A multiple instance learning framework for identifying key sentences and detecting events

Wei Wang, Yue Ning, Huzefa Rangwala, Naren Ramakrishnan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

26 Scopus citations

Abstract

State-of-the-art event encoding approaches rely on senten or phrase level labeling, which are both time consuming a infeasible to extend to large scale text corpora and emergi domains. Using a multiple instance learning approach, take advantage of the fact that while labels at the senten level are difficult to obtain, they are relatively easy to gath at the document level. This enables us to view the proble of event detection and extraction in a unified manner. U ing distributed representations of text, we develop a multip instance formulation that simultaneously classifies news ticles and extracts sentences indicative of events without a engineered features. We evaluate our model in its ability detect news articles about civil unrest events (from Spani text) across ten Latin American countries and identify t key sentences pertaining to these events. Our model, trained without annotated sentence labels, yields performance that is competitive with selected state-of-the-art models for event detection and sentence identification. Additionally, qualitative experimental results show that the extracted event-related sentences are informative and enhance various downstream applications such as article summarization, visualization, and event encoding.

Original languageEnglish
Title of host publicationCIKM 2016 - Proceedings of the 2016 ACM Conference on Information and Knowledge Management
Pages509-518
Number of pages10
ISBN (Electronic)9781450340731
DOIs
StatePublished - 24 Oct 2016
Event25th ACM International Conference on Information and Knowledge Management, CIKM 2016 - Indianapolis, United States
Duration: 24 Oct 201628 Oct 2016

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings
Volume24-28-October-2016

Conference

Conference25th ACM International Conference on Information and Knowledge Management, CIKM 2016
Country/TerritoryUnited States
CityIndianapolis
Period24/10/1628/10/16

Keywords

  • CNN
  • Deep learning
  • Event detection
  • Information extraction
  • MIL

Fingerprint

Dive into the research topics of 'A multiple instance learning framework for identifying key sentences and detecting events'. Together they form a unique fingerprint.

Cite this