A Survey on Web Multimedia Mining

TL;DR

This survey reviews the current state of multimedia mining, discussing techniques for extracting knowledge from rich media data and addressing challenges in retrieval, indexing, and classification.

Contribution

It provides a comprehensive overview of multimedia mining models, issues in application processes, and recent developments in handling large-scale multimedia data.

Findings

Multimedia mining is essential for extracting implicit knowledge from rich media.

Efficient retrieval and classification depend on effective data fusion across modalities.

The field is still in early stages with ongoing research challenges.

Abstract

Modern developments in digital media technologies has made transmitting and storing large amounts of multi/rich media data (e.g. text, images, music, video and their combination) more feasible and affordable than ever before. However, the state of the art techniques to process, mining and manage those rich media are still in their infancy. Advances developments in multimedia acquisition and storage technology the rapid progress has led to the fast growing incredible amount of data stored in databases. Useful information to users can be revealed if these multimedia files are analyzed. Multimedia mining deals with the extraction of implicit knowledge, multimedia data relationships, or other patterns not explicitly stored in multimedia files. Also in retrieval, indexing and classification of multimedia data with efficient information fusion of the different modalities is essential for the system's overall performance. The purpose of this paper is to provide a systematic overview of multimedia mining. This article is also represents the issues in the application process component for multimedia mining followed by the multimedia mining models.