Department of Computer Science and Information Systems: Recent submissions

  • Forced axisymmetric response of linearly tapered circular plates 
    Goyal, Navneet (Elsevier, 1994-05)
    Forced axisymmetric response of a circular plate of linearly varying thickness, based on the classical theory, is analyzed by the eigen-function method. An exact solution for the free vibration mode shapes is obtained by ...
  • Forced asymmetric response of linearly tapered circular plates. 
    Goyal, Navneet (Elsevier, 1999-03)
    The eigenfunction method is used to analyze the asymmetric response of linearly tapered circular plates subjected to transverse loads, uniformly distributed over an annular sectorial area of the plate. The analysis is based ...
  • An Efficient Multi-Component Indexing Embedded Bitmap Compression for Data Reorganization 
    Goyal, Navneet; Sharma, Yashvardhan (Asian Network for Scientific Information Publications, 2008)
    In the present study, we discuss bitmap indices with compression using multi-component indexing for the efficient storage and fast retrieval of large scientific data. The bitmap compression indices embedded multi-component ...
  • Forced Motion of a Semi-Infinite Plate of Linearly Varying Thickness 
    Goyal, Navneet (Elsevier, 1994-06)
    Forced motion of a semi-infinite plate of linearly varying thickness based on classical theory is analyzed by an eigenfunction method. Uniformly distributed and concentrated impulsive loads applied to plates clamped at ...
  • Effect Of Transverse Shear And Rotatory Inertia On The Forced Motion Of A Plate-Strip Of Linearly Varying Thickness 
    Goyal, Navneet (Elsevier, 1994-07)
    Shear theory and the eigenfunction method are used to analyze the forced motion of a plate-strip of linearly varying thickness. A plate clamped at both edges and a cantilever plate subjected to uniformly distributed and ...
  • Incremental models for query clustering and query-context aware document clustering 
    Goyal, Navneet; Goyal, Poonam (Inder Science, 2015)
    The traditional query clustering algorithms are designed to work on previously collected data from query stream. These algorithms become less and less effective with time because users' interests, query meaning and popularity ...
  • Topical document clustering: two-stage post processing technique 
    Goyal, Poonam; Goyal, Navneet (Inder Science, 2018)
    Clustering documents is an essential step in improving efficiency and effectiveness of information retrieval systems. We propose a two-phase split-merge (SM) algorithm, which can be applied to topical clusters obtained ...
  • An efficient method for batch updates in OPTICS cluster ordering 
    Goyal, Poonam; Goyal, Navneet (Inder Science, 2018)
    DBSCAN is one of the popular density-based clustering algorithms, but requires re-clustering the entire data when the input parameters are changed. OPTICS overcomes this limitation. In this paper, we propose a batch-wise ...
  • Parallel SLINK for big data 
    Goyal, Navneet; Goyal, Poonam (Springer, 2019-06)
    The major strength of hierarchical clustering algorithms is that it allows visual interpretations of clusters through dendrograms. Users can cut the dendrogram at different levels to get desired number of clusters. A major ...
  • A novel multimodal clustering framework for images with diverse associated text 
    Goyal, Navneet; Goyal, Poonam (ACM Digital Library, 2019-07)
    With the enormous growth in the number of images on the web, image clustering has become an essential part of any image retrieval system. Since web images are often accompanied by related text or tags, both visual and ...
  • New binning strategy for bitmap indices on high cardinality attributes 
    Goyal, Navneet; Sharma, Yashvardhan (ACM Digital Library, 2009-01)
    Bitmap indices are the preferred indexing structures for read only & high dimensional data in data warehouses and scientific databases. High cardinality attributes pose a new challenge in terms of having space efficient ...
  • A Multi-purpose Density Based Clustering Framework 
    Goyal, Navneet; Goyal, Poonam (Springer, 2011)
    In this paper, we present a multi-purpose density-based clustering framework. The framework is based on a novel cluster merging algorithm which can efficiently merge two sets of DBSCAN clusters using the concept of ...
  • Phase-Wise Clustering of Time Series Gene Expression Data 
    Goyal, Navneet; Goyal, Poonam (IEEE, 2011)
    Extensive studies have shown that analyzing microarray time series data is important in bioinformatics research and biomedical applications. An observation in the analysis of gene expression data is that many genes have ...
  • Parallelizing OPTICS for multicore systems 
    Goyal, Navneet; Goyal, Poonam (ACM Digital Library, 2014-10)
    Parallelizing algorithms to leverage multiple cores in a processor or multiple nodes in a cluster setup is the only way forward to handle ever-increasing volumes of data. OPTICS is a well-known density based clustering ...
  • Parallelizing OPTICS for Commodity Clusters 
    Goyal, Navneet; Goyal, Poonam; Challa, Jagat Sesh (ACM Digital Library, 2015-01)
    In this paper, we propose an algorithm, DOPTICS, a parallelized version of a popular density based cluster-ordering algorithm OPTICS. Parallelizing OPTICS is challenging because of its strong sequential data access behavior. ...
  • A Fast, Scalable SLINK Algorithm for Commodity Cluster Computing Exploiting Spatial Locality 
    Goyal, Navneet; Goyal, Poonam (IEEE, 2016)
    Single linkage (SLINK) hierarchical clustering algorithm is a preferred clustering algorithm over traditional partitioning-based clustering as it does not require the number of clusters as input. But, due to its high time ...
  • Scalable Parallel Algorithms for Shared Nearest Neighbor Clustering 
    Goyal, Navneet; Goyal, Poonam (IEEE, 2016)
    Clustering is a popular data mining technique which discovers structure in unlabeled data by grouping objects together on the basis of a similarity criterion. Traditional similarity measures lose their meaning as the number ...
  • A High Performance Computing Framework for Data Mining 
    Goyal, Navneet; Goyal, Poonam (IEEE, 2016)
    Mining large data sets is no longer the prerogative of computer scientists - specialists in a wide variety of domains are performing analytics as a day-to-day activity. Often such analyses are specific to the domain and ...
  • A Parallel Framework for Grid-Based Bottom-Up Subspace Clustering 
    Goyal, Navneet; Goyal, Poonam (IEEE, 2016)
    Clustering is a popular data mining and machine learning technique which discovers interesting patterns from unlabeled data by grouping similar objects together. Clustering high-dimensional data is a challenging task as ...
  • Spatial Locality Aware, Fast, and Scalable SLINK Algorithm for Commodity Clusters 
    Goyal, Navneet; Goyal, Poonam (IEEE, 2016)
    Single linkage (SLINK) hierarchical clustering algorithm is a preferred clustering algorithm over traditional partitioning-based clustering as it does not require the number of clusters as input. But, due to its high time ...

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