Soft Computing Techniques for Duplicate Question Detection in Transliterated Bilingual Data E-BOOK

By way of the increased penetration of the Internet, social networking websites have become a 
constitutive and indispensable concern of our lives. Social networks make sharing   of   
information,   communication   and   collaboration   straightforward   and opportune.  Social  
media  websites  have  grown  significantly  popular  over  the  last decade  as  the  key  open  
source  platforms  for  general  information  and  knowledge sharing.  Social  media  news  feeds  
and  question  answering  sites  are  increasingly becoming popular and valuable resources for 
enriching and enhancing the knowledge base. Teaching-learning process is now immensely influenced 
by the emerging role of social  media  and  cannot  be  ignored.  Increased  accessibility  of  the 
 internet  and  the ubiquitous  networks  are  major  factors  to  change  the  pedagogical  and  
learning ecosystem's  dynamics  .  Community question  answering  (CQA)  as  a  crowd- 
sourced   service   has   emerged   as   a   collective   intelligence   social   system   which 
facilitates  participation  of  volunteers  to  express  their  knowledge  and  clear  their 
uncertainties    regarding    some    topics.    The    alternate    perspectives    promotes 
receptiveness in sharing and learning, interactions and collaborations which describe the  
advantages  of  intensive  use  of  a  typical  Q&A  website  as  open  source  of information. But 
on the flip side, it is laborious and long-drawn-out task to segregate the semantically duplicate 
information, best answers/semantically matched questions and  experts  for  better  user  
experience  .  These  Q&A  forums  however  facilitate instant   information,   comprehend   
issues   related   to   higher   response   time   and compromised   quality   of   answers   with  
 the   influx   of   questions   and   answers.

Furthermore,  semantically  duplicate  content  falsify  the  mechanism  employed  for filtering.  
Thus  the  present  needs  shifted  the  point  of  focus  towards  the  hitches  of 'filter  
failure'  from  the  issues  of  'information  overload'.  To  build  an  intelligent, proficient 
and semantic  filtering solutions  that can adjust, realign the responses and
give  options  as  per  user's  interest  has  become  pivotal.