DocumentCode
3438389
Title
Cloud Based Predictive Analytics: Text Classification, Recommender Systems and Decision Support
Author
Hammond, Kevin ; Varde, Aparna S.
Author_Institution
Dept. of Comput. Sci., Montclair State Univ., Montclair, NJ, USA
fYear
2013
fDate
7-10 Dec. 2013
Firstpage
607
Lastpage
612
Abstract
This paper presents a detailed study of technologies based on Hadoop and MapReduce available over the cloud for large-scale data mining and predictive analytics. Although some studies may have shown that cloud technologies relying on the MapReduce framework do not perform as well as parallel database management systems, e.g., with ad hoc queries and interactive applications, MapReduce has still been widely used by many organizations for big data storage and analytics. A number of MapReduce based tools are broadly available over the cloud. In this work we explore the Apache Hive data warehousing solution and particularly its Mahout data mining libraries for predictive analytics. We present results in the context of text classification, recommender systems and decision support. We develop prototype tools in these areas and discuss our outcomes from the study useful to researchers and other professionals in cloud computing and application domains. To the best of our knowledge, ours is among the first few in-depth studies on Mahout with application prototypes available for use.
Keywords
cloud computing; data mining; data warehouses; decision support systems; parallel databases; recommender systems; text analysis; Apache Hive data warehousing solution; Hadoop; Mahout data mining libraries; MapReduce framework; cloud based predictive analytics; cloud computing; decision support; large-scale data mining; recommender system; text classification; Classification algorithms; Data models; Electronic mail; Java; Prototypes; Text categorization; Cloud computing; Data mining; Mahout; Predictive analytics;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining Workshops (ICDMW), 2013 IEEE 13th International Conference on
Conference_Location
Dallas, TX
Print_ISBN
978-1-4799-3143-9
Type
conf
DOI
10.1109/ICDMW.2013.95
Filename
6753976
Link To Document