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Department of Computer Science and Information Systems: Recent submissions

Now showing items 181-200 of 954

Provenance Framework for Twitter Data using Zero-Information Loss Graph Database

Goyal, Navneet (ACM Digital Library, 2021)

Social media is an ever-evolving web based platform for sharing thoughts, opinions, ideas and other contents. Among all social media networks, Twitter has become one of the most popular social networking/micro-blogging ...
Detection of Malicious Webpages Using Deep Learning.

Goyal, Navneet (IEEE, 2021)

Malicious Webpages have been a serious threat on Internet for the past few years. As per the latest Google Transparency reports, they continue to be top ranked amongst online threats. Various techniques have been used till ...
Twitter Data Modelling and Provenance Support for Key-Value Pair Databases

Goyal, Navneet (Springer, 2021-02)

In Big Data environments, reliability of data plays an important role to determine trustworthiness of the outcomes of an analysis. Big data provenance ensures the reliability of data by providing details about the origin ...
Android Web Security Solution using Cross-device Federated Learning

Goyal, Navneet (IEEE, 2022)

Over the last one decade or so, Machine Learning has changed the global technology landscape with applications in almost all disciplines and verticals. Mobile and Web Security is an important research area in which researchers ...
A Generalized Multimodal Deep Learning Model for Early Crop Yield Prediction

Goyal, Navneet; Goyal, Poonam (IEEE, 2022)

Early crop yield prediction is crucial in agriculture for making administrative plans to ensure food security, post harvest management and distribution of a crop. Remote sensing data captured using various satellites provide ...
AnyStreamKM: Anytime k-medoids Clustering for Streaming Data

Challa, Jagat Sesh; Goyal, Navneet; Goyal, Poonam (IEEE, 2022)

Stream Clustering algorithms have gained a lot of importance in the recent past due to rapid rising utilities of IoT systems and applications. Anytime algorithms and frameworks play a key role in handling streams that have ...
Social data provenance framework based on zero-information loss graph database

Goyal, Navneet (Springer, 2022-07)

Social media has become a common platform for global communication across the world due to its rapid dissemination of information among a large audience. Its popularity has raised a crucial challenge to capture the social ...
Big social data provenance framework for Zero-Information Loss Key-Value Pair (KVP) Database

Goyal, Navneet (Springer, 2021-11)

Social media has been playing a vital importance in information sharing at massive scale due to its easy access, low cost, and faster dissemination of information. Its competence to disseminate the information across a ...
Big Data and Artificial Intelligenc

Goyal, Navneet (Springer, 2023)

This book constitutes the proceedings of the 11th International Conference on Big Data and Artificial Intelligence, BDA 2023, held in Delhi, India, during December 7–9, 2023. The17 full papers presented in this volume ...
Multimodal Semantographic Metalanguage (MSM): A novel methodology for digital enablement of semi-literates

Goyal, Poonam; Goyal, Navneet (ACM Digital Library, 2023-06)

People in developing countries without tertiary education, face hurdles in using digital platforms for communication. The linguistic diversity of this section of population makes design of near-universal digital enablement ...
LSFuseNet: Dual-Fusion of Landsat-8 and Sentinel-2 Multispectral Time Series for Permutation Invariant Applications

Goyal, Navneet; Goyal, Poonam (IEEE, 2023)

Satellite data provides valuable insights into environmental changes and natural resource management, such as monitoring deforestation, mapping land use changes, and identifying areas at risk of soil degradation. Landsat-8 ...
Utilizing MODIS Fire Mask for Predicting Forest Fires Using Landsat-9/8 and Meteorological Data

Goyal, Navneet; Goyal, Poonam (IEEE, 2023)

Recent years have seen some of the largest forest fires ever, including the 2020 California megafires and the Australian bushfires, causing billions of dollars in property damage and destroying millions of acres of green ...
An Adaptive Hierarchical Method for Anytime Set-wise Clustering of Variable and High-Speed Data Streams

Challa, Jagat Sesh; Goyal, Poonam; Goyal, Navneet (IEEE, 2023)

Set-wise Clustering is a clustering technique for data streams that groups sets of objects based on distribution patterns, applicable in contexts like retail chain clustering, text-based community clustering, restaurant ...
Provenance Framework for Multi-Depth Querying Using Zero-Information Loss Database

Goyal, Navneet (World Scientific, 2023)

Data provenance is a kind of metadata that describes the origin and derivation history of data. It provides the information about various direct and indirect sources of data and different transformations applied on it. ...
Fusion of multivariate time series meteorological and static soil data for multistage crop yield prediction using multi-head self attention network

Goyal, Poonam; Goyal, Navneet (Elsevier, 2023-09)

Yield prediction is helpful for timely harvest management, crop planning, and food security. It depends on many factors like location, climate, soil characteristics, genotype, etc. The data used in yield prediction is a ...
VOLTAGE: A Versatile Contrastive Learning based OCR Methodology for ultra low-resource scripts through Auto Glyph Feature Extraction

Goyal, Poonam; Goyal, Navneet (Association for Computational Linguistics, 2024)

UNESCO has classified 2500 out of 7000 languages spoken worldwide as endangered. Attrition of a language leads to loss of traditional wisdom, folk literature, and the essence of the community that uses it. It is therefore ...
Efficient Representation Learning of Satellite Image Time Series and Their Fusion for Spatiotemporal Applications

Goyal, Poonam; Goyal, Navneet (Association for the Advancement of Artificial Intelligence, 2024)

Satellite data bolstered by their increasing accessibility is leading to many endeavors of automated monitoring of the earth's surface for various applications. Such applications demand high spatial resolution images at a ...
A Survey and Experimental Review on Data Distribution Strategies for Parallel Spatial Clustering Algorithms

Challa, Jagat Sesh; Balasubramaniam, Sundar; Goyal, Navneet; Goyal, Poonam (Springer, 2024-06)

The advent of Big Data has led to the rapid growth in the usage of parallel clustering algorithms that work over distributed computing frameworks such as MPI, MapReduce, and Spark. An important step for any parallel ...
A Utility Tool for Personalised Medicine

Gavankar, Chetana (ACM Digital Library, 2018)

Biomedical research is drowning in data, yet starving for knowledge. As the volume of scientific literature is growing unprecedentedly, revolutionary measures are needed for data management. Accessibility, analysis and ...
A Comparative Study of Semantic Search Systems

Gavankar, Chetana (IEEE, 2020)

Today’s internet consists of mostly unstructured data, most of it being unusable for average users. With increase in the number of smart devices that are getting access to the web, we have a large set of unlinked data that ...

Now showing items 181-200 of 954

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