Call For Paper Volume:4 Issue:6 Jun'2017

PERSONALIZED INFORMATION RETRIEVAL SYSTEM USING MAP REDUCE AND VECTOR SPACE MODEL

Publication Date : 19/03/2016



Author(s) :

SHIVANGI GOEL , SHIVANGI GOEL , ABHISHEK SHARMA.


Volume/Issue :
Volume 3
,
Issue 3
(03 - 2016)



Abstract :

The big data is the concept of large spectrum of data, which is being created day by day. In recent years handling these data is the biggest challenge. Hadoop is an open source platform which is used effectively to handle the big data applications. The two core concepts of the hadoop are Mapreduce and Hadoop distributed file system (HDFS). HDFS is the storage mechanism and map reduce is the programming language. Results are produced faster than other traditional database operations. We proposed vector space model algorithm and map reduce,this algorithm for as improve the data classification and make it uniform. Then apply modified K-Means clustering on input data which we get from above algorithm and output is stored in clustered form. K means reduce the number of comparison which makes execution faster. Clustered Data act as input for MapReduce. MapReduce apply Mapper,Combiner and Reducer Mechanism over data and eliminate duplicate data from large amount of data set. For test data the divide and conquer approach is applied on each row of the cluster. Divide andconquer technique is  used to match records within a  cluster which further improves the efficiency of the algorithm.  Web-based recommender that makes suggestions by using text categorization from Search Keyword. Recommendation systems are one of these tools. They suggest items of interests (such as books, movies, CDs, news, pictures, etc.) by using statistical and machine learning techniques


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PERSONALIZED INFORMATION RETRIEVAL SYSTEM USING MAP REDUCE AND VECTOR SPACE MODEL

March 10, 2016