BITS Faculty Publications

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    India Holiday Bureau: Planning for the Tourist Season
    (IESE Publishing, 2013) Bindumadhavan, Krishnamurthy
    The owner and chief executive officer of the India Holiday Bureau (IHB), was besieged by calls from irate travelers seeking an explanation for the poor customer service they had received. It was the peak of the tourist season in India, with international visitors pouring into the country to explore its temples, palaces, hills, beaches and wildlife reserves. IHB had accepted several online hotel-booking requests, but because the hotel did not have sufficient staff to follow through on these requests, several customers were left stranded at the airport without their promised airport transfers. Others had been forced to go without hotel rooms altogether. IHB knew that a lack of accurate forecasting and proper planning was at the root of this problem. How could the owner accurately predict the growth that would continue to overwhelm IHB unless the company prepared for it?
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    Incremental MapReduce for K-Medoids Clustering of Big Time-Series Data
    (IEEE, 2018) Jangiti, Saikishor
    There is a high necessity to refresh the data mining results, as the former results become stale and obsolete over time due to dynamic and evolving data. Clustering is one of the important data mining techniques that help to group data points with similarity together. To mine the data generated exponentially in these days, MapReduce, a parallel programming framework can be combined MapReduce with the k-medoids clustering algorithm to arrive at the optimum results quickly. Due to the parallel processing architecture of Hadoop, the proposed iterative algorithm for processing incremental data using an intermediate key file exhibited better performance over conventional k-medoids.