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Browsing Department of Computer Science and Information Systems by Author "Goyal, Poonam"

Browsing Department of Computer Science and Information Systems by Author "Goyal, Poonam"

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  • 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 ...
  • 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 ...
  • 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 ...
  • 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 ...
  • On the Universality of Deep Contextual Language Models 
    Goyal, Poonam (NLP Association of India, 2021)
    Deep Contextual Language Models (LMs) like ELMO, BERT, and their successors dominate the landscape of Natural Language Processing due to their ability to scale across multiple tasks rapidly by pre-training a single model, ...
  • 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 ...
  • A Rapid Prototyping Approach for High Performance Density-Based Clustering 
    Goyal, Navneet; Goyal, Poonam (IEEE, 2019-10)
    Big Data has significantly increased the dependence of data analytics community on High Performance Computing (HPC) systems. However, efficiently programming an HPC system is still a tedious task requiring specialized ...
  • Rapid Prototyping of Hierarchical Agglomerative Clustering Algorithms for Distributed Systems 
    Goyal, Poonam; Goyal, Navneet (IEEE, 2019)
    Hierarchical Agglomerative Clustering (HAC) algorithms are used in many applications where clusters have a hierarchical relationship between them. Their parallelization is challenging due to the dependence of every ...
  • A robust approach for finding conceptually related queries using feature selection and tripartite graph structure 
    Goyal, Poonam (Sage, 2013-03)
    The information explosion on the Internet has placed high demands on search engines. Despite the improvements in search engine technology, the precision of current search engines is still unsatisfactory. Moreover, the ...
  • 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 ...
  • 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 ...
  • 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 ...

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