Data organization: Automate keywording with AI

In order to use data efficiently, companies need to organize it thoughtfully and in line with their requirements. The tagging of files, documents and content plays a key role here. Because only if all information is easily accessible can companies use it to add value to their processes.

We will show you how tagging works, how you can benefit from it and why artificial intelligence is essential for the efficient organization and use of your data.

The most Important in a Nutshell

• The keywording of documents and content includes content analysis, the determination of keywords, the keywording itself, an optional review and integration into existing systems.
• The advantages of indexing include easy access to information and better collaboration between all employees.
• With Konfuzio, you can automate the entire keywording process - from document import to final integration into databases.
• Konfuzio's AI is suitable, for example, for the automated keywording of invoices in document management, online articles in a content management system or products in e-commerce. Find out now how you can use Konfuzio to organize data in your company!

Tagging - Meaning

Tagging, also known as keywording, describes the process of adding keywords or tags to a specific piece of content to make it easier to categorize and find. These keywords are often terms that represent the content or topic of the material. Companies use tagging primarily to classify and organize data using terms. 

In practice, they make documents efficiently findable, for example. Indexing is therefore important for databases, digital filing systems, archives, content management systems and online platforms. It improves organization and access to information.

How does Tagging work?

Companies usually take these 5 steps to tag files or documents:

1. Content analysis

The first step in tagging files is to analyze the content, be it a text document, image, video or other type of data. During this analysis, companies identify the relevant characteristics, topics and key information.

2. Determination of tags

Based on the analysis, companies select keywords or tags that best describe the content. These keywords are representative of the main topics or elements of the content.

3. Tagging 

Companies tag the documents with the selected keywords. It is important to consider the context, nuances and specific requirements of the content. This is where the challenge lies: if you do not have any software for keywording that automates the process, you have to carry out meaningful keywording manually.

Indexing documents with artificial intelligence, algorithms for machine learning, natural language processing (NLP) and optical character recognition (OCR) provides a remedy here.

We will show you in detail how tagging works with modern technology in the course of this article.

4. Verification and quality assurance (optional)

After tagging, companies check the results to ensure that the keywords are accurate and appropriate. However, this is only relevant for semi-automated or manual tagging. In the case of automated tagging, an artificial intelligence performs the entire process independently. A check is only necessary in the rarest of cases.

5. Integration into systems (optional)

Companies integrate the keywords into the corresponding system such as a database, an archive or a digital personnel file. Companies only have to carry out this last step themselves if they do not have the appropriate software with AI. 

Tagging - 6 important Advantages

Tagging documents helps companies to use their data more efficiently and optimize their business processes. In practice, the process generates these benefits, for example:

Improved findability

By adding relevant tags or keywords to content, companies improve its findability. Users are thus able to search for specific information more quickly and accurately.

Example: An online store uses product tags to make it easy for customers to search and navigate through the catalog.

Better collaboration between employees

Tagging documents makes it easier for employees to find and share relevant information. This promotes collaboration as team members can quickly access the resources they need without wasting time on time-consuming searches.

Example: In a project team, documents are indexed to ensure that team members can efficiently access the information they need.

Increase productivity

The improved findability and efficient collaboration made possible by indexing help to increase overall productivity. Employees complete their tasks faster as they can access relevant resources more easily.

Example: A company indexes training materials to ensure that employees can quickly access up-to-date training content, which speeds up the learning process, reduces errors and increases productivity.

Efficient document management

When companies index documents, they make it easier to organize and access important information. Employees work more efficiently by always having all relevant documents to hand with just a few clicks.

Example: A company indexes internal documents according to projects or topics in order to create a structured database.

Optimized content organization

If content such as texts, images and videos are indexed, companies can organize content in a targeted manner, which improves the creation of corresponding libraries and archives.

Example: A media company indexes its articles and videos by topic to create a clear and searchable content library.

Better search on websites 

Tagging content on websites optimizes the search function, which leads to an improved user experience.

Example: A company adds tags to its knowledge database to enable a precise and fast search for customers and employees.

Tagging with AI: Fully automate the process with Konfuzio

Manual tagging of documents means an enormous amount of work, especially for companies that organize and process large amounts of data. Automated tagging is indispensable for them. Konfuzio has artificial intelligence that automates the entire tagging process:

Automated document import

Before companies take a close look at the content of the relevant documents for indexing, they must first collect them from various sources. Konfuzio does this automatically. The AI compiles the documents from various channels - such as archive folders, email attachments or software applications. It does not matter what format the documents are in. 

