Information Discovery and Delivery Emerald Journal Impact Factor

Information Discovery and Delivery - Emerald | 2024 Impact Factor: 2.6 | Cite Score:8.0 | Q2

Information Discovery and Delivery Journal With Cite Score

Cite Score and Journal Rank of Information Discovery and Delivery

About: Information Discovery and Delivery (IDD) is a peer-reviewed journal that focuses on research related to information retrieval, discovery, and delivery systems. The journal covers a broad spectrum of topics including search engines, recommendation systems, data mining, knowledge management, and information retrieval algorithms. It aims to provide a platform for significant advancements in the methods and technologies used for discovering and delivering information across various domains.
Objective:
The primary objective of IDD is to advance the field of information discovery and delivery by disseminating high-quality research and innovative methodologies. The journal seeks to offer a comprehensive resource for researchers, practitioners, and educators to share their work on new techniques, systems, and applications in information retrieval and delivery. IDD aims to support the development of effective and efficient solutions that enhance the ability to find and utilize relevant information in diverse contexts.
Interdisciplinary Approach:
IDD embraces an interdisciplinary approach, encouraging contributions from various fields such as computer science, information science, data analytics, and user experience design. This approach ensures a comprehensive exploration of information discovery and delivery issues, integrating diverse perspectives and methodologies. By promoting interdisciplinary research, the journal aims to address complex challenges and develop integrated solutions that advance the effectiveness of information retrieval and management systems.
Impact:
The journal has a significant impact on both academic research and practical applications in the field of information discovery and delivery. It is widely cited by researchers, practitioners, and industry professionals interested in the latest developments in information retrieval and delivery technologies. The research published in IDD contributes to the advancement of new algorithms, systems, and techniques that improve the efficiency and accuracy of information discovery and delivery. The journal serves as a valuable resource for professionals involved in the design, implementation, and optimization of information systems.
Significance:
IDD plays a crucial role in advancing the study and practice of information discovery and delivery by providing a platform for high-quality research and practical insights. Its contributions support the development of innovative solutions and methodologies that address current and future challenges in information retrieval and management. The journals commitment to excellence and interdisciplinary focus make it an essential resource for anyone involved in research, development, and application in this field. Through its rigorous scholarship and broad coverage, IDD helps shape the future of information systems, driving progress in the effective discovery and delivery of information.

Journal Home: Journal Homepage

Editor-in-Chief: Professor Wu He

Scope: The Information Discovery and Delivery (IDD) journal focuses on research related to the discovery, retrieval, and delivery of information across various domains. Its scope includes, but is not limited to:
Information Retrieval: Research on methods and algorithms for retrieving relevant information from large datasets, including search engines, indexing techniques, and query processing.
Information Discovery: Exploration of techniques for discovering useful information and patterns from data, including data mining, knowledge discovery, and machine learning approaches.
Data and Information Integration: Studies on integrating data from diverse sources, including data fusion, data warehousing, and semantic integration.
Information Filtering: Research on techniques for filtering information to provide users with relevant content, including recommendation systems, content filtering, and adaptive filtering.
Personalization and User Modeling: Exploration of methods for personalizing information delivery based on user preferences and behavior, including user profiling, personalization algorithms, and adaptive systems.
Information Retrieval Systems: Studies on the design and evaluation of information retrieval systems, including search interfaces, ranking algorithms, and evaluation metrics.
Big Data and Analytics: Research on the discovery and delivery of information from big data environments, including data analytics, scalability issues, and distributed processing.
Text and Document Mining: Exploration of techniques for mining text and document data, including natural language processing (NLP), text classification, and sentiment analysis.
Information Visualization: Research on methods for visualizing information to support discovery and understanding, including data visualization techniques, interactive visualizations, and visual analytics.
Information Systems Design: Studies on the design and development of information systems for efficient discovery and delivery, including system architecture, user interfaces, and system performance.
Search Engine Technologies: Exploration of technologies and algorithms used in search engines, including crawling, indexing, and ranking algorithms.
Content Management: Research on systems and practices for managing and delivering digital content, including content management systems (CMS), digital asset management, and content delivery networks (CDNs).