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Browsing BITS Faculty Publications by Author "Goyal, Navneet"

Browsing BITS Faculty Publications by Author "Goyal, Navneet"

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  • Grid-R-tree: a data structure for efficient neighborhood and nearest neighbor queries in data mining 
    Goyal, Poonam; Goyal, Navneet; Challa, Jagat Sesh (Springer, 2020-04)
    The use of multi-dimensional indexing structures has gained a lot of attention in data mining. The most commonly used data structures for indexing data are R-tree and its variants, quad-tree, k-d-tree, etc. These data ...
  • 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 ...
  • Image Retrieval for Complex Queries Using Knowledge Embedding 
    Goyal, Navneet; Goyal, Poonam (ACM Digital Library, 2020-03)
    With the increase in popularity of image-based applications, users are retrieving images using more sophisticated and complex queries. We present three types of complex queries, namely, long, ambiguous, and abstract. Each ...
  • Improved Bitmap Indexing Strategy for Data Warehouses 
    Sharma, Yashvardhan; Goyal, Navneet (IEEE, 2006)
    Improving the query performance is critical in data warehousing and decision support systems. A lot of methods have been proposed by various researches. Indexing the data warehouse is a common but effective technique. ...
  • 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 ...
  • 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 ...
  • MalCrawler: A Crawler for Seeking and Crawling Malicious Websites 
    Goyal, Navneet (ACM Digital Library, 2017-01)
    Over the years, internet has become the major source of security threat to computer systems. With the number of people browsing internet increasing exponentially in the last couple of years, browser based attacks have ...
  • 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 ...
  • Multilevel Event Detection, Storyline Generation, and Summarization for Tweet Streams 
    Goyal, Navneet; Goyal, Poonam (IEEE, 2020)
    Users acting as real-time sensors post information about current events on various social media sites like Twitter, Facebook, Instagram, and so on. This generates a huge amount of data requiring significant effort to process ...
  • New Approach to overcome the complexity issues raised by Simple Bitmap Indexing 
    Goyal, Navneet; Sharma, Yashvardhan (Springer, 2006)
    Recently Data Warehouse System is becoming more and more important for decision makers. Most of the queries against a large Data Warehouse are complex and iterative. The ability to answer these queries efficiently is a ...
  • 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 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 ...
  • 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 ...
  • Parallel Framework for Efficient k-means Clustering 
    Goyal, Navneet; Goyal, Poonam (ACM Digital Library, 2015-10)
    Handling and processing of larger volume of data requires efficient data mining algorithms. k-means is a very popular clustering algorithm for data mining, but its performance suffers because of initial seeding problem. ...
  • 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 ...
  • 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 ...
  • 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. ...
  • 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 ...
  • 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, ...
  • 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 ...

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