Natural Language Processing (NLP) is that field of computer science which consists of interfacing computer representations of information with natural languages used by humans. It examines the use of computers in understanding and manipulating the natural language text and speech. The main aim of the researchers in this field is to collect the necessary details about how natural languages are b...

One of the most recent developments in NLP is the emergence of linguistic annotation metasystems which make use of existing processing tools and implement pipelined architecture. In this paper we describe a system that offers a new perspective in exploiting NLP meta-systems by providing a common processing framework. This framework supports most of common NLP tasks by chaining tools that are ab...

The role of lexical resources is often understated in NLP research. The complexity of Chinese, Japanese and Korean (CJK) poses special challenges to developers of NLP tools, especially in the area of word segmentation (WS), information retrieval (IR), named entity extraction (NER), and machine translation (MT). These difficulties are exacerbated by the lack of comprehensive lexical resources, e...

The growing need for Chinese natural language processing (NLP) is largely in a range of research and commercial applications. However, most of the currently Chinese NLP tools or components still have a wide range of issues need to be further improved and developed. FudanNLP is an open source toolkit for Chinese natural language processing (NLP), which uses statistics-based and rule-based method...

Nonlinear Model Predictive Control (NMPC) has gained wide attention through the application of dynamic optimization. However, this approach is susceptible to computational delay, especially if the optimization problem cannot be solved within one sampling time. In this paper we propose an advanced-multi-step NMPC (amsNMPC) method based on nonlinear programming (NLP) and NLP sensitivity. This met...

Natural language processing (NLP) systems can help solve the data entry problem by providing coded data from textual reports for clinical applications. A number of NLP systems have shown promise, but have not yet achieved wide-spread use for practical applications. In order to achieve such use, a system must have broad coverage of the clinical domain and not be restricted to limited application...

The role of lexical resources is often understated in NLP research. The complexity of Chinese, Japanese and Korean (CJK) poses special challenges to developers of NLP tools, especially in the area of word segmentation (WS), information retrieval (IR), named entity extraction (NER), and machine translation (MT). These difficulties are exacerbated by the lack of comprehensive lexical resources, e...

International research in NLP is dominated by work on English. NLP techniques and systems can be ported to other natural languages, but this is generally a labour-intensive task, requiring scarce computational and linguistic expertise; hence minority languages are poorly represented in NLP technology. We present an automated approach to porting an NLP technology, the AIML-based chatbot, to new ...

of results Three hundred thirteen patients were included. Most were males (60%) with ages 20-40 years old. About 1/3 (30%) was non-Portuguese. Diagnosis was made by routine serology in 36% of individuals and, in 36%, after development of symptomatic infection. At the time of diagnosis, 42% (n=132) of patients were considered LP. The only risk factor associated with late diagnosis was male gende...