Text mining is a new and exciting area of computer science research that tries to solve the
crisis of information overload by combining techniques from data mining, machine learning …

The Handbook of Natural Language Processing, Second Edition presents practical tools
and techniques for implementing natural language processing in computer systems. Along …

We assume that the tokenization of a sentence is fixed and known at parsing time. That is to
say that dependency parsers will always operate on a pre-tokenized input and are not …

Each year the Conference on Computational Natural Language Learning (CoNLL) 1
features a shared task, in which participants train and test their systems on exactly the same …

Parsing unrestricted text is useful for many language technology applications but requires
parsing methods that are both robust and efficient. MaltParser is a language-independent …

In this paper, we first present a dependency-based method for parser evaluation. We then
use the method to evaluate a broad-coverage parser, called MINIPAR, with the SUSANNE …

Machine learning based on various forms of inductive inference has been used for a wide
range of problems in natural language processing, with syntactic parsing being one of the …

Robustness is a key issue for natural language processing in general and parsing in
particular, and many approaches have been explored in the last decade for the design of …

We present the issues that we have encountered in designing a treebank architecture for
Turkish along with rationale for the choices we have made for various representation …

As part of evaluating a summary automatically, it is usual to determine how much of the
contents of one or more humanproduced 'ideal'summaries it contains. Previous automated …