@Karunyu, There is a better dimension of "new knowledge". For example Wikipedia has more than 2 million articles in free text form, with a few guidelines and common customs to make articles consistent for readers. This can be considered a lightly structured knowledge repository i.e. you make your way to the page to get the information. You can't get any more information out than the people who wrote on the page put in. However, if instead of typing text, the Wikipedians would do four things..... 1. Enter their data as linked data using standard tags rather than just figures in text and table. 2. Make factual statements using formal assertions with controlled vocabularies rather than free text 3. Add a subject backbone and thesarus to connect related terms together, and 4. Add a natural language query processor. Then it could answer questions like: Which cities in the World have populations over 10 million? How much do Kenyans spend on shipping every year? e.t.c. Regards Edward Mayaka On Mon, Jan 31, 2011 at 10:11 AM, Peter Karunyu <pkarunyu@gmail.com> wrote:
On Sun, Jan 30, 2011 at 10:17 AM, Odhiambo Washington <odhiambo@gmail.com>wrote:
No wonder sometimes I don't find what I am searching for, until I start doubting my keywords! Sasa I know the reason. There are times I have searched for items until I got frustrated.
I'd like to know, if someone cares to explain in summary, how these other search engines work. How do they penetrate the deep Internet?
@Wash, in my recent experiments with DSpace, I learnt that a lot of universities and research organizations publish their works via this piece of software and its pretty easy to deny Google bots access to this honey pot of information.
To put it another way, suppose KIPPRA, KARI, KEMRI, all universities and other bodies which generate 'new' knowledge chose to NOT release their works to the public internet, Google would not find it and thus, you would not find it. I assume then that this is what is called deep internet, no?
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