Neural Navigational Technique 6: Context-Dependent Associative Search

This technique is a fancy way of saying you're just guessing what the user wants.

It's like a game of "I'm thinking of a word, you try to guess it, and I'll give you a hint if you're right or wrong."

How it works:

1. The user inputs a search query.

2. The algorithm looks at the query and tries to match it with a list of possible answers.

3. If it finds a match, it shows the user the result and asks if they want to refine their query.

4. If it doesn't find a match, it shows the user a random result that's kinda related to their query and hopes they're happy with it.

Example:

If a user searches for "cat," the algorithm might show them a picture of a dog.

Why? Because the user is clearly thinking of a cat.

But wait, there's more!

This technique also uses machine learning to learn from the user's past searches and adapt its results accordingly.

It's like a personal shopping assistant, but instead of shopping, it's helping you find the thing you're thinking of, even if you're not quite sure what it is.

Subpage 1: Query Refinement - The Art of Asking the Right Questions Subpage 2: Machine Learning Myths - Debunking the FUD Subpage 3: User Experience Expectations - What the User Wants