Multimedia Information Retrieval System Challenges and Issues

This paper reviews existing literature on substance-based multimedia data retrieval and evaluates its role in various research directions, including browsing and search optimization models, user studies, efficient computing, machine learning, semantic queries, emerging features and media types, high-performance indexing, and evaluation methodologies. We identify and discuss significant future challenges based on the current state of the art. These challenges include retrieval models, cross-lingual retrieval, web search, user modeling, content extraction, topic retrieval and tracking, summarization, question answering, meta-search, distributed retrieval, multimedia retrieval, data extraction, and the requirements for testbeds in future research.

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Publication Details

Journal
Journal of computing and artificial intelligence
Published
2024-12-28
DOI
https://doi.org/10.69591/jcai.2.2.2
Primary Topic
Image Retrieval and Classification Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Multimedia Information Retrieval System Challenges and Issues

R. A. Khan
Journal of computing and artificial intelligence
Image Retrieval and Classification Techniques
article

Multimedia Information Retrieval System Challenges and Issues

R. A. Khan
article en

Abstract

This paper reviews existing literature on substance-based multimedia data retrieval and evaluates its role in various research directions, including browsing and search optimization models, user studies, efficient computing, machine learning, semantic queries, emerging features and media types, high-performance indexing, and evaluation methodologies. We identify and discuss significant future challenges based on the current state of the art. These challenges include retrieval models, cross-lingual retrieval, web search, user modeling, content extraction, topic retrieval and tracking, summarization, question answering, meta-search, distributed retrieval, multimedia retrieval, data extraction, and the requirements for testbeds in future research.

Journal of computing and artificial intelligenceVol. 2(2)
University of Management and Technology (PK)
Openalex Percentile: Top 69%
Image Retrieval and Classification Techniques
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