve the level of digital financial management, achieve deep integration of business-finance-tax, and drive the overall digital transformation of enterprises, enterprises need to leverage modern information technology. To solve these problems,Kailing Technology OCR Intelligent Data Extraction Platform emerged at the right time.

Advantages of Kailing Technology OCR Intelligent Data Extraction Platform：

Can be privately deployed:The intelligent data retrieval platform can be deployed on the enterprise's intranet to ensure data security.

Basic engine with high recognition accuracy:The underlying layer is equipped with general and table engines, supporting data extraction from documents and table-type files, ensuring high recognition accuracy for model training and data retrieval.

Strong generalization capability:Supports standard certificates and licenses, internally reprinted documents, and non-formatted documents (contracts, bid documents).

Small-sample training:Through the basic recognition engine, OCR is performed on the entire document before field extraction, without the need for a large number of documents to train a dedicated engine.

Single interface, automatic classification:Provides a single API that supports both document classification and data extraction, enabling quick and easy integration.

Preset templates available:For commonly used certificates (ID cards, business licenses, real estate ownership certificates, etc.), enterprises can choose to preset them in the data retrieval platform.

How to label templates to improve recognition accuracy

Sample selection:

When choosing sample images for templates, try to choose clear ones with complete fields and images, and avoid images that are incompletely displayed.

If the document type has images in multiple styles (photo/scan/electronic original), you can choose to add them to the sample.

For images where the field value contains special characters, try to add them to the sample list for annotation.

Try to choose an image that broadly covers all fields of a sample. For example, for multi-row fields, try to upload multi-row images as samples for training, and the values of these fields in the sample images should contain as few empty fields as possible.

Category tagging:

Try to frame-select the title (it can be part of the title).

Try to ensure the framed values are representative and unique.

Classification granularity:

The same template type can contain multiple keywords; note whether they overlap with existing model keywords.

Whether to subdivide is determined by adding some keywords.

Field annotation:

When selecting the fields to extract, currently try to select all fields in the figure for labeling (mark keys with breakpoints to conveniently use keys to split value values, for example, when a table row detail ends, mark the key value with a breakpoint).

When labeling fields in table format, if for this type of document the table field content will not be empty within the table, you can choose not to check the "This value can be null" checkbox; if the content within the table may be empty, you need to check the "This value can be null" checkbox, which can improve table accuracy.

On the field annotation page, you can enter and use a "regular expression" (when defining fields, you can optionally set the part of speech: date, time, amount, ID, currency, gender).

If the value in the image for the field to be extracted contains letters or special characters (such as "-" or "+"), you can directly edit the already-selected value to add letters or special characters (no need to add new samples).

Kailing Technology OCR Intelligent Data Extraction PlatformWith its powerful functions and convenient operation process, it provides enterprises with efficient and accurate document management and data processing solutions，Meet enterprises' diverse needs, helping enterprises reduce costs, improve efficiency, and achieve digital transformation.

Kailing Technology provides enterprise business-finance-tax digital product lines according to enterprise needs:

Solutions for businesses including sales contract management system, procurement contract management system, fully digitalized Leqi interface project, output automatic invoicing system, employee expense control and reimbursement system, input VAT invoice management system, supply chain collaborative reconciliation system, image OCR recognition system, automatic financial bookkeeping system, and electronic accounting archives system, professionally and efficiently supporting the transformation and upgrading of enterprise business-finance-tax digital management.

If you have any business-finance-tax digital transformation needs, welcome to contact us. Beijing Kailing Technology will serve you wholeheartedly.