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Knowledge Management Using Recommender Systems
S. S. Sandhu,
Published in Springer Singapore
Volume: 2
Pages: 183 - 207
Knowledge is defined as the practical or theoretical comprehension of a subject. It refers to the skills, information, and facts acquired over time through education and/or experience. Knowledge management plays a vital role in the industry today. Knowledge that cannot be shared or communicated with others is mostly redundant and becomes actionable and useful only when shared. Knowledge management refers to a set of processes developed specifically for the purpose of creating, storing, disseminating, and applying knowledge. The idea here is to give an organization the capability to learn from its environment and to incorporate the acquired knowledge into its business processes so as to streamline them and increase their efficiency. With the amount of data/information increasing exponentially, discerning what information is relevant becomes tougher by the day and as a result, knowledge management systems are gaining importance. Recommender systems are a subcategory of information filtering systems. These seek to predict the probability of a user preferring a particular item out of a given set of items. To aid in the knowledge retrieval and dissemination processes of knowledge management systems, the use of intelligent techniques is on the rise. Recommender systems form one such category of intelligent techniques. This chapter presents an overview of the different works done to incorporate recommender systems into the domain of knowledge management. Applications in the scientific, engineering, and industrial knowledge management contexts have been discussed. © Springer Nature Singapore Pte Ltd. 2018. All rights reserved.
About the journal
JournalData powered by TypesetKnowledge Computing and its Applications
PublisherData powered by TypesetSpringer Singapore
Open Access0