Software Developer - Bioinformatics

UQAM | Université du Québec à Montréal

  • Workflow Mining
  • Ontologies
  • Sequential Pattern Mining
  • Information Extraction
  • Recommender Systems

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Work in progress

Ontology-based workflow extraction from texts using word sense disambiguation

bioRxiv 082784; doi: http://dx.doi.org/10.1101/082784
A. Halioui | A.B. Diallo | P. Valtchev

This paper introduces a method for automatic workflow extraction from texts using Process-Oriented Case-Based Reasoning (POCBR). While the current workflow management systems implement mostly different complicated graphical tasks based on advanced distributed solutions (e.g. cloud computing and grid computation) ... (read more)



Towards an ontology-based recommender system for relevant bioinformatics workflows

submitted to BMC Bioinformatics:
A. Halioui | A.B. Diallo | P. Valtchev

Ontology- powered pattern mining : discovery of frequent abstract workflows in phylogeny

submitted to ACM SAC 2017:
A. Halioui | A.B. Diallo | P. Valtchev

CASTOR: A machine learning approach for generic viral genome classification

submitted to BMC Bioinformatics:
M.A. Remita | A. Halioui | A.A.M. Diouara | B. Daigle | G. Kiani | A.B. Diallo

Collaborative Repository for Research Corpora of Linked Digital Objects

E. Rizkallah | A. Halioui

International Conference on Statistical Analysis of Textual Data, May. 2016

This text exposes the rational, theoretic and main functionalities of a Web application to a collaborative repository for research corpora: RECOLTE. Steeped in ... (read more)


Acquisition of generic problem solving knowledge through information extraction and pattern mining

A. Halioui | A.B. Diallo | P. Valtchev

ICTAI 27th IEEE International Conference on Tools with Artificial Intelligence, Nov. 2015

In many technical domains, the generic problem-solving knowledge is scarce even though a large number of concrete resolutions exist and are well documented. This makes the machine learning from ... (read more)

Workflow Mining : Discovering Generalized Process Models from Texts

A. Halioui | A.B. Diallo | P. Valtchev

Workshop IJCAI BAI: Bioinformatics and Artificial Intelligence, Jun. 2015

Contemporary workflow management systems are driven by explicit process models specifying the inter-dependencies between tasks. Creating these models is a challenging and time-consuming process. Existing approaches for mining concrete workflows into models tackle design aspects with no regard for the diverging abstraction levels of the tasks. ... (read more)


Supervised Machine Learning by Generation of Rules: One Class Against All Others

A. Halioui | A. Borgi

SITA’10: 6th Conf. devoted to the theory and applications of intelligent systems, Rabat (Morocco), Nov. 2015

Several methods and techniques for data classification are available within the framework of supervised induction. In supervised machine learning by generation of rules, classification rules are automatically built at the learning phase. At classification phase, an inference engine uses rules to classify new objects. SUCRAGE is a machine learning system under this framework where ... (read more)

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