The big data era is characterized by an explosion of information in the form of digital data collections, ranging from scientific knowledge, to social media, news, and everyone's daily life. Examples of such collections include scientific publications, enterprise logs, news articles, social media, and general web pages. Valuable knowledge about multi-typed entities is often hidden in the unstructured or loosely structured, interconnected data. Mining latent structures around entities uncovers hidden knowledge such as implicit topics, phrases, entity roles and relationships. In this monograph, we investigate the principles and methodologies of mining latent entity structures from massive unstructured and interconnected data. We propose a text-rich information network model for modeling data in many different domains. This leads to a series of new principles and powerful methodologies for mining latent structures, including (1) latent topical hierarchy, (2) quality topical phrases, (3) entity roles in hierarchical topical communities, and (4) entity relations. This book also introduces applications enabled by the mined structures and points out some promising research directions.
Product Identifiers
Publisher
Morgan & Claypool Publishers
ISBN-13
9781627056601
eBay Product ID (ePID)
213415436
Product Key Features
Author
Chi Wang, Jiawei Han
Publication Name
Mining Latent Entity Structures
Format
Paperback
Language
English
Subject
Computer Science
Publication Year
2015
Type
Textbook
Number of Pages
159 Pages
Dimensions
Item Height
235mm
Item Width
191mm
Item Weight
333g
Additional Product Features
Title_Author
Chi Wang, Jiawei Han
Series Title
Synthesis Lectures on Data Mining and Knowledge Discovery