Faculty Publications

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Publications by NITK Faculty

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Author: search.filters.author.Raghavendra, S.R.

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    Clustering web page sessions using sequence alignment method
    (2011) Poornalatha, G.; Raghavendra, S.R.
    This paper illustrates clustering of web page sessions in order to identify the users' navigation pattern. In the approach presented here, user sessions of variable lengths are compared pair wise, numbers of alignments are found between them and the distances are measured. Web page sessions are clustered by employing the modified k-means algorithm. A couple of web access logs including the well known NASA data set are used to illustrate the effectiveness of the clustering. R-squared measure is applied to determine the optimal number of clusters and chi-squared test is carried out to see the association between the various web page sessions that are clustered. These two measures show the goodness of the clusters formed. © 2011 Springer-Verlag.
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    HAMP –A highly abstracted and modular programming paradigm for expressing parallel programs on heterogenous platforms
    (Newswood Limited publication@iaeng.org, 2012) Balasubramanian, S.; Raghavendra, S.R.
    With the start of the parallel computing era, due to power and thermal considerations, there is a growing need to bridge the gap between parallel hardware and software. The unintuitive nature of parallel programming and the high learning curve often prove a bottleneck in the development of quality parallel software. We propose HAMP – A Highly Abstracted and Modular Programming paradigm for expressing parallel programs. We provide the developer with high level modular constructs that can use to generate hardware specific optimized code. HAMP abstracts programs into important kernels and provides scheduling support to manage parallelism. By abstracting the scheduling and hardware features from the developer, we cannot only, considerably reduce the learning curve, but also increase software lifetime. © 2012 Newswood Limited. All rights reserved.
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    Web page prediction by clustering and integrated distance measure
    (2012) Poornalatha, G.; Raghavendra, S.R.
    The tremendous progress of the internet and the World Wide Web in the recent era has emphasized the requirement for reducing the latency at the client or the user end. In general, caching and prefetching techniques are used to reduce the delay experienced by the user while waiting to get the web page from the remote web server. The present paper attempts to solve the problem of predicting the next page to be accessed by the user based on the mining of web server logs that maintains the information of users who access the web site. The prediction of next page to be visited by the user may be pre fetched by the browser which in turn reduces the latency for user. Thus analyzing user's past behavior to predict the future web pages to be navigated by the user is of great importance. The proposed model yields good prediction accuracy compared to the existing methods like Markov model, association rule, ANN etc. © 2012 IEEE.
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    New sparse matrix storage format to improve the performance of total SPMV time
    (2012) Bayyapu, B.; Raghavendra, S.R.; Guddeti, G.
    Graphics Processing Units (GPUs) are massive data parallel processors. High performance comes only at the cost of identifying data parallelism in the applications while using data parallel processors like GPU. This is an easy effort for applications that have regular memory access and high computation intensity. GPUs are equally attractive for sparse matrix vector multiplications (SPMV for short) that have irregular memory access. SPMV is an important computation in most of the scientific and engineering applications and scaling the performance, bandwidth utilization and compute intensity (ratio of computation to the data access) of SPMV computation is a priority in both academia and industry. There are various data structures and access patterns proposed for sparse matrix representation on GPUs and optimizations and improvements on these data structures is a continuous effort. This paper proposes a new format for the sparse matrix representation that reduces the data organization time and the memory transfer time from CPU to GPU for the memory bound SPMV computation. The BLSI (Bit Level Single Indexing) sparse matrix representation is up to 204% faster than COO (Co-ordinate), 104% faster than CSR (Compressed Sparse Row) and 217% faster than HYB (Hybrid) formats in memory transfer time from CPU to GPU. The proposed sparse matrix format is implemented in CUDA-C on CUDA (Compute Unified Device Architecture) supported NVIDIA graphics cards. © 2012 SCPE.
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    Web sessions clustering using hybrid sequence alignment measure (HSAM)
    (Springer-Verlag Wien michaela.bolli@springer.at, 2013) Poornalatha, G.; Raghavendra, S.R.
    Web usage mining inspects the navigation patterns in web access logs and extracts previously unknown and useful information. This may lead to strategies for various web-oriented applications like web site restructure, recommender system, web page prediction and so on. The current work demonstrates clustering of user sessions of uneven lengths to discover the access patterns by proposing a distance method to group user sessions. The proposed hybrid distance measure uses the access path information to find the distance between any two sessions without altering the order in which web pages are visited. R2 is used to make a decision regarding the number of clusters to be constructed. Jaccard Index and Davies–Bouldin validity index are employed to assess the clustering done. The results obtained by these two standard statistic measures are encouraging and illustrate the goodness of the clusters created. © 2012, Springer-Verlag.