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I am PhD student in the Computer Science PhD Program of Cinvestav - Tamaulipas (Mexico). My doctoral work is about ontology learning. My thesis advisor is Dr. Ivan Lopez Arevalo. Since July 2011 until February 2012, I was a research visitor in DERI Unit for Natural Language Processing, NUI Galway, Ireland under supervision of Dr. Paul Buitelaar.

me@DBLP / ACM / DERI UNLP / MCyTI

Once we accept our limits, we go beyond them. Albert Einstein

"Ethical axioms are found and tested not very differently from the axioms of science. Truth is what stands the test of experience."


Albert Einstein

Research

My research interests are:
- Ontology learning
- Natural Language Processing
- Semantic Web

After completion of my Bachelor in Computer Science I studied a Master in Science and Information Technology. My Master work was about 1) representing corporate knowledge in a OWL ontology and 2) the development of a tool for editing and browsing such ontology, the tool allows annotate heterogeneous resources for a corporate semantic web. Now, in my PhD work I am interested in ontology learning from textual resources, particurlarly how add more expressiveness to the ontology (e.g. by adding class expression axioms). Previous to getting axioms, I can obtain a well-defined ontology structrure from text by using text clustering techniques, lexical-syntactic patterns, and the Web as knowledge source. I think it could be possible obtain a model in Description Logic to represent such knowledge with a logical formalism.

PhD (Computer Science)

Thesis: Ontology Learning by using text clustering techniques

Supervised by: Ivan Lopez-Arevalo

Abstract:

Ontologies provide a structural organizational knowledge, they support the exchange and sharing of information. Ontology learning techniques from text have emerged as a set of techniques to get ontologies from unstructured information. Many works currently focus on inexpressive ontologies. Ontologies can describe more than just terms, attributes, and the relations between terms. Ontologies can enable logical inference on facts. Only a few approaches present methods for enriching inexpressive ontologies with axioms which is based on a syntactic analysis. In this research, ontology learning techniques will be proposed and developed to automatically discover terms, concepts, relations, and axioms from documents.

Datasets

M. Sc. (Science and Technology Information)

Thesis: Distributed allocation of a Corporate Semantic Web

Supervised by: Carolina Medina-Ramirez and Ricardo Marcelin-Jimenez

Abstract:

The huge amount of information available on the Web has become overwhelming problem, this problem is faced also by organizations but in a different scale. In fact, representation, search and exchange of information have become crucial operations, not only for individuals but also for organizations (scientific communities or companies). In this masther thesis we focused in incorporating semantic representation, storage and retrieval capabilities in a P2P corporate memory. By semantic capabilities, we mean the key elements of Semantic Web, i.e. ontologies, annotations and those languages supporting knowledge representation. We proposed a method to allocate a corporate semantic web in a distributed storage system. The deployment of this corporate semantic web comprises an instance of the graph embedding problem, we decided to tackle this challenge using a well-know meta-heuristic called Ant Colony Optimization.

When you can do the common things of life in an uncommon way you will command the attention of the world. George Washington Carver (Scientist)