Daily procedures such as scientific experiments and business processes have the potential to create a huge amount of data every day, hour, or even second, and this may lead to a major problem for the future of efficient data search and retrieval as well as secure data storage for the world’s scientists, engineers, doctors, librarians, and business managers.
Design, Performance, and Analysis of Innovative Information Retrieval examines a number of emerging technologies that significantly contribute to modern Information Retrieval (IR), as well as fundamental IR theories and concepts that have been adopted into new tools or systems. This reference is essential to researchers, educators, professionals, and students interested in the future of IR.
The many academic areas covered in this publication include, but are not limited to:
This work is aimed at researchers, academics, advanced students, and practitioners using XML stream data processing and concerned with the design of information retrieval systems in higher education and industry. International contributors in computer science, software engineering, and information science report on research in key word search in XML and XML stream processing technologies, then describe methods for dealing with large amounts of XML documents generated by legend systems, focusing on compression without decompression through a system called XCVQ-QP. Section 3 presents work on automatic mapping of XML documents into relational databases, focusing on the system MAXDOR, and section 4 investigates multi-feature query-language-based classification in image retrieval. Section 5 presents collaborative approaches in business process management in information retrieval, concentrating on these methods: Petri-net for analysis of business process modeling methods, pi-calculus for advanced branching, rule based approaches for process modeling, and WS-CDL. Lu is affiliated with the University of Huddersfield, UK.