NDLI: A Survey of Big Data and Computational Intelligence in Networking

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A Survey of Big Data and Computational Intelligence in Networking

Content Provider	Scilit
Author	Zhu, Yujia Wu, Yulei Min, Geyong Zomaya, Albert Hu, Fei
Copyright Year	2017
Description	With the rapid development of computing capabilities and storage techniques, there is no doubt that we are facing a series of opportunities and challenges brought about by the big data era. Simply put, big data not only injects wisdom into decision-making and performance improvement but also poses a great threat to traditional data processing techniques. For example, NeteaseMusic is a popular musical software among Chinese teenagers and it is well known for a particular function, Daily Recommendation, which aims to provide users with the songs in which they may be interested. It tracks what songs individual users listen to most frequently and what pages they look at; it usually develops some relevant tags for each song, such as “sad,” “pleasure,” “Country music,” and “Quiet.” Besides these tags, it is able to utilize some initial information like similar singers and albums. This software develops algorithms to 5better understand the customers by taking advantage of the digital data mentioned above. Customers can respond to each song with “like” or “dislike” by highlighting, or not, a heart tag beneath the song. This process is similar to a training process in machine learning. According to these valuable data, indicating users' preference NeteaseMusic can recommend songs to users with very high accuracy. Book Name: Big Data and Computational Intelligence in Networking
Related Links	https://content.taylorfrancis.com/books/download?dac=C2016-0-99932-0&isbn=9781315155678&doi=10.1201/9781315155678-2&format=pdf
DOI	10.1201/9781315155678-2
Language	English
Publisher	Informa UK Limited
Publisher Date	2017-12-14
Access Restriction	Open
Subject Keyword	Book Name: Big Data and Computational Intelligence in Networking Building and Construction Decision Making Big Data Computing Survey Function Recommend
Content Type	Text
Resource Type	Chapter

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