[email hidden] (Philipp Lenssen) wrote in message news:<[email hidden]>...
Quoted message said:At memecodes.outer-court.commemecodes.outer-court.comOpen ↗ :
"Here's an idea for a set of evolutionary pages that have "natural" offspring and grow into
being more popular. I plan to put up a set of pages with random words; Project Memecodes. Say,
5,000 pages with random word sequences (let's pray to the Googlegod I won't get the death
penalty for that).
Now whenever a page gets a visitor who arrived from Google, the page will create a new modified
randomized version of itself via its database back-end, and create a link to it in a visible
place. The new page will continue do the same as the old page. After a while, a page "dies" and is
taken offline. Soon several pages would be able to specialize on search niches in the Web
environment ? word combinations people are looking for that are not yet covered online and
therefore make my evolutionary pages turn up in the top results which people actually click on. A
search phrase entered by a search engine visitor is just like food in nature's ecosystem ? there
will be specialized pages to catch this food. A page's "meme code" will lead it to become a
successful species with a lot of offspring, or die and be forgotten.
Like infinite monkeys writing Shakespeare, if the experiment will be running long enough with
enough modifications, the once randomly worded pages might even modify themselves to the point of
becoming natural language."
Hope that made sense -- feedbackw welcome 🙂
It's a very interesting idea, but the speed of the evolution might be improved if you used search
query data directly without waiting for people to actually find your pages (considering that search
engines will only reindex your pages every few weeks). You might also annoy people less if you went
about it this way. There are a number of places you can go to see data about what people type into
search engines.
One example: metaspy.commetaspyOpen ↗
For a list of others sites with search query data see:
searchenginewatch.com2156041Open ↗
Other people have tried to generate natural language texts based on word co-occurrence statistics
using text from books, newspapers, etc. The texts that resulted contained strings of words that
sounded grammatical within a window of two or three words, but which didn't form proper sentences.
Co-occurrence statistics aren't enough.
In your case though, things are even worse. Given that most search queries are lists of key words
(mostly nouns) rather than grammatical sequences of words, and that when people do enter a
grammatical sequence, it is usually just a noun phrase, I doubt that you will achieve anything like
natural language texts. One of the obstacles is that many of the highly frequent words that you get
in English like 'of', 'the', 'and', etc. are ignored/filtered out by search engines, but are
essential for producing grammatical sentences. People also naturally tend to search using nouns as
keywords rather than verbs or adjectives although there is no rational reason for this. For example,
they will tend to use the noun 'rehearsal' as a keyword rather than the verb 'rehearse'. As a
result, I predict your texts will end up light in verbs and adjectives as well as having almost no
grammatical function words. My bet is they will also avoid using words like 'this', 'it',
'yesterday', 'here', etc. which depend on context for their interpretation so these would also end
up disappearing from your texts.
Hope this helps,
H.
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Like-minds don't notice shared mistakes. Talk to someone else.
