Project Abstract

Own Web-Based System on Bookmark Manager introduces an innovative web-based solutiondesigned to transform the management of digital bookmarks through the integration ofadvanced machine learning algorithms. This project leverages Natural Language Processingand clustering techniques to significantly enhance the user experience by automating thecategorisation, optimisation, and personalisation of bookmarks. The system aims to improvefunctionality by enabling efficient and intelligent management tailored to individual userpreferences. By employing a combination of TF-IDF for initial feature extraction, andsophisticated classification algorithms such as Naive Bayes, Support Vector Machines, andConvolutional Neural Networks the system offers robust categorisation capabilities.Further, it incorporates clustering algorithms like K-Means and DBSCAN for dynamic foldermanagement and utilises semantic search technologies including Elasticsearch integrated withBERT for optimised search functionality. Personalisation is achieved through collaborative andcontent-based filtering techniques that adapt to user behaviours and preferences. TheBookmark Manager System represents a significant advancement in the field of digital resourcemanagement, promising not only to streamline the process of bookmarking but also to enhanceaccessibility and usability of saved web resources, thereby setting a new standard for personaland professional bookmark management tools.

Keywords: Web development, Bookmark Management System, Clustering Algorithm

 Conference Details

Session: Presentation Stream 26 at Presentation Slot 7

Location: GH043 at Wednesday 8th 13:30 – 17:00

Markers: George Brooks (GTA), Markus Roggenbach

Course: MSc Advanced Computer Science, Masters PG

Future Plans: I’m looking for an industry placement