Filter
Add to wishlist

Constrained Clustering: Advances in Algorithms, Theory, and Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) eBook

$14.00

  • Delivery: Can be download immediately after purchasing. For new customer, we need process for verification from 30 mins to 24 hours.
  • Version: PDF/EPUB. If you need another version, please Contact us
  • Quality: Full page, full content, high quality images, searchable text and you can print it.
  • Compatible Devices: Can be read on any devices (Kindle, NOOK, Android/IOS devices, Windows, MAC,..).
  • e-Book Features: Purchase and read your book immediately, access your eTextbook anytime and anywhere, unlimited download and share with friends.
  • Note: If you do not receive the download link within 15 minutes of your purchase, please Contact us. Thank you!
  • 5% off all orders over $25 with code:: 5OFF2024
  • 10% off all orders over $50 with code: 10OFF2024
SKU: 9781584889960 Categories: ,

The big data era is upon us: data are being generated, analyzed, and used at an unprecedented scale, and data-driven decision making is sweeping through all aspects of society. Since the value of data explodes when it can be linked and fused with other data, addressing the big data integration (BDI) challenge is critical to realizing the promise of big data. BDI differs from traditional data integration along the dimensions of volume, velocity, variety, and veracity. First, not only can data sources contain a huge volume of data, but also the number of data sources is now in the millions. Second, because of the rate at which newly collected data are made available, many of the data sources are very dynamic, and the number of data sources is also rapidly exploding. Third, data sources are extremely heterogeneous in their structure and content, exhibiting considerable variety even for substantially similar entities. Fourth, the data sources are of widely differing qualities, with significant differences in the coverage, accuracy and timeliness of data provided. This book explores the progress that has been made by the data integration community on the topics of schema alignment, record linkage and data fusion in addressing these novel challenges faced by big data integration. Each of these topics is covered in a systematic way: first starting with a quick tour of the topic in the context of traditional data integration, followed by a detailed, example-driven exposition of recent innovative techniques that have been proposed to address the BDI challenges of volume, velocity, variety, and veracity. Finally, it presents merging topics and opportunities that are specific to BDI, identifying promising directions for the data integration community.