The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Swarm Intelligence in Text Document Clustering
Abstract
In this chapter, we introduce three nature inspired swarm intelligence clustering approaches for document clustering analysis. The major challenge of today’s information society is being overwhelmed with information on any topic they are searching for. Fast and high-quality document clustering algorithms play an important role in helping users to effectively navigate, summarize, and organize the overwhelmed information. The swarm intelligence clustering algorithms use stochastic and heuristic principles discovered from observing bird flocks, fish schools, and ant food forage. Compared to the traditional clustering algorithms, the swarm algorithms are usually flexible, robust, decentralized, and self-organized. These characters make the swarm algorithms suitable for solving complex problems, such as document clustering.
Related Content
.
© 2023.
34 pages.
|
.
© 2023.
15 pages.
|
.
© 2023.
15 pages.
|
.
© 2023.
18 pages.
|
.
© 2023.
24 pages.
|
.
© 2023.
32 pages.
|
.
© 2023.
21 pages.
|
|
|