Information Extraction and Visualization of Unstructured Textual Data

Syed Usama Hashmi, Ajay Bansal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

There is a large amount of textual data on the web that has to be analyzed manually by humans in order to use it in meaningful ways. Techniques that can analyze the data, convert it to meaningful information, connect it with other sources of information, and allow querying would be extremely useful. There are different kinds of textual information available with each kid catering to a different kind of audience. This paper presents an information extraction approach that is a modified traversal algorithm on dependency parse output of text to extract all subject predicate object pairs from text while ensuring that no information is missed out. The output format is designed specifically to fit on a node-edge-node model and form the building blocks of a network that makes understanding of the text and querying of information from corpus quick and intuitive.

Original languageEnglish (US)
Title of host publicationProceedings - 13th IEEE International Conference on Semantic Computing, ICSC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages142-145
Number of pages4
ISBN (Electronic)9781538667835
DOIs
StatePublished - Mar 11 2019
Event13th IEEE International Conference on Semantic Computing, ICSC 2019 - Newport Beach, United States
Duration: Jan 30 2019Feb 1 2019

Publication series

NameProceedings - 13th IEEE International Conference on Semantic Computing, ICSC 2019

Conference

Conference13th IEEE International Conference on Semantic Computing, ICSC 2019
CountryUnited States
CityNewport Beach
Period1/30/192/1/19

Keywords

  • Information Extraction
  • Natural Language processing
  • Visualization of Unstructured data

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

Cite this

Hashmi, S. U., & Bansal, A. (2019). Information Extraction and Visualization of Unstructured Textual Data. In Proceedings - 13th IEEE International Conference on Semantic Computing, ICSC 2019 (pp. 142-145). [8665534] (Proceedings - 13th IEEE International Conference on Semantic Computing, ICSC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICOSC.2019.8665534