Question

I’m new to this really useful Q&A website and I’m not really good in English, so sorry about that.

I was interested in a web project that I think is not hard to do and it is a simplified surfing.

Algorithm description 1
Algorithm description 2

This algorithm is made ​​sure the kid is very simple because it quickly analyzes web content and find relevant information.

Can someone tell me how this algorithm functioning that I tried to make something similar?

On what principles funcionise this algorithm?

THANKS!

Answer 1

I just answered very similar question. In your particular case it makes sense to manually create topic list, train it with machine learning on some examples and then, during searching, classify each search result to one of topics. Thus you will get search results, grouped by topic.

UPD. Ok, here’s step by step instruction for one possible way.

First of all, take a look at my recent post about document similarity computation. Then do the following:

1. Implement procedure for computing similarity between 2 texts (as described in my post) or find something similar.
2. Create several collections of documents, one for every category (topic) you want to use (food, IT, politics, medicine, etc.).
3. Compute common vector of all documents in every collection.
4. When the user performs the search, compute vector for every result you found.
5. Classify every result to the category that has the most similar common vector.
6. Group results by computed category.