Idealog: Look Into It – A Browser Extension

It is really a simple idea and must be easy to do. It may even exist. Otherwise, I would like to get it built during one of the product sprints.


I was reading a bunch of articles on Technology Review and started noticing terms, I  have not heard before. Terms  like ‘flow cyclometry’, ‘bio base’, ‘biomaterials’, ‘life sensors’. It may be because, I don’t know much about Bioinformatics, Computational Bio-Science and other related fields. Anyway, I was wondering whether there is a way to mark these terms and have a bot research them and create a summary/research page to read.

What is it?

Let us give it a name – Look Into It. It is a browser extension that does the following:

  1. You click on a keyword or phrase and choose to research it
  2. These terms are stored in a database (somewhere in the cloud, preferably)
  3. A bot looks at this list, does some magic (which I can explain later in another blog post), gathers information and creates a page. It can add a link to this page in my reading list.
  4. I can read the info (and this may trigger more terms to research) and if I like to keep it, just save it (into my personal knowledge base).

Random Thoughts

  • Besides curious cats like me, students and other types of learners may be able to use it as well
  • Over a period of time, you build yourself a nice reading list and knowledge base. You may choose to publish all of it or selective bundles of topics.

Like many other ideas, this goes into a queue and a cooling period. If someone expresses interest, I can bring it back to life and discuss some implementation details. It did help me  to get a couple of cool domain names!

2 thoughts on “Idealog: Look Into It – A Browser Extension

  1. Very nice idea and would be invaluable tool for learning & discovering new technologies/concepts. came to my mind as I was thinking about this. Given a set of pages, Dhiti groups them into concepts and provides a concept based navigation, with the concepts tied to Ontology based on WikiPedia.
    If had APIs, I would implement this on top of them and leverage the curated links in every Wikipedia concept page to go and get related content and summarize.

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