Page 234 - Big Data Analytics for Intelligent Healthcare Management
P. 234
CHAPTER
INTELLIGENCE-BASED HEALTH
RECOMMENDATION SYSTEM 9
USING BIG DATA ANALYTICS
Abhaya Kumar Sahoo, Sitikantha Mallik, Chittaranjan Pradhan, Bhabani Shankar Prasad Mishra,
Rabindra Kumar Barik, Himansu Das
KIIT, Bhubaneswar, India
9.1 INTRODUCTION
Nowadays, everything is available through the Internet. When people want to buy any kind of product
through the Internet, they first search for reviews or comments about that product. At that time, people
may be confused about whether that product is preferable or not based on these comments. Therefore, a
recommendation system provides a platform to recommend products that are valuable and acceptable
to people. Such a system is based on the features of the item, user preferences, and brand information.
This filtering-based system collects a large amount of information dynamically from the user’s interest,
ratings, choices, or item’s behavior, filters this data, and provides vital information. The theme of data
analytics and big data are not unfamiliar concepts. However, the way they are characterized is contin-
uously varying. Various approaches are made to efficiently retrieve large quantities of data because
there are a lot of unstructured and unprocessed data that needs to be processed and used in various
applications. The healthcare sector is the best illustration of the application of big data analytics in
different spheres of influence [1–3]. Data and information are spread among healthcare centers, hos-
pitals, and clinics. Beside the three Vs (Section 9.3), the veracity of healthcare data is also important for
its role towards improving healthcare. Veracity refers to consistency and trustworthiness in data [4–8].
A recommendation system has the capability to anticipate whether a person would purchase a prod-
uct or not based on the user’s preferences. This system can be implemented based on a user’s profile or
an item’s profile. This chapter explains the collaborative filtering-based health recommendation sys-
tem, which provides valuable information to users based on the item’s profile. Nowadays, there are
many blogs and social forums that are accessible on the internet, where people can provide opinions,
reviews, blogs, and viewpoints regarding products. After obtaining ratings for any product from users,
the recommendation system makes decisions about users who don’t give any ratings. Several
e-business websites are using a recommendation system to increase their revenue in the competitive
market [9–11]. Millions of users buy their products through online e-commerce websites. After buying
products, they give their opinions or any comments about that product in the respective web forum.
Therefore, generating revenue is the main goal of all entrepreneurs. Using this recommendation system
process, we can increase our sales productivity in the market. While the preferences made by customers
227
Big Data Analytics for Intelligent Healthcare Management. https://doi.org/10.1016/B978-0-12-818146-1.00009-X
# 2019 Elsevier Inc. All rights reserved.
