Open Data Platform for Knowledge Access in Plant Health Domain : VESPA Mining

Important data are locked in ancient literature. It would be uneconomic to produce these data again and today or to extract them without the help of text mining technologies. Vespa is a text mining project whose aim is to extract data on pest and crops interactions, to model and predict attacks on crops, and to reduce the use of pesticides. A few attempts proposed an agricultural information access. Another originality of our work is to parse documents with a dependency of the document architecture

Research on Reasoning and Modeling of Solving Mathematics Situation Word Problems of Primary Schools

[[abstract]]This research developed a web-based reasoning of mathematical situation word problems using the natural language processing technology. Our system provided the steps of morphological analysis, syntax analysis, semantic analysis and rule judgment to infer the semantic structure and operational structure of situation word problems. It also adopted the language of MathML and SVG to provide the web-based illustration of solving procedure in mathematical situation word problems. Keywords: situation word problem; natural language processing; MathML; SVG

Improving Supervised Classification Using Information Extraction

Peer reviewe

Protein-protein interaction: A supervised learning approach

Master'sMASTER OF SCIENC

Geospatial phrase grounding and disambiguation

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 101-107).GeoCoder is a spatial reasoning system that converts natural language inputs into a set of precise spatial coordinates to display on a map. GeoCoder's spatial knowledge is represented in a set of ontologies. GeoCoder parses input phrases and adds location reference individuals to its ontology model. Relationships between location references are recognized based on mid-level structural patterns in the parsed phrase. GeoCoder grounds (or finds possible geometries for) location references in an iterative process, in which locations are grounded based on their relationships to previously grounded locations. GeoCoder improves upon previous systems by grounding and disambiguating at the phrase level, interpreting parses with rules that match mid level structure patterns, expressing disambiguation heuristics in ontologies, and improving scalability by separating grounding from reasoning about relationships.by Amy Michelle Slagle.M.Eng

Relation extraction for information extraction from free text

Ph.DDOCTOR OF PHILOSOPH