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Books > Computing & IT > Computer communications & networking
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Business and Consumer Analytics: New Ideas (Hardcover, 1st ed. 2019)
Loot Price: R8,194
Discovery Miles 81 940
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Business and Consumer Analytics: New Ideas (Hardcover, 1st ed. 2019)
Expected to ship within 12 - 17 working days
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This two-volume handbook presents a collection of novel
methodologies with applications and illustrative examples in the
areas of data-driven computational social sciences. Throughout this
handbook, the focus is kept specifically on business and
consumer-oriented applications with interesting sections ranging
from clustering and network analysis, meta-analytics, memetic
algorithms, machine learning, recommender systems methodologies,
parallel pattern mining and data mining to specific applications in
market segmentation, travel, fashion or entertainment analytics. A
must-read for anyone in data-analytics, marketing, behavior
modelling and computational social science, interested in the
latest applications of new computer science methodologies. The
chapters are contributed by leading experts in the associated
fields.The chapters cover technical aspects at different levels,
some of which are introductory and could be used for teaching. Some
chapters aim at building a common understanding of the
methodologies and recent application areas including the
introduction of new theoretical results in the complexity of core
problems. Business and marketing professionals may use the book to
familiarize themselves with some important foundations of data
science. The work is a good starting point to establish an open
dialogue of communication between professionals and researchers
from different fields. Together, the two volumes present a number
of different new directions in Business and Customer Analytics with
an emphasis in personalization of services, the development of new
mathematical models and new algorithms, heuristics and
metaheuristics applied to the challenging problems in the field.
Sections of the book have introductory material to more specific
and advanced themes in some of the chapters, allowing the volumes
to be used as an advanced textbook. Clustering, Proximity Graphs,
Pattern Mining, Frequent Itemset Mining, Feature Engineering,
Network and Community Detection, Network-based Recommending Systems
and Visualization, are some of the topics in the first volume.
Techniques on Memetic Algorithms and their applications to Business
Analytics and Data Science are surveyed in the second volume;
applications in Team Orienteering, Competitive Facility-location,
and Visualization of Products and Consumers are also discussed. The
second volume also includes an introduction to Meta-Analytics, and
to the application areas of Fashion and Travel Analytics. Overall,
the two-volume set helps to describe some fundamentals, acts as a
bridge between different disciplines, and presents important
results in a rapidly moving field combining powerful optimization
techniques allied to new mathematical models critical for
personalization of services. Academics and professionals working in
the area of business anyalytics, data science, operations research
and marketing will find this handbook valuable as a reference.
Students studying these fields will find this handbook useful and
helpful as a secondary textbook.
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