@article{MAKHILLAJIT20131275769,
    title = {Synonym Based Duplicate Record Detection},
    journal = {Asian Journal of Information Technology},
    volume = {12},
    number = {7},
    pages = {236-241},
    year = {2013},
    issn = {1682-3915},
    doi = {ajit.2013.236.241},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2013.236.241},
    author = {K. and},
    keywords = {Data integration,duplicate record detection,WordNet ontology,synonyms,catalog integration,un-supervised matching},
    abstract = {As the amount of data and data providers are increasing tremendously, 
  there is a high demand for integrating data from heterogeneous data sources. 
  Often, in the real world, entities have two or more representations and data 
  are not defined in a consistent way across different data sources. When answering 
  user’s query, results are returned 
  to the users by combining data from several databases and the results include 
  duplicate entries. Duplicate detection techniques detect multiple representations 
  of identical real world entities. Without using duplicate record detection techniques, 
  the quality of the extracted data remains low. This study presents an unsupervised 
  duplicate record detection technique which does not require expert’s 
  knowledge or hand coded rules to detect duplicate records. A large lexical database 
  called WordNet ontology is used to match the entities.}
    }