Cécile
Picard‐Limpens

         Dr.
Computer
Science

        ccl.picard@gmail.com



     Freddy
Limpens

       Ph.D
Com...
How
will
I
get
rid
of


all
these
rusty
coffee
makers??

1.  Making
visible
on
the
web
the
stock
of
2nd
hand
shops

    ("ressourceries",
Emmaus
communiMes,
SalvaMon
Army,
etc.)

...
Training
data

                                                                                
clusters
of
objects


    ...
Hot
liquid
container




                      AUTOMATIC

                      shape
recogni;on
:

     Picture
         ...
The
goal
:

 ?
        Finding
semanMcally


                   Related
tags


     ?

          To
enhance
searching

?

...
The
idea
:

1.
/
Mapping
tags


With
ontologies’
concepts




                                      Hot
liquid

          ...
www.slideshare.net/fabien_gandon/web‐smanMque‐et‐web‐social‐1700977

www.slideshare.net/fabien_gandon/web‐smanMque‐et‐web‐social‐1700977

www.slideshare.net/fabien_gandon/web‐smanMque‐et‐web‐social‐1700977

The
idea
:

2.
/
Mining
semanMc
relaMons

From
tags’
structure
and
features





                           Coocurring


 ...
1. 
The
user
enter
"coffee
maker"





                                                          Results
for
"coffee
maker":...
•    An
automaMc
archiving
of
second‐hand
objects























     and
their
easy
retrieving
by
a
potenMal
user...
•    Benchmark
current
shape
recogniMon
methods 
       
   
     
   


     on
our
specific
problem

•    Looking
for
ava...
Reinventing the Inventory
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Reinventing the Inventory

526

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John is wondering..”How could I find the coffee maker my parents had when I was ten years
old??..” The current merchant systems have a tendency to filter out objects that do not have a
mercantile value. For example, John is searching for an object that has a value for him and maybe
not for other people and for the common mercantile system. For this reason, it will be very difficult
for him to find the object even on the web. On the other hand, we observe the development of
second-hand shops that gather objects that are pushed aside. John knows that he could have a
chance to find its coffee maker in those shops. However, he may have to visit many places to finally
find it!
Starting from this observation, we propose a novel approach to manage storage and cataloguing of
objects of any kind. The idea consists in assisting the digitizing of objects collected by 2nd hand
shops in order to allow them to publish online their catalog.

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Reinventing the Inventory

  1. 1. Cécile
Picard‐Limpens
 Dr.
Computer
Science
 ccl.picard@gmail.com
 Freddy
Limpens
 Ph.D
Computer
Science
 freddy.limpens@inria.fr

  2. 2. How
will
I
get
rid
of

 all
these
rusty
coffee
makers??

  3. 3. 1.  Making
visible
on
the
web
the
stock
of
2nd
hand
shops
 ("ressourceries",
Emmaus
communiMes,
SalvaMon
Army,
etc.)
 2.  Helping
these
organizaMons
digiMzing
and
cataloguing
their
 stock
 3.  Enhancing
categorizaMons
and
search
in
catalogs
with
semanMc
 technologies


  4. 4. Training
data
 
clusters
of
objects

 Hot
liquid
container
 associated

 to

a
class
 (tag)
 2.
AUTOMATIC
 shape
recogni;on
:
 1.
Take
 ‐ 
Find
closest
cluster

 
a
picture
 ‐ 
link
tag
to
object
 Seman;c
technologies
 
Set
of
ontologies
 describing
classes

of
objects

 (tags)
and
their
relaMons
 3.
SEMI‐AUTOMATIC
 Hot
liquid
 refining
of
the
tagging
 container
 ‐ 
AutomaMcally
suggest

 id
:


hl‐123456
 tags
:
 

related
tags
(ontology)
 coffee
pot
 
hot
liquid
container
 ‐ 
Manually
validate
or

 coffee
maker
 ☐
coffee
maker
 

correct
suggesMons
 tea
pot
 =
subClassOf
  
coffee
pot
 ☐
tea
pot


  5. 5. Hot
liquid
container
 AUTOMATIC
 shape
recogni;on
:
 Picture
 ‐ 
Find
closest
cluster

 ‐ 
link
tag
to
object
 RELATED
WORK
 Image
analysis
tools
with
machine
learning
 and
staMsMcal
modeling
techniques
 •  FIRE
(Flexible
Image
Retrieval
Engine),
a
content‐based
image
retrieval
system 
 Thomas
Deselaers,
RWTH
Aachen
University
 •  LEAR
team:
visual
object
recogniMon
for
object
category
detecMon 
 INRIA‐LJK
Grenoble
 taking
into
account
shape,
color
or
texture
(via
opencv
library) Université
de
Mons
&
numediart,
Belgium
 
 •  Mediacycle:
allows
to
browse
image
libraries
by
organizing
them
into
clusters

  6. 6. The
goal
:
 ?
 Finding
semanMcally

 Related
tags

 ?
 To
enhance
searching
 ?
 coffee
maker

  7. 7. The
idea
:
 1.
/
Mapping
tags

 With
ontologies’
concepts
 Hot
liquid
 container
 coffee
pot
 coffee
maker
 tea
pot
 =
subClassOf

  8. 8. www.slideshare.net/fabien_gandon/web‐smanMque‐et‐web‐social‐1700977

  9. 9. www.slideshare.net/fabien_gandon/web‐smanMque‐et‐web‐social‐1700977

  10. 10. www.slideshare.net/fabien_gandon/web‐smanMque‐et‐web‐social‐1700977

  11. 11. The
idea
:
 2.
/
Mining
semanMc
relaMons
 From
tags’
structure
and
features
 Coocurring

 tags
 String‐based
mapping

  12. 12. 1. 
The
user
enter
"coffee
maker"

 Results
for
"coffee
maker":
 coffee
maker
 

 
 
 
2. 
The
system
suggests
addiMonal
results
thanks
to
semanMc
relaMons
 Related
results
:
 
Results
for
"tea
pot":
 
Results
for
"coffee
pot":

  13. 13. •  An
automaMc
archiving
of
second‐hand
objects






















 and
their
easy
retrieving
by
a
potenMal
user
 •  A
good
picture
of
sustainable
development
 •  All
the
techniques
used
aimed
to
be
free
and
open
source

  14. 14. •  Benchmark
current
shape
recogniMon
methods 
 
 
 
 

 on
our
specific
problem
 •  Looking
for
available
ontologies/folksonomies
of
everyday
 objects
to
bootstrap
semanMc
funcMonnaliMes
 •  PracMcal
experiment
in
a
«
ressourcerie
»
 
 
 
 
 
 

 (hnp://courtcircuioelleMn.wordpress.com/)

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