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MappingBooks   Jump  in  the  book!  

Dan  Cristea1,  2,  Ionuț  Cris2an  Pistol   1  

1  Alexandru  Ioan  Cuza  University  of  Iași  

Faculty  of  Computer  Science  

2  Romanian  Academy,  the  Iași  branch  

Ins2tute  for  Computer  Science     {dcristea,  ipistol}@info.uaic.ro    

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The  idea:  

I  like  to  read  books  and  to  travel…  

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I  need  help  to   remember  all  

kinship  

rela2ons  

between  

characters  

(4)
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Exploita2on  of  textual  informa2on  

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MappingBooks  –  a  project  proposal  

•  A  MappedBook  is  a  book  connected  with  

loca2ons/events  in  the  virtual  and  real  world   and  sensi2ve  to  the  instantaneous  loca2on  (as   seized  by  the  mobile/tablet)  of  a  reader.    

•  The  informa2on  made  available  could  possibly   be  different  depending  on  the  moment  and  

the  place  of  the  reader.    

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Aims  

1)  connect  en22es’  men2ons  in  the  form  of  

nominals  (noun  phrases)  =>  one  coreferen2al   chain  corresponds  to  each  en2ty;    

2)  no  preliminary  records  about  linked  en22es  =>  

the  knowledge  base  evolves  from  scratch;    

3)  look  specially  for  coreferen2al  (iden2ty  of  en2ty   men2ons)  and  geographical  rela2ons  (posi2on,   distance,  point-­‐of,  near,  intersects,  etc.);    

4)  texts  under  inves2ga2on:  Geography  manuals   and  traveling  guides    

(8)

En2ty  linking  

•  Challenges  in  en2ty  linking:    

– name  varia2ons     – ambigui2es  

– absence  

•  en2ty  

•  link  type  

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En22es  

•  Type  PERSON  

•  Type  LOCATION  

•  Type  ORGANISATION  

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Textual  realisa2on  of  en22es  

•  Syntac2c  realisa2on:  NPs  (proper  nouns,  common   nouns,  adjec2ves,  complement  PPs;  but  NO  rela2ve   clauses)  

•  Characterised  by  dis2nc2ve  heads  

– [casa  de  pe  [munte]]  

•  If  intersected  !  imbricated  

– [Muzeul  [Grigore  An7pa]]  

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TA = Text Analytics

NER = Name Entity Recognition EC = Entity Crowling

RD = Relations Detection GEO = Geography

M&T = Maps and Trajectories

AR = Augmented Reality DEV = Device Info

INT = Interfaces RES = Resources

M&E = Management and Evaluation

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Features  we  want  to  have  

•  The  capacity  to  see  a  text  different  than  a  string  of   leeers  

– sentence  splifng   – tokenisa2on  

– POS-­‐tagging   – lemma2sa2on   – NP  chunking  

– anaphora  resolu2on    

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Features  we  want  to  have  

•  Know  who’s  who  

– recognise  names  and  types   – disambiguate  names    

– recognise  an  en2ty  in  the  text  even  if  men2oned  with  a   common  noun  or  a  pronoun  

– use  an  ontology  of  types  

NAME  ENTITY  RECOGNITION  

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Features  we  want  to  have  

•  What  virtual  world  en22es  are  men2oned  in  the   book  

– link  textual  men2ons  of  en22es  in  the  virtual  world  

– decide  what  info  from  virtual  would  be  relevant  to  user   – use  mul2ple  sources  

ENTITY  CROWLING  

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Features  we  want  to  have  

•  Trace  on  Google  Maps  a  spa2al  rela2on  described   in  the  book  

– spa2al  rela2ons  detec2on  in  text  

– use  Google  Maps  APIs  or  related  free  technologies   – trace  loca2ons  and  paths  on  maps  

RELATIONS  DETECTION   MAPS&TRAJECTORIES  

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Features  we  want  to  have  

•  Fetch,  process  and  make  use  of  geo-­‐data  

– Geographic  Informa2on  Systems  (GIS)   – geographic  layers  

GEOGRAPHY  

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Features  we  want  to  have  

•  Know  where  I  am  

•  What  real  world  en22es  are  in  my  proximity    

– detec2on  of  my  posi2on  

– computa2on  of  distances  from  the  men2oned  places   – signalling  interes2ng  loca2ons  in  proximity  

DEVICE  INFO  

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Features  we  want  to  have  

•  Mix  images  with  generated  info  

– process  images  =>  segment,  contours,  recogni2on   – sense  orienta2on  of  the  camera    

– decide  info  to  be  displayed  

 

AUGMENTED  REALITY  

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Features  we  want  to  have  

•  Aerac2ve  user  interfaces  

– analyse  use  cases  

– design  dedicated  user  interfaces  

– accommodate  on  the  screen  a  segment  of  text,  a  map,   user’s  posi2on,  web  info,  etc.  

INTERFACES  

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Features  we  want  to  have  

•  Client-­‐server  

– user’s  Portrait   – the  databases  

– standards  and  communica2on  protocols  

CLIENT-­‐SERVER  

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Other  issues…  

•  RESOURCES    

– find  the  texts   – clear  IPR  

– perform  annota2on  

– find  other  relevant  linguis2c  data  

•  MANAGEMENT  AND  EVALUATION  

– establish  evalua2on  criteria  and  metrics   – monitor  the  evolu2on  of  the  project    

– report  dangers  

– perform  final  evalua2on  

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MappingBooks  –  Conclusions  

•  Mul2-­‐dimensional  mash-­‐ups  combining  textual,   geographical  and  temporal  data  

•  Spot  the  book  men2ons  (persons  and  loca2ons)  

•  Make  heavy  use  of  en2ty  linking  techniques  =>  

connec2ng  en2ty  men2ons  onto  the  virtual  world    

•  Links  sensi2ve  to:    

– the  context  of  men2ons  in  the  book     – the  current  loca2on  of  the  user  

– the  moment  the  user  ini2ates  an  access    

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Acknowledgements  

•  MappingBools  is  a  project  supported  by  a   grant  of  CNCSIS,  Romanian  Ministry  of  

Educa2on  and  Research,  July  2014  –  June  

2016,  in  a  consor2um  with  SIVECO  Bucharest   and  “Ștefan  cel  Mare”  University  of  Suceava  

•  Thanks  to  our  students  in  Computer  Science,   for  developing  a  prototype  of  the  system  

during  their  project  in  AI,  in  the  Autumn  –   Winter  term  of  2013-­‐2014…  

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…  and  thank  you  for  listening!  

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