in any discourse domain, certain chunks are particularly frequent and deserve attention by the novice to be initiated and by the expert to maintain a sense of community. to make a relevant contribution to the awareness about applied linguistics texts and discourse, this study attempted to develop lists of lexical chunks frequently used in the abstracts of applied linguistics journals. the abstr...

For the Authorship Attribution (AA) task, character n-grams are considered among the best predictive features. In the English language, it has also been shown that some types of character n-grams perform better than others. This paper tackles the AA task in Portuguese by examining the performance of different types of character n-grams, and various combinations of them. The paper also experimen...

In this paper, we present an unsupervised two-phase approach to extract keywords from Arabic documents that combines statistical analysis and linguistic information. The first phase detects all the N-grams that may be considered keywords. In the second phase, the N-grams are analyzed using a morphological analyzer to replace the words of the N-grams with their base forms that are the roots for ...

In [GIJ01a, GIJ01b] we described how to use q-grams in an RDBMS to perform approximate string joins. We also showed how to implement the approximate join using plain SQL queries. Specifically, we described three filters, count filter, position filter, and length filter, which can be used to execute efficiently the approximate join. The intuition behind the count filter was that strings that are...

This study was conducted to evaluate the effects of the different levels of vermi (Eisenia fetida) meal on fermented ration in broiler chicken growth and profitability under two management systems. For this purpose, 120 day old broiler chickens (cobb vantress) were tested in a Completely Randomized Design with four (4) dietary treatments: first, the commercial feeds (control), second, 2% vermi ...

Signature-based malicious code detection is the standard technique in all commercial anti-virus software. This method can detect a virus only after the virus has appeared and caused damage. Signature-based detection performs poorly when attempting to identify new viruses. Motivated by the standard signature-based technique for detecting viruses, and a recent successful text classification metho...

There is an inherent redundancy in natural languages whereby certain common phrases (or n-grams) appear frequently in general sentences, each time with the same syntactic analysis. We explore the idea of exploiting this redundancy by pre-constructing the parse structures for these frequent n-grams. When parsing sentences in the future, the parser does not have to re-derive the parse structure f...

We introduce the Rel-grams language model, which is analogous to an n-grams model, but is computed over relations rather than over words. The model encodes the conditional probability of observing a relational tuple R, given that R′ was observed in a window of prior relational tuples. We build a database of Rel-grams co-occurence statistics from ReVerb extractions over 1.8M news wire documents ...

The Burrows-Wheeler Transform (BWT) is a compression method which reorders an input string into the form, which is preferable to another compression. Usually Move-To-Front transform and then Huffman coding is used to the permutated string. The original method [3] from 1994 was designed for an alphabet compression. In 2001, versions working with word and n-grams alphabet were presented. The newe...

A growing body of research has recently been conducted on semantic textual similarity using a variety of neural network models. While recent research focuses on word-based representation for phrases, sentences and even paragraphs, this study considers an alternative approach based on character n-grams. We generate embeddings for character n-grams using a continuous-bag-of-n-grams neural network...