TextDive: construction, summarization and exploration of multi-dimensional text corpora

Wang, Qi

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https://hdl.handle.net/2142/90938 Copy

Description

Title

TextDive: construction, summarization and exploration of multi-dimensional text corpora

Author(s)

Wang, Qi

Issue Date

2016-04-20

Director of Research (if dissertation) or Advisor (if thesis)

Han, Jiawei

Department of Study

Computer Science

Discipline

Computer Science

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• multi-dimensional text corpora analysis
• text cube analysis
• text summarization

Abstract

With massive datasets accumulating in text repositories (e.g., news articles, customer reviews, etc.), it is highly desirable to systematically utilize and explore them by data mining, NLP and database techniques. In our view, documents in text corpora contain informative explicit meta-attributes (e.g., category, date, author, etc.) and implicit attributes (e.g., sentiment), forming one or a set of highly-structured multi-dimensional spaces. Much knowledge can be derived if we develop effective and efficient multi-dimensional summarization, exploration and analysis technologies. In this demo, we propose an end-to-end, real-time analytical platform TextDive for processing massive text data, and provide valuable insights to general data consumers. First, we develop a set of information extraction, entity typing and text mining methods to extract consolidated dimensions and automatically construct multi-dimensional textual spaces (i.e., text cubes). Furthermore, we develop a set of OLAP-like text summarization, data exploration and text analysis mechanisms that understand semantics of text corpora in multi-dimensional spaces. We also develop an efficient computational solution that involves materializing selective statistics to guarantee the interactive and real-time nature of TextDive.

Graduation Semester

2016-05

Type of Resource

text

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http://hdl.handle.net/2142/90938

Copyright and License Information

Copyright 2016 Qi Wang

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