Abstract Big data analytics technologies are to extract value from very large data volume, variety of data, and highly rate of data stream. With the fast deployment of cloud services with mobile devices, big data analytics is shifting from personal computer to mobile devices. But, significant limitations of mobile devices are less storage amount and processing power. This paper proposes a big data analytic... Big data analytics technologies are to extract value from very large data volume, variety of data, and highly rate of data stream. With the fast deployment of cloud services with mobile devices, big data analytics is shifting from personal computer to mobile devices. But, significant limitations of mobile devices are less storage amount and processing power. This paper proposes a big data analytic platform on mobile cloud computing with efficient query execution time by developing MapReduce Transformation Process and query operation based on input query’s complexity level. Furthermore, this paper presents the process of RESTful web service for providing seamless connectivity between mobile devices and cloud storage, where store the data and all of necessary processing steps are done by cloud backend. This proposed platform is evaluated by using Census dataset and compared the result with other traditional high level query languages, such as Pig, Hive, and Jaql. Read More Read Less

Abstract Most people think that searching information on Web is easy as long as you have Google with you. Yes it is true indeed. But Google or any search engine can be very helpful if the user can express and transform their information need into a correct query. The fact is user having a lot of problems to formulate such query. That is... Most people think that searching information on Web is easy as long as you have Google with you. Yes it is true indeed. But Google or any search engine can be very helpful if the user can express and transform their information need into a correct query. The fact is user having a lot of problems to formulate such query. That is why user reformulates queries several times for getting a more relevant set of results. The aim of this paper is to present evaluation of four different techniques employed in query reformulation process. This work proposes the combination of ontology and important keyword to reformulate new query. The experimental results shows that reformulation using ontology terms alone have incredibly increases the recall and decreases the precision. But when the ontology terms combine with important keywords, it provides better results than the other techniques. Read More Read Less

Abstract Big data analytics technologies are to extract value from very large data volume, variety of data, and highly rate of data stream. With the fast deployment of cloud services with mobile devices, big data analytics is shifting from personal computer to mobile devices. But, significant limitations of mobile devices are less storage amount and processing power. This paper proposes a big data analytic... Big data analytics technologies are to extract value from very large data volume, variety of data, and highly rate of data stream. With the fast deployment of cloud services with mobile devices, big data analytics is shifting from personal computer to mobile devices. But, significant limitations of mobile devices are less storage amount and processing power. This paper proposes a big data analytic platform on mobile cloud computing with efficient query execution time by developing MapReduce Transformation Process and query operation based on input query’s complexity level. Furthermore, this paper presents the process of RESTful web service for providing seamless connectivity between mobile devices and cloud storage, where store the data and all of necessary processing steps are done by cloud backend. This proposed platform is evaluated by using Census dataset and compared the result with other traditional high level query languages, such as Pig, Hive, and Jaql. Read More Read Less

Abstract Most people think that searching information on Web is easy as long as you have Google with you. Yes it is true indeed. But Google or any search engine can be very helpful if the user can express and transform their information need into a correct query. The fact is user having a lot of problems to formulate such query. That is... Most people think that searching information on Web is easy as long as you have Google with you. Yes it is true indeed. But Google or any search engine can be very helpful if the user can express and transform their information need into a correct query. The fact is user having a lot of problems to formulate such query. That is why user reformulates queries several times for getting a more relevant set of results. The aim of this paper is to present evaluation of four different techniques employed in query reformulation process. This work proposes the combination of ontology and important keyword to reformulate new query. The experimental results shows that reformulation using ontology terms alone have incredibly increases the recall and decreases the precision. But when the ontology terms combine with important keywords, it provides better results than the other techniques. Read More Read Less