Commit 2a4661e1 authored by Jan Niklas Böhm's avatar Jan Niklas Böhm
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Rewrite text on random walks and pagerank

parent 32ea84fe
number = {1999-66},
month = {November},
author = {Lawrence Page and Sergey Brin and Rajeev Motwani and Terry Winograd},
note = {Previous number = SIDL-WP-1999-0120},
title = {The PageRank Citation Ranking: Bringing Order to the Web.},
type = {Technical Report},
publisher = {Stanford InfoLab},
year = {1999},
institution = {Stanford InfoLab},
url = {},
abstract = {The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a mathod for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them. We compare PageRank to an idealized random Web surfer. We show how to efficiently compute PageRank for large numbers of pages. And, we show how to apply PageRank to search and to user navigation.}
author = {Alfred Inselberg},
title = {The plane with parallel coordinates},
......@@ -43,10 +43,15 @@ representation of how it could have looked at a previous time. The
relationships are used to construct a graph, on which either
word2vec\penalty5000\ \citep{word2vec-nips} or RDF2Vec~\citep{rdf2vec}
will be applied. % autoencoders, what do they do, how do they work?
The networks take random walks as input that need to
be generated first. An approach that is similar to the random surfer
model can be employed which will generate random walks more
The networks take random walks as input. These random walks need to
be generated first. Since random walks have a lot of similarities with
the “random surfer” in \citet{pagerank}, an approach for generating
random walks would be to calculate the transition probability matrices
and draw the random walks from this instead of creating them over the
graph. This approach should allow a more efficient generation process
as the matrix operations are implemented more efficiently in the
language than custom code.
The idea is that the latent representation that has been created from the network will be
able to place related accounts in a close proximity, or where vector shifts describe a certain type of relation. With the latent
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