Machine Learning Semantic Web Team-‐‑ based science - VIVO

steelsquareInternet and Web Development

Oct 20, 2013 (4 years and 18 days ago)

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Machine  Learning  
Capability
Definition
Semantic  Web  
Data  (VIVO)
Team-­‐‑based  Science
Scenarios
Problem  Statement
:  
Machine  Learning  can  be  applied  to  VIVO  data  in  order  to  recommend  Information  Sources  and  Resources,  thus  facilitating  team-­‐‑based  science.
No  Machine  Learning

No  machine  learning  
techniques  are  used.
VIVO  data  is  used  as  it  is  
without  any  machine  
learning  applied  to  it.
Even  without  machine  learning,  
team-­‐‑based  science  still  benefits  
from  structured  and  authoritative  
data  provided  by  VIVO.  
Single  researcher  or  team  uses  VIVO  tools  to  
search
 for  
other  entities  and  information  sources  that  can  prove  
helpful  in  research.
ScaEered  Machine  Learning

Some  machine  learning  
algorithms  are  used  at  
different  places  in  VIVO  
community.
Machine  learning  
techniques  are  applied  to  
certain  sections  of  VIVO  
data.  
Various  applications  using  machine  
learning  benefit  team-­‐‑based  science  
by  analyzing  user  paHerns  to  
recommend  information  resources.
VIVO  based  applications  perform  machine  learning  on  
user  data,  to  
recommend
 information  sources  relevant  to  
the  user’s  research.
Basic  Machine  Learning

Basic  machine  learning  
techniques  are  used.
Data  mining  techniques  
are  used  by  applying  
machine  learning  for  
discovering  
soft-­‐‑
links(possible  predicates)  
between  subject  &  object.
Soft-­‐‑links  
discovered  by  applying  
machine  learning  on  VIVO  data  can  
help  to  identify  various  
relationships  which  were  difficult  
to  predict  otherwise.
Feature-­‐‑based  statistical  machine  learning  can  be  used  to  
perform  analysis  on  VIVO  data  to  derive  
inferences
 about  
relevant  information  sources.
Mature  Machine  Learning

Machine  learning  
techniques  are  used  to  
much  greater  extent.
Machine  learning  
algorithms  are  applied  to  
explore  VIVO  and  
unstructured  data,  and  to  
generate  
recommendations.
The  recommendations  can  be  
generated  using  "ʺlearnt  ontologies"ʺ  
from  free  text  sources  .  VIVO  
information  sources  are  a  good  
starting  point  and  these  sources  can  
be  extended  to  data  from  web.
Single  researcher  or  team  receives  notifications  
recommending  possible  resources  to  assist  in  research.  
This  will  involve  
learning  ontologies
 
from  textual  data  
and  on  the  semantic  annotation  of  
unstructured  data
.  
Machine  
Learning
Semantic  
Web
Team-­‐‑
based  
science
When  machine  learning  is  applied  to    
structured  data  of  semantic  web,  it  enables  
the  creation  of  ‘intelligent  agents’  which  in  
turn  can  provide  valuable  information  to  
facilitate  and  improve  team-­‐‑based  science.  
Learning  from  researchers’  interactions  with  
various  information  objects  and  people,  these  
agents  can  search  for  other  linkages  to  
provide  researchers  with  a  more  
comprehensive  and  relevant  set  of  applicable  
information  resources.  
Machine  Learning  
enables  the  
construction  and  
study  of  systems  
that  can  learn  from  
data.  After  
learning,  it  can  be  
used  to  identify  
paHerns,  that  are  
otherwise  difficult  
to  identify  by  
naked  eye.
Semantic  Web,  
also  known  as  
‘web  of  data’,  
enables  people  to  
create  data  on  the  
web,  build  
vocabularies,  and  
write  rules  for  
handling  data.    
VIVO  enables  
semantic  web-­‐‑
compliant  data.
Team-­‐‑based  science  
is  a  collaborative  
effort  to  address  a  
scientific  challenge  
that  leverages  the  
strengths  and  
expertise  of  
professionals  trained  
in  different  fields.  It  
reduces  the  time  to  
find  solutions  
through  effective  
collaboration.
References:  hHps://www.aamc.org/newsroom/reporter/jan2013/325940/team-­‐‑based-­‐‑science.html
;  
hHp://www.larkc.eu/wp-­‐‑content/uploads/2008/10/learningrdf23.pdf
;