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Author:Tirunagari, Santosh
Title:Mining causal relations from maritime accident investigation reports
Publication type:Master's thesis
Publication year:2013
Pages:x + 58 s. + liitt. 6      Language:   eng
Department/School:Tietotekniikan laitos
Main subject:Informaatiotekniikka   (T-61)
Supervisor:Oja, Erkki
Instructor:Lindh-Knuutila, Tiina ; Hänninen, Maria
OEVS:
Electronic archive copy is available via Aalto Thesis Database.
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Location:P1 Ark Aalto  3928   | Archive
Keywords:pattern classification
connectives method
causal relations
SVM
naive Bayes
information extraction
MAIB
Abstract (eng): Text mining is a process of extracting information of interest from text.
Such a method includes techniques from various areas such as Information Retrieval (IR), Natural Language Processing (NLP), and Information Extraction (IE).
In this thesis, text mining methods are applied to extract causal relations from maritime accident investigation reports collected from the Marine Accident Investigation Branch (MAIB).
These causal relations provide information on various mechanisms behind accidents, including human and organizational factors relating to the accident.
The objective of this thesis is to facilitate the analysis of the maritime accident investigation reports, by means of extracting contributory causes with more feasibility.
A careful investigation of contributory causes from the reports provides opportunity to improve safety in future.

Two methods have been employed in this thesis to extract the causal relations.
They are 1) Pattern classification method and 2) Connectives method.
The earlier one uses na'ive Bayes and Support Vector Machines (SVM) as classifiers.
The latter simply searches for the words connecting cause and effect in sentences.

The causal patterns extracted using these two methods are compared to the manual (human expert) extraction.
The pattern classification method showed a fair and sensible performance with F-measure(average) = 65% when compared to connectives method with F-measure(average) = 58%.
This study is evidence, that text mining methods could be employed in extracting causal relations from marine accident
ED:2013-09-26
INSSI record number: 47260
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