2. Credits
Speaker Romeu "@malk_zameth" MOURA
Company @linagora
License CC-BY-SA 3.0
SlideShar j.mp/XXgBAn
e ● Mining Graph Data
Sources ● Mining the Social Web
● Social Network Analysis for
startups
● Social Media Mining and Social
Network Analysis
● Graph Mining
15. Plenty of vanity metrics
pollution.
Sometimes very surprising ones.
16. Number of followers is a
vanity metric
@GuyKawasaki (~1.5M followers) is much more
retweeted than the user with most followers
(@justinbieber, ~34M)
17. Why use graphs?
What is the itch with Inductive Logic that Inductive
Graphs scratch?
38. Inputs needed
1. Minimal frequency where we consider a
conformation to be a pattern : threshold
2. Number of most frequent pattern we will
retain : beam size
3. Arbitrary number of times we will iterate:
levels
47. DT-CLGBI(graph: D)
begin
create_node DT in D
if thresold-attained
return DT
else
P <- select_most_discriminative(CL-CBI(D))
(Dy, Dn) <- branch_DT_on_predicate(p)
for Di <- Dy
DT.branch_yes.add-child(DT-CLGBI(Di))
for Di <- Dn
DT.branch_no.add-child(DT-CLGBI(Di))