PC Assembly

Abstract—  Now  days,  purchasing  branded  Desktop  PC  from  a  single  Vendor  is  getting  expensive day  by  day.  Also  consumers  are  required  to  rely  on  single  Vendor  for  their  whole  Desktop  PC  and thereby  compromising  on  the  hardware  so  as  to  reduce  cost.  To  overcome  this  problem  a  new approach  was  developed  i.e.  to  assemble  the  PC  by  purchasing  its  essential  component  from  different vendors.  A  large  number  of  websites  allow  users  to  post  reviews  about  product  they  bought.  People who find it difficult to understand the  technical specification of a  product often tends to  read  reviews. There  are  thousands  of  reviews  of  customers  available  on  different  e-commerce  portal  related  to  a product.  So  it  is  difficult  for  the  customers  to  get  an  idea  about  the  product  from  wide  range  of reviews.  In  this  project  we  aim  to  summarize  the  customer‟s  reviews  in  factual  form  using  part-ofspeech  tagger  (POS),  Lexicon  algorithm,  and  Naive  Bayesian  classifier  which  are  all  based  on Natural  language  processing  (NLP).We  have  developed  a  rating  system  which  rates  each  computer peripherals  based  on  its  performance  &  cost  and  thereby  calculating  the  final  rating  of  assembled system  virtually  so  that  consumers  can  judge  whether  the  assembled  product  meets  all  the requirement  as expected. Keywords-  PC  Assembly,  Reviews,  POS,  Opinion  Mining,  Extraction,  Java,  Perl,  XML,  Products