Natural Language Processing

Natural Language processing (NLP) is a field of computer science and linguistics concerned with the interactions between computers and human (natural) languages.


One of the long-standing challenges in natural language processing is uniquely identifying entities in text, which when performed accurately and with formal ontologies, supports efforts such as semantic search and question-answering.

Physician logs of Medical ICU admission requests, which included clinical presentation and triage decisions, were prospectively collected over one year at an academic tertiary care center.

We present an end-to-end approach that takes unstructured textual input and generates structured output compliant with a given vocabulary.

Machine learning allows computers to learn a model for a given task, such as face recognition, with a high degree of accuracy, using data. However, after these models are generated, they are often treated as black boxes by developers and the limitations of a model are often unknown to end-users.

This paper compares three commitment strategies for HTN planning: (1) a strategy that delays variable bindings as much as possible; (2) a strategy in which no non-primitive task is expanded until all variable constraints are committed; and (3) a strategy that chooses between expansion and variabl

In this paper we explain how we applied genetic programming to behavior-based team coordination in the RoboCup Soccer Server domain. Genetic programming is a promising new method for automatically generating functions and algorithms through natural selection.

CALL FOR PAPERS

Earth Science Informatics, Special Issue - Semantic e-Science

Guest Editors:

One of the long-standing challenges in natural language processing is uniquely identifying entities in text, which when performed accurately and with formal ontologies, supports efforts such as semantic search and question-answering.

Managing a complex illness often requires different treatment regimens spread over a long time. The complexity of these potentially life-threatening diagnoses can be daunting to patients while they are most vulnerable.

We are developing prototypes that explicate our vision of connecting personal medical data to scientific literature as well as to emerging grey literature (e.g., community forums) to help people find and understand information relevant to complex medical journeys.