The amount of data shared and stored on the web and other document
repositories is steadily on the rise. Unfortunately, this growth
increases inefficiencies and difficulties when trying to find the
most relevant and up-to-date information due to unstructured data.
Advanced Metaheuristic Methods in Big Data Retrieval and Analytics
examines metaheuristic techniques as an important alternative model
for solving complex problems that are not treatable by
deterministic methods. Recent studies suggest that IR and
biomimicry can be used together for several application problems in
big data and internet of things, especially when conventional
methods would be too expensive or difficult to implement. Featuring
coverage on a broad range of topics such as ontology, plagiarism
detection, and machine learning, this book is ideally designed for
engineers, graduate students, IT professionals, and academicians
seeking an overview of new trends in information retrieval in big
data.
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