• 168 Citations
  • 5 h-Index
19942018
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Personal profile

Biography

Most Significant Research Contributions

My research contribution is centered on the application of theoretical linguistics to specific real-world problems, in particular to automated text-based question answering and summarisation. Since 2009 I have focused on medical text processing.

I joined the University of Zurich and became the principal researcher in the ExtrAns and WebExtrAns projects (from 1996 to 2001). Both projects were based on the development of answer extraction systems. Answer extraction systems locate those sentences in the source text that contain the answer posed by the user. The outcome of the project was a working system that handles questions about 500 Linux/Unix documentation documents ("manpages"). I was the principal designer of the overall system and the integration of all modules. I was also the principal contributor to the design of the logical forms and the question-answering method that used the logical forms. The success of ExtrAns and WebExtrAns is evident from the fact that the system is cited as a pioneering question-answering system, an example of a question answering system of technical domains, and an example of the use of logical forms for question answering.

In Macquarie University I established the AnswerFinder project. AnswerFinder is a question answering system that combines the use of logical information (inspired from ExtrAns and WebExtrAns), state-of-the-art approaches in question answering, and innovative graph-based machine learning methods to find the exact answer to the user question. AnswerFinder has participated in the question answering track of the Text REtrieval conference (TREC), the main international forum for the evaluation of question-answering systems, between 2003 and 2006. AnswerFinder is in fact the only Australian-based question answering system that has participated in the question answering track of TREC.

Since 2009 I have led various projects related to the development and application of text-processing technologies that help the medical doctor find and appraise clinical evidence found in the vast resources of medical publications. I have gathered a summarisation corpus sourced from the Journal of Family Practice, and used the corpus to develop and evaluate techniques for text summarisation, clustering, keyword exraction, and appraisal of the medical evidence.

Biography

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  • 26 Similar Profiles
Medicine Engineering & Materials Science
Learning systems Engineering & Materials Science
Semantics Engineering & Materials Science
Linguistics Engineering & Materials Science
Information retrieval Engineering & Materials Science
Classifiers Engineering & Materials Science
Syntactics Engineering & Materials Science
Information retrieval systems Engineering & Materials Science

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Projects 2009 2017

A GPU-based Cluster for Computing

Dras, M., Johnson, M., Mans, B., Molla-Aliod, D. & Honnibal, M.

1/01/1331/12/13

Project: Research

Optimization Techniques for Human Language Technology

Molla-Aliod, D., Johnson, M., Ekbal, A., Saha, S. & Bhattacharyya, P.

6/08/1230/04/13

Project: Research

Research Outputs 1994 2018

Macquarie University at BioASQ 6b: deep learning and deep reinforcement learning for query-based multi-document summarisation

Molla, D., 2018, The 6th BioASQ Workshop: A challenge on large-scale biomedical semantic indexing and question answering: Proceedings of the Workshop. Stroudsburg: Association for Computational Linguistics, p. 22-29 8 p.

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

Reinforcement learning
Neural networks
Deep learning
Experiments

Overview of the 2018 ALTA Shared Task: classifying patent applications

Molla, D. & Seneviratne, D., Dec 2018, Proceedings of the Australasian Language Technology Association Workshop 2018. Kim, S. M. & Zhang, X. J. (eds.). Association for Computational Linguistics (ACL), p. 84-88 5 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearch

Open Access

Supervised machine learning for extractive query based summarisation of biomedical data

Mandeep Kaur & Molla, D., 2018, Ninth International Workshop on Health Text Mining and Information Analysis (LOUHI): Proceedings of the Workshop. Stroudsburg: Association for Computational Linguistics, p. 29-37 9 p.

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

Learning systems
Automation

Automated text summarisation and evidence-based medicine: a survey of two domains

Sarker, A., Molla, D. & Paris, C., 25 Jun 2017, (Submitted) Arxiv.org pre-prints. 35 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearch

Medicine
Processing

CSIRO at 2017 TREC Precision Medicine Track

Nguyen, V., Karimi, S., Falamaki, S., Molla, D., Paris, C. & Wan, S., 2017, The Twenty-Sixth Text REtrieval Conference (TREC 2017) Proceedings. National Institute of Standards and Technology, 5 p.

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

Merging
Medicine
Genes