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CW 2012_06
Oleksandr Kolomiyets
Algorithms for temporal information processing of text and their applications
March 9, 2012
Advisor(s): Sien Moens, Danny De Schreye
Abstract
Temporal information processing of text is a complex information extraction task in which temporally relevant information in text has to be extracted and properly represented in order to be used by a machine. In general the temporal information processing task regards the major concepts of temporal cognition such as time, events, and relations between events and times when they are encoded in language. This work explores the algorithms for temporal information processing of text and focuses on the automated extraction of temporal information. Three major temporal concepts in language are identified: time expressions - expressions in text that denote time, temporal events - events that happen or last in time, and temporal relations between events and times. With respect to this distinction temporal information processing of text can be divided into a number of corresponding sub-tasks, such as recognition and normalization of time expressions, recognition of events, and recognition of temporal relations between events and times. In this thesis we describe approaches for automated recognition and representation of times, events, and recognition of temporal relations performed by means of computer algorithms. The proposed algorithms are based on supervised statistical machine learning methods that sometimes are accompanied by symbolic rule-based approaches.
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