N-gram | EPFL Graph Search

Are you an EPFL student looking for a semester project?

Work with us on data science and visualisation projects, and deploy your project as an app on top of GraphSearch.

n-gram is a series of n adjacent letters (including punctuation marks and blanks), syllables, or rarely whole words found in a language dataset; or adjacent phonemes extracted from a speech-recording dataset, or adjacent base pairs extracted from a genome. They are collected from a text or speech corpus. If Latin numerical prefixes are used, then n-gram of size 1 is called a "unigram", size 2 a "bigram" (or, less commonly, a "digram") etc. If, instead of the Latin ones, the English cardinal numbers are furtherly used, then they are called "four-gram", "five-gram", etc. Similarly, using Greek numerical prefixes such as "monomer", "dimer", "trimer", "tetramer", "pentamer", etc., or English cardinal numbers, "one-mer", "two-mer", "three-mer", etc. are used in computational biology, for polymers or oligomers of a known size, called k-mers. When the items are words, n-grams may also be called shingles. Examples Figure 1 shows several example sequences and the c

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications

Related people

Related units

Related concepts

Related courses

Related lectures

Summary

Official source

About this result

Related publications (9)

Related publications

Related people

Related units

Related concepts (9)

Related concepts

Related courses (5)

Related courses

Related lectures (20)

Related lectures

Analyse multi-échelle de n-grammes sur 200 années d'archives de presse

Vincent Christian Buntinx

The recent availability of large corpora of digitized texts over several centuries opens the way to new forms of studies on the evolution of languages. In this thesis, we study a corpus of 4 million press articles covering a period of 200 years. The thesis tries to measure the evolution of written French on this period at the level of words and expressions, but also in a more global way by attempting to define integrated measures of linguistic evolution. The methodological choice is to introduce a minimum of linguistic hypotheses in this study by developing new measures around the simple notion of n-gram, a sequence of n consecutive words. The thesis explores on this basis the potential of already known concepts as temporal frequency profiles and their diachronic correlations, but also introduces new abstractions such as the notion of resilient linguistic kernel or the decomposition of profiles into solidified expressions according to simple statistical models. Through the use of distributed computational techniques, it develops methods to test the relevance of these concepts on a large amount of textual data and thus allows to propose a virtual observatory of the diachronic evolutions associated with a given corpus. On this basis, the thesis explores more precisely the multi-scale dimension of linguistic phenomena by considering how standardized measures evolve when applied to increasingly long n-grams. The discrete and continuous scale from the isolated entities (n=1) to the increasingly complex and structured expressions (1 < n < 10) offers a transversal axis of study to the classical differentiations that ordinarily structure linguistics: syntax, semantics, pragmatics, and so on. The thesis explores the quantitative and qualitative diversity of phenomena at these different scales of language and develops a novel approach by proposing multi-scale measurements and formalizations, with the aim of characterizing more fundamental structural aspects of the studied phenomena.

EPFL2017

Benign synthesis of quinolinecarboxamide ligands, H(2)bqbenzo and H(2)bqb and their Pd(II) complexes: X-ray crystal structure, electrochemical and antibacterial studies

Maryam Bagheