Swarm Intelligence for Web Document Classification

Posted December 12, 2017 | Leadership | Technology | Amplify
neural network

Clustering large amounts of unstructured data into relatively smaller chunks based on some similarity is at the crux of unstructured data analytics. Here’s where “swarm intelligence” can play a role — an application that drives neural networks for clustering unstructured data. The authors offer an excellent example of swarm intelligence via a model that learns to classify Web documents. We can easily apply this same algorithm to business, medicine, defense, and supply chains, to name a few other areas.

About The Author
Tad Gonsalves
Tad Gonsalves is a Professor in the Department of Information & Communication Sciences at Sophia University, Tokyo, Japan. His research interests include computational intelligence and machine learning algorithms as well as bio-inspired optimization techniques for engineering and business applications. Dr. Gonsalves is also actively engaged in designing image recognition and low-cost autonomous driving systems. As an educator, his passion is… Read More
Yasuaki Nishimoto
Yasuaki Nishimoto is a Cloud Engineer at a Japanese IT firm. His area of interests include swarm intelligence, meta-heuristic optimization, supervised and unsupervised machine learning applications, and game design. Mr. Nishimoto holds a master’s degree in information systems engineering from Sophia University, Tokyo, Japan. He can be reached at
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