ABSTRACT
Automated event extraction remains a very difficult challenge requiring information analysts to manually identify key events of interest within massive, dynamic data. Many techniques for extracting events rely on domain specific natural language processing or information retrieval techniques. As an alternative, this work focuses on detecting events based on identifying event characteristics of interest to an analyst. An evolutionary algorithm is developed as a proof of concept to demonstrate this approach. Initial results indicate that this approach represents a feasible approach to identifying critical event information in a massive data set with no apriori knowledgeof the data set.
- Wikipedia: Danish cartoons, Current March 2007, http://en.wikipedia.org/wiki/Jyllands-Posten_Muhammad_cartoons_controversyGoogle Scholar
- Huttunen, S., Yangarber, R., and Grishman, R. "Complexity of Event Structure in IE Scenarios", in Proc of the 19th International Conf. on Computational Linguistics, August 2002. Google ScholarDigital Library
- Turmo, J., Ageno, A., and Catala, N. "Adaptive Information Extraction", ACM Computing Surveys, Vol. 38, No. 2, July 2006. Google ScholarDigital Library
- Patton, R.M. Application of Intelligent Method for Improved Testing and Evaluation of Simulation Systems Software. Ph.D. Thesis, University of Central Florida, Orlando, FL, 2002. Google ScholarDigital Library
- Wikipedia: Madrid train bombings, Current March 2007, http://en.wikipedia.org/wiki/11_March_2004_Madrid_attacksGoogle Scholar
- Bertaux, J.L., et. al. "Monitoring solar activity on the far side of the Sun from sky reflected Lyman alpha radiation", Geophysical Research Letters, Vol. 27, No. 9, pages 1331--1334, May 2000.Google ScholarCross Ref
- Marcy, G.W. and Butler, R. P., "Detection of Extrasolar Giant Planets", Annual Review of Astronomy and Astrophysics Vol 36: 57--97, September 1998.Google ScholarCross Ref
- Yang, Y., Pierce, T., and Carbonell, J. "A Study on Retrospective and On-Line Event Detection", in Proc. of the 21st annual international ACM SIGIR, August 1998. Google ScholarDigital Library
- Allan, J., Papka, R., and Lavrenko, V. "On-line New Event Detection and Tracking", in Proc. of the 21st annual international ACM SIGIR, August 1998. Google ScholarDigital Library
- Yang, Y., Ault, T., Pierce, T., and Lattimer, C. "Improving text categorization methods for event tracking", in Proc. of the 23rd annual international ACM SIGIR, July 2000. Google ScholarDigital Library
- Salton, G., Wong, A., and Yang, C. S., "A Vector Space Model for Automatic Indexing", Communications of the ACM, Vol. 18, No. 11, pages 613--620, 1975. Google ScholarDigital Library
- Reed, J., et al. "TF-ICF: A New Term Weighting Scheme for Clustering Dynamic Data Streams" in Proc. of the 5th International Conference on Machine Learning and Applications (ICMLA'06). Orlando, FL., 2006. Google ScholarDigital Library
- LingPipe, Current March 2007, http://www.alias-i.com/lingpipe/Google Scholar
- Stanford Log-linear Part-Of-Speech Tagger, Current March 2007, http://nlp.stanford.edu/software/tagger.shtmlGoogle Scholar
- Dasgupta, D. and McGregor, D.R. "Species adaptation to nonstationary environments: A structured genetic algorithm" Presented at Artificial Life III workshop, Santa Fe, New Mexico, June 1992.Google Scholar
- Dasgupta, D. and McGregor, D.R. "Nonstationary Function Optimization using the Structured Genetic Algorithm" In Proc. of Parallel Problem Solving From Nature Conference, Brussels, Belgium, September 1992.Google Scholar
- Mahfoud, S.W. Niching Methods for Genetic Algorithms. Masters Thesis, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, 1995. Google ScholarDigital Library
Index Terms
- Discovering event evidence amid massive, dynamic datasets
Recommendations
Discovering event episodes from news corpora: a temporal-based approach
ICEC '09: Proceedings of the 11th International Conference on Electronic CommerceWhen performing environmental scanning, organizations typically deal with a numerous of events and topics about their core business, relevant technique standards, competitors, and market, where each event or topic to monitor or track generally is ...
Where the Event Lies: Predicting Event Occurrence in Textual Documents
SIGIR '16: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information RetrievalManually inspecting text in a document collection to assess whether an event occurs in it is a cumbersome task. Although a manual inspection can allow one to identify and discard false events, it becomes infeasible with increasing numbers of ...
Improving Event Detection by Automatically Assessing Validity of Event Occurrence in Text
CIKM '15: Proceedings of the 24th ACM International on Conference on Information and Knowledge ManagementManually inspecting text to assess whether an event occurs in a document collection is an onerous and time consuming task. Although a manual inspection to discard the false events would increase the precision of automatically detected sets of events, it ...
Comments