Fast retrieval approach of sentimental analysis with implementation of bloom filter on Hadoop
Devendra Kumar Tayal, Sumit Kumar Yadav · 2016
For faster growing environment there is a need to analyze sentiments with accurate results and limited time consumption. Hadoop architecture uses sentimental data for processing. As it needs large amount of data for analysis so it requires techniques that can give fast and accurate result. Bloom filter has techniques that uses the database and build a log that can be used for searching results faster. Sentimental analysis uses tree data structure. This data approach uses systematic way for traversal. This data, with implementation of bloom filter, can grow at a high rate efficiently with the use of suitable hash function. Sentimental analysis needs a large data for complete analysis, so Hadoop framework can provide platform to store large dataset and process it.