Alexiei Dingli


Demonstration of a Prototype for a Conversational Companion for Reminiscing about Images
Yorick Wilks | Roberta Catizone | Alexiei Dingli | Weiwei Cheng
Proceedings of the ACL 2010 System Demonstrations

Using Dialogue Corpora to Extend Information Extraction Patterns for Natural Language Understanding of Dialogue
Roberta Catizone | Alexiei Dingli | Robert Gaizauskas
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

This paper examines how Natural Language Process (NLP) resources and online dialogue corpora can be used to extend coverage of Information Extraction (IE) templates in a Spoken Dialogue system. IE templates are used as part of a Natural Language Understanding module for identifying meaning in a user utterance. The use of NLP tools in Dialogue systems is a difficult task given 1) spoken dialogue is often not well-formed and 2) there is a serious lack of dialogue data. In spite of that, we have devised a method for extending IE patterns using standard NLP tools and available dialogue corpora found on the web. In this paper, we explain our method which includes using a set of NLP modules developed using GATE (a General Architecture for Text Engineering), as well as a general purpose editing tool that we built to facilitate the IE rule creation process. Lastly, we present directions for future work in this area.


Information Extraction Tools and Methods for Understanding Dialogue in a Companion
Roberta Catizone | Alexiei Dingli | Hugo Pinto | Yorick Wilks
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

This paper discusses how Information Extraction is used to understand and manage Dialogue in the EU-funded Companions project. This will be discussed with respect to the Senior Companion, one of two applications under development in the EU-funded Companions project. Over the last few years, research in human-computer dialogue systems has increased and much attention has focused on applying learning methods to improving a key part of any dialogue system, namely the dialogue manager. Since the dialogue manager in all dialogue systems relies heavily on the quality of the semantic interpretation of the user’s utterance, our research in the Companions project, focuses on how to improve the semantic interpretation and combine it with knowledge from the Knowledge Base to increase the performance of the Dialogue Manager. Traditionally the semantic interpretation of a user utterance is handled by a natural language understanding module which embodies a variety of natural language processing techniques, from sentence splitting, to full parsing. In this paper we discuss the use of a variety of NLU processes and in particular Information Extraction as a key part of the NLU module in order to improve performance of the dialogue manager and hence the overall dialogue system.


Mining Web Sites Using Unsupervised Adaptive Information Extraction
Alexiei Dingli | Fabio Ciravegna | David Guthrie | Yorick Wilks
10th Conference of the European Chapter of the Association for Computational Linguistics