INformation retrieval

A chat with Rubén Lang

INformation retrieval, is a branch of study of artificial intelligence, we could go in that line using the tools of the semantic web.

In this way, we would achieve improved results. The tricky thing is to sort out the amount of info that exists and how to consider when it is good or not.

If you browse a digital content the links have been put by those who make the pages and only the search engines allow you to go further and have an authentic personal route.

All concepts of a digital document should be links, considering that each click is an attempt to delve into the information.

For example, if the content is on a specific topic, or if you are already reading several specific topics, each word in the dictionary thus generated could be a more in-depth search related to these contents.

If you have clicked on chocolate and then on pastry, we could have an ontological relationship between these terms, and look for new content that links to them.

It would be about giving more relevant information and allowing them to go freely to any place on the network that people want to access.

This history is a kind of “personalized usage intelligence” that helps the user find what they are looking for.

So far your clicks are not consistent, because they are conditioned by the design of the contents and do not have INformation retrieval. So LK could make you browse and search at the same time and can create a semantic profile of your behavior, which helps you better understand a topic.