MANAGBL.AI uses Keywords for a first categorization of contents
One way to set up useful keywords for categorization of texts is to use a technique called "keyword extraction." This involves using natural language processing (NLP) algorithms to automatically identify and extract the most important keywords and phrases from a given text. These keywords can then be used to categorize the text and make it easier to search and organize.
Here are a few tips for setting up keywords for text categorization:
Identify the main topics and themes: Before you can choose the right keywords, you need to understand what the requests are about. Analyze past requests carefully and identify the main topics and themes they cover.
Use nouns and noun phrases: Nouns and noun phrases are often the most important and descriptive words in a text, so they make good keywords. For example, if the request is about a dog, some possible keywords could be "dog," "canine," "puppy," "breed," "collar," and so on.
Use relevant and specific keywords: The keywords you choose should be relevant to the requests and specific enough to accurately describe their content. Avoid using overly general or vague words that could apply to many different requests.
Avoid using words that are already present: There's no need to include words that are already present in the text as keywords. This will just make the keywords list longer without adding any additional information.
Keep the keywords list short and focused: It's better to have a short list of highly relevant and specific keywords than a long list of general or irrelevant words. Keep the list focused on the main topics and themes of the text to make it as useful as possible.
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