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16.3 MB
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495B956F195197DC48CCFD3AA55F7A254F32B544
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July 10, 2025, 2:03 p.m.
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(Last updated: July 10, 2025, 2:04 p.m.)
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| ['Bock J. Ontology Alignment using Biologically-inspired Optimisat. Algorithm 2013.pdf'] | 0 bytes |
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NOTE
SOURCE: Bock J. Ontology Alignment using Biologically-inspired Optimisat. Algorithm 2013
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COVER
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MEDIAINFO
Textbook in PDF format Looking outside our windows we recognise the amazing results of an enduring and massively parallel process called evolution. In billions of years evolution has created cells, plants, animals, and humans, including the human brain. With the ability to think, communicate, combine, and reason, the human brain is capable of dealing with complex information artifacts we call knowledge. While knowledge on the one hand is the root of all great inventions such as aeroplanes, pharmaceuticals, and computers, it also creates new challenges. The vast amounts of knowledge become difficult to manage, which is why we seek for assistance in computer science. One such difficulty in knowledge management is the fact that knowledge is distributed, which, in turn, leads to ad hoc or permanent knowledge integration tasks. In those cases where knowledge is represented formally in terms of ontologies, this problem has become known as ontology alignment. Astonishingly, the emergence of parallel and distributed computing infrastructures now stimulates the imitation of evolutionary processes in the form of nature-inspired problem solving algorithms. The application of evolutionary and other biologically-inspired algorithms, such as computational swarm intelligence, have been shown very useful for complex optimisation problems. This book presents the work of my doctoral thesis on applying biologically-inspired optimisation algorithms to the problem of ontology alignment. It is a fascinating thought to take one of the first steps towards computationally assisting knowledge management by emulating the natural processes that created our brains in the first place
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