Department of Computer Science and Information Systems: Recent submissions

  • 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 ...
  • DD-Rtree: A dynamic distributed data structure for efficient data distribution among cluster nodes for spatial data mining algorithms 
    Goyal, Navneet; Goyal, Poonam; Challa, Jagat Sesh (IEEE, 2016)
    Parallelizing data mining algorithms has become a necessity as we try to mine ever increasing volumes of data. Spatial data mining algorithms like Dbscan, Optics, Slink, etc. have been parallelized to exploit a cluster ...
  • Exact, Fast and Scalable Parallel DBSCAN for Commodity Platforms 
    Goyal, Navneet; Goyal, Poonam (ACM Digital Library, 2017-01)
    DBSCAN is one of the most popular density-based clustering algorithm capable of identifying arbitrary shaped clusters and noise. It is computationally expensive for large data sets. In this paper, we present a grid-based ...
  • A Domain Specific Language for Clustering 
    Goyal, Navneet; Goyal, Poonam (Springer, 2016-11)
    Clustering of large volumes of data is a complex problem which requires use of sophisticated algorithms as well as High Performance Computing hardware like a cluster of computers. It is highly desirable that data mining ...
  • AnyFI: An Anytime Frequent Itemset Mining Algorithm for Data Streams 
    Goyal, Navneet; Goyal, Poonam; Challa, Jagat Sesh (IEEE, 2017)
    Mining frequent itemsets from transactional data streams has been vastly studied in literature. The existing algorithms mine frequent itemsets within the stream's constrained environment of limited time and memory. However, ...
  • Linguistic Patterns and Cross Modality-based Image Retrieval for Complex Queries 
    Goyal, Navneet; Goyal, Poonam (ACM Digital Library, 2018)
    With the rising prevalence of social media, coupled with the ease of sharing images, people with specific needs and applications such as known item search, multimedia question answering, etc., have started searching for ...
  • Pattern-Based Automatic Parallelization of Representative-Based Clustering Algorithms 
    Goyal, Poonam; Goyal, Navneet (IEEE, 2018)
    Ease of programming and optimal parallel performance have historically been on the opposite side of a tradeoff, forcing the user to choose. With the advent of the Big Data era and rapid evolution of sequential algorithms, ...
  • Optical Character Recognition for Sanskrit Using Convolution Neural Networks 
    Goyal, Navneet (IEEE, 2018)
    Ancient Sanskrit manuscripts are a rich source of knowledge about Science, Mathematics, Hindu mythology, Indian civilization, and culture. It therefore becomes critical that access to these manuscripts is made easy, to ...

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