The document discusses an invited talk by Dr. Gan Keng Hoon on text analytics, focusing on transforming unstructured data into meaningful insights applicable across various domains. It covers levels of analysis including word, sentence, and document, along with desired outcomes such as text classification and keyword extraction. The talk aims to highlight techniques and issues related to text analytics and their relevance to decision making.

1. A View of Text Analytics from Word,
Sentence and Document Levels
Dr. Gan Keng Hoon
School of Computer Sciences
Universiti Sains Malaysia
GKH USM 1
Invited Talk at Xiamen University
14 July 2021

2. Talk Overview
Text analytics is a process that turns unstructured data to meaningful
insights. This process can be applied in any domains that requires
decision making using textual data. Some desired outcomes include
classified texts, top keywords and summary. To achieve these
outcomes, various levels of analysis can be performed on the textual
data. This talk focuses on the view of analysis at word, sentence and
document levels. At the end of the talk, audience will get a touch of the
issues and techniques related to this view and their links to text
analytics outcomes.
GKH USM 2

3. Talk Outline
Text Analytics Overview
Word
Sentence
Document
Text Analytics Scenario
Research & Development Highlights
GKH USM 3

4. Text Analytics
GKH USM 4
Text Actions
Text
Analytics
Components
Actions