A fast approach to identify trending articles in hot topics from XML based big bibliographic datasets

摘要: Nowadays XML based big bibliographic datasets are common in different domains which provide meta data about articles published that domain. They have well defined tags give details of the year, title, authors, abstract, keywords, type article, venue publishing article and other such specific each article. A lot statistics can be extracted from this dataset. Most time tag pertaining to domain sub topic information associated with will absent dataset as it is not an attribute. Hence for must mapped its This paper investigates problem proposes a fast approach find trending hot topics datasets. The proposed framework uses ontology first classify into topics. Fast detection topics, keywords achieved using novel Map Reduce algorithms implemented on hadoop distributed framework. Performance comparison demonstrates outperforms non-Map counterpart quickly sorting out titles particular