Text analysis and identification of tags

Konfuzio recognizes using NLP, OCR and Computer Vision (in the case of text in images) the content in the documents and analyzes it. In this way, the AI forms the basis for indexing the documents. This is because it identifies relevant keywords, topics and other important information.

Automatic tagging

Konfuzio is now able to generate keywords and tags for the respective documents. These describe the documents precisely and correspond to the keywording specifications and objectives. 

Comparison with predefined categories (optional)

If companies already have specific categories or tags for their documents, Konfuzio can take these into account in predefined structures and match the automatically generated keywords with them.

Feedback and improvement (optional)

If desired, Konfuzio integrates user feedback mechanisms to continuously improve the performance of the AI algorithms. In addition to feedback from human users, the algorithms learn thanks to Machine Learning automatically with each tagging.

Storage of indexed documents 

Once the documents have been tagged, Konfuzio saves them in a database or archive. There they are sorted according to the generated tags - and, if required, with additional metadata such as date, category or author. They can now be found immediately for later searches and analysis.

Tagging with Konfuzio: 3 practical Use Cases

Companies organize their data efficiently and facilitate the exchange of information by tagging with AI. Konfuzio is suitable for use wherever information is available in document form. 3 classic use cases for automated tagging with Konfuzio are as follows:

Use case 1: Automated indexing of invoices

A company receives a large number of invoices in various formats every day, including PDFs, scanned documents and emails. Manually categorizing and organizing these invoices is time-consuming and error-prone.

Solution with Konfuzio

The company uses Konfuzio to enable the automated indexing of invoices. This involves the following steps:

• Document import: Konfuzio imports the invoices from the various channels and prepares them for further processing.
• Text extraction: Konfuzio extracts the text from the invoices, including relevant details such as amount, invoice number and supplier information.
• Automatic tagging: Using NLP and machine learning, Konfuzio automatically generates tags such as "invoice", "supplier" and "amount".
• Categorization and storage: Konfuzio categorizes the invoices according to the generated tags and saves them in a digital document archive or database.
• Assignment to tagging: If desired, Konfuzio assigns invoices to the correct contact person after tagging.

Result

employees always have the right invoice for further processing. What's more, you can quickly access invoices using the indexed categories, which significantly speeds up the invoice management workflow.

Use Case 2: Indexing online articles in the content management system

An online magazine publishes numerous articles on various topics every day. The organization and findability of these articles should be improved.

Solution with Konfuzio

The online magazine uses Konfuzio to automatically generate tags for tagging its articles using AI. To do this, Konfuzio takes these steps:

• Text analysis and keyword extraction: Konfuzio analyzes the text of each article and extracts keywords and relevant topics.

• Automatic tagging: Based on the extracted keywords, the AI automatically generates tags such as "politics", "technology" or "culture".

• Structuring the content: The articles are structured according to the generated tags, which enables improved navigation for readers.

Result

Readers can now search for specific topics and receive relevant articles, which increases the user-friendliness of the website and thus user satisfaction.

Use case 3: Tagging of products in e-commerce

An online retailer offers a wide range of products and would like to improve the search and navigation in the product catalog.

Solution with Konfuzio

The company uses Konfuzio to automatically index products and optimize navigation in the product catalog. To do this, it takes these steps:

• Text extraction and keyword analysis: Konfuzio extracts relevant information from the product sheets and analyzes it for keywords.
• Automatic tagging: Konfuzio generates automatically Tags such as "electronics", "clothing" or specific product features.
• Product categorization: The AI categorizes the products according to the generated tags, which makes navigation easier for customers.

Result

Customers can use tags categories and filters to quickly search for specific products and navigate through the catalog. In this way, users complete a purchase faster and with a higher probability.

Conclusion: Konfuzio for automated tagging with AI

In a business world where the amount of data to be analyzed is growing exponentially, automated organization and analysis of this data is essential. Konfuzio is a powerful solution for automating the keywording of documents from start to finish. The application uses state-of-the-art AI technologies for this purpose. Companies are thus able to organize and store their enormous amounts of data without manual effort - and thus ensure easy access. In this way, organizations not only work more efficiently, but also make well-founded, data-based decisions.

Talk to one of our experts now and find out how you can use Konfuzio for automatic keywording in your company!