PG's essays, ranked "Google-style"
solipsys.co.uk
solipsys.co.uk
http://www.solipsys.co.uk/new/PaulGrahamEssays.html?HN
I was prompted to provide these links by this item:
http://news.ycombinator.com/item?id=2011897
I do regularly re-visit PG's essays, and I use these charts/graphs to see what catches my eye on any particular occasion.
Put people on pages at random, and have them click on an outgoing link at random. Then, 20% of the time, teleport them to a new, random page. What is their distribution in the long run?
The higher the number, the more likely you are to end up there. This means you have more incoming links, but they are incoming links from pages with higher rankings. Incoming links from lower ranked pages - pages with few incoming links - don't give you much "Google Juice".
I'm curious, do people really not know this? Should I write it up? It's a standard piece of linear algebra to find the eigenvector of the appropriate matrix. I thought pretty much everyone would know it.
Wasn't there an article on here a little while ago about how most jobs seem easy to the worker because the "common knowledge" is fairly trained in?
Yes please!! I just learned about eigenpairs and the teacher refused to explain their significance. I have no idea what they are beyond their purely abstract definition. I would definitely read your post about this.
http://michaelnielsen.org/blog/lectures-on-the-google-techno...
Skip past the opening, and down to "Basic Description of PageRank". The article eventually gets somewhat technical, but hopefully this at least helps explain the basics. Incidentally, I don't use the term "eigenvector" in the article, but when we're analysing an equation like Mq =q, that's an eigenvector equation!
Linear algebra is stupendously useful material, and I think it really should be standard in any CS curriculum. It wasn't in mine.
echo Retrieving index
curl http://www.paulgraham.com/articles.html > data0
echo Extracting URLs
grep -ho "<a href[^>]*>[^<]*<.a>" data0 | grep -v http | grep -v RSS > data1
ComputeRankings takes the list of essays, extracts outgoing links to create a digraph, and then computes the Page-Rank of each page.CreatePGER takes the results and an HTML template and glues them together to create the rankings page.
echo Creating rankings page
./ComputeRankings.py > ComputeRankings.out
./Create_PGER.py > PaulGrahamEssaysRanking
MakeGraph outputs dot files for the giant component and the "other nodes" graph. echo Creating DOT file
./MakeGraph.py > links0.dot
Then I use neato to layout the graphs. In each case I run it a few hundred times and pick the result that has the largest boxes. That means it's the most compact output, and seems to be a good heuristic. echo Create Giant.png
./LayoutGraph Giant 11,40
echo Create Other.png
./LayoutGraph Other 8,5
Finally I create the HTML you see using an HTML template. echo Create page with map
./Create_PGE.py > PaulGrahamEssays
There's a small lie in this. The web site is actually a statically generated "wiki". When it was first devised I didn't have the facility to run scripts on my host. I generate the pages as plain text with some mark-down, then off-line generate the entire site. Then I upload the parts that have changed.If you try to edit then your suggested new version gets emailed to me, where it goes through an aggressive spam filter. Then it sits in my inbox for me to decide if it's a good change. If so, I trigger a refresh. Some people have passwords that trigger the refresh automatically, without my intervention, so it really does work as a limited access wiki.
Er, right. Is that what you wanted to know?
GraphName=$1
GraphSize=$2
echo Laying out graph $1
LayoutParms="-Gstart=random -Nshape=box -Goverlap=false -Gsplines=true"
for n in 9 8 7 6 5 4 3 2 1 0
do
for m in 9 8 7 6 5 4 3 2 1 0
do
neato ${GraphName}.dot $LayoutParms -Gsize="${GraphSize}" -Tpng -o ${GraphName}.png -Timap -o ${GraphName}.map
score=`sed "s/,/ /g" ${GraphName}.map | gawk '{printf("%04d\n",$5-$3)}' | sort -rn | head -1`
mv ${GraphName}.png ${GraphName}.png_$score
mv ${GraphName}.map ${GraphName}.map_$score
echo $n$m $score `ls -l ${GraphName}.png_* | tail -1`
done
done
cp `ls ${GraphName}.png_0??? | tail -1` ${GraphName}.png
cp `ls ${GraphName}.map_0??? | tail -1` ${GraphName}.map
ls -r ${GraphName}.png_0??? | tail -n +2 | xargs rm
ls -r ${GraphName}.map_0??? | tail -n +2 | xargs rm for n in {9..0}; do echo $n ; done
or for n in $(seq 9 -1 0); do echo $n ; done(Maybe because it is my hobby to push back against dress codes. One time, I was visiting my company's Singapore office. "You can't wear tennis shoes here, it's against the dress code!" "Do you know who I am?" "Nope." "Can you fire me?" "Nope." "Then what are you going to do about it?" :)
Protip: pissing off random people in your company for childish reasons is a piss-poor career move.
http://en.wikipedia.org/wiki/PageRank
It is what google ranking is said ot be based upon. though they keep their exact algorithm secret afaik.
In a nutshell, you give each page a base score, and have it give away part of its score to the pages it links to. Assuming that the page author wouldn't link to a page with poor/irrelevant content, you get some sort of quality/popularity score for each page.
Suggestion - please use a san-serif font.
It's actually a neat idea of the original web, but it's of little practical value today.
http://www.solipsys.co.uk/Giant.png
http://www.solipsys.co.uk/Other.png
These will change as I experiment. Comments welcome.