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Profile Inference from Heterogeneous Data

Fundamentals and New Trends
  • Xin Lu
  • Shengxin ZhuEmail author
  • Qiang NiuEmail author
  • Zhiyi Chen
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 353)

Abstract

One of the essential steps in most business is to understand customers’ preferences. In a data-centric era, profile inference is more and more relaying on mining increasingly accumulated and usually anonymous (protected) data. Personalized profile (preferences) of an anonymous user can even be recovered by some data technologies. The aim of the paper is to review some commonly used information retrieval techniques in recommendation systems and introduce new trends in heterogeneous information network based and knowledge graph based approaches. Then business developers can get some insights on what kind of data to collect as well as how to store and manage them so that better decisions can be made after analyzing the data and extracting the needed information.

Keywords

User profile Heterogeneous data Recommendation systems Information network Similarity 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of MatheamticsXi’an Jiaotong Liverpool UniversitySuzhouChina

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