Using PageRank in a Brain

Following up on my post about modeling & consciousness...

The use of a PageRank-like algorithm would explain some behaviors of the human brain. The most popular ideas or concepts require less processing time to recall, and the less popular take more. Likewise, the most popular pages show up first in a Google search, and you have to dig down deeper to find the less popular. The PageRank algorithm constantly updates; as new pages are indexed, the scores of the pages they link to are refreshed, just as the neural connections between frequently access bits of memory are strengthened in the human mind.

Other people have suggested that PageRank works like the human brain, and it makes a lot of sense to me. The amount of information collected by a brain (of any type) is vast, and requires some efficient method of determining what's important and what's not.

Using NLP to Organize Unstructured Data

Another facet of the information overload problem is trying to get a handle of the volumes of unstructured data created by organizations on a daily basis, and package them into a searchable, manageable package. Some establishment struggle with file plan compliance and enforcement, while others provide tools to index and search documents based on keywords. IBM, on the other hand, is applying NLP techniques to try and solve the problem. OmniFind tackles content classification by scanning varied types of unstructured data, automatically learning and categorizing information into newly-created as well as existing taxonomies. By understanding linguistics, semantics, and context, OmniFind is able to determine connections and make inferences beyond the reach of even the greatest keyword-based search algorithms. Another example of NLP making information easier to find, access, and use.

Stovepipe NLP Research

The National Science Foundation is sponsoring research into NLP designed to help government clerks get a handle of the information overload coming from the glut of public comments pouring into www.regulations.gov. The site allows officials to solicit and consider public comments while creating rule and regulations concerning things like organic food labeling and media ownership consolidation. It seems to be a success, as far more comments are submitted than can be effectively sorted through by hand. While it seems reasonable to apply NLP techniques to this problem, should the research money be directed at something like the more general problem of information overload than such a narrow application as this?