A text can be plagiarised in different ways. The text may be copied and pasted word by word, parts of the text may be changed, or the whole text may be summarised into one or two lines. Different kinds of plagiarism require different strategies to detect them. But rarely do we know beforehand what type of plagiarism we are dealing with. In this paper we present a system that can detect verbatim...

Error mining is a useful technique for identifying forms that cause incomplete parses of sentences. We extend the iterative method of Sagot and de la Clergerie (2006) to treat n-grams of an arbitrary length. An inherent problem of incorporating longer n-grams is data sparseness. Our new method takes sparseness into account, producing n-grams that are as long as necessary to identify problematic...

Automatic dependency annotations have been used in all kinds of language applications. However, there has been much less exploitation of dependency annotations for the linguistic description of language varieties. This paper presents an attempt to employ dependency annotations for describing style. We argue that for this purpose, linear n-grams (that follow the text’s surface) alone do not appr...

The thiobarbiturates differ from other barbiturates in having a sulfur atom to replace the carbonyl oxygen at the C-2 position. The drug 2-thiobarbituric acid was soluble in 95% ethanol and 5% water for sensitive detection and measurement. All samples were examined at 340 nanometer wavelength. An ultraviolet-visible instrument with one centimeter glass cuvettes was suitable for this assay. The ...

We compare the performance of character n-gram features (n = 3–8) and lexical features (unigrams and bigrams of words), as well as their combinations, on the tasks of authorship attribution, author profiling, and discriminating between similar languages. We developed a single multi-labeled corpus for the three aforementioned tasks, composed of news articles in different varieties of Spanish. We...

We present NN-grams, a novel, hybrid language model integrating n-grams and neural networks (NN) for speech recognition. The model takes as input both word histories as well as n-gram counts. Thus, it combines the memorization capacity and scalability of an n-gram model with the generalization ability of neural networks. We report experiments where the model is trained on 26B words. NN-grams ar...

Statistical n-gram language modeling is used in many domains like speech recognition, language identification, machine translation, character recognition and topic classification. Most language modeling approaches work on n-grams of terms. This paper reports about ongoing research in the MEMPHIS project which employs models based on character-level n-grams instead of term n-grams. The models ar...

A prospective observational study of feeding in low birth weight (LBW) infants with birth weight (BW) of at least 1.8 kg admitted to the Neonatal Intensive Care Unit (NICU) showed that nearly 80% of mothers provided expressed breastmilk (EBM) and a further 14% breastfed their infants before discharge. Weight gain was overall poor at a mean of 9.48 +/- 7.82 grams per kg per day with those on pre...