Document Classification

Document Classification

Almost every organization using or may need a Document Management System (DMS) to store, track, and manage electronic documents.

In addition to that, Document Management System should be truly capable of accurately finding the documents that you need at the time you need them or to route them appropriately, documents must first be labeled in the form of metadata information attached to them. Since each organization has very different types of content and classification categories, it should be able to easily configured for as per need to the specific organization.

After all, no business is the same.

Yes, docEdge DMS capabilities easily allow you to organize, categorize, tag, label any document there.

Importance of Document Classification

Document Categorisation in docEdge DMS assists in the organization of electronic documentation as manual identification of semantic themes in your documents. Our docEdge DMS software is having with all the features of document classification. So, you can quite categorize every document to be easily found or routed or analyzed most effectively.

Further, for maximum flexibility and accuracy, the future roadmap of docEdge DMS is to provide various such categorization strategies.

    • Machine learning categorization- This document categorization feature can be useful with the availability of training data. From training data, the categorization software is then able to create models which the system can use to categorize new documents. It is important that machine-learning categorization is quite useful — even with a small amount of training data.
    • Topic tagging categorization- With this type of categorization, no training data is required. Here, the user provides concept tagging rules based on simple phrases, words, suffixes, or prefixes. This categorization approach is simple and useful when the user is familiar with the domain and can craft accurate rules.
    • Semantic extraction categorization. This type of categorization utilizes semantic entity and event extraction to categorize documents based on names of organizations, places, and events. It is suitable when the target categories relate to concepts already covered by available semantic extraction software.

After that, the document classification in docEdge DMS would be automatic categorization, which can be used separately or in combination, and provides an application programming interface. Through both rule-based and machine learning-based techniques,

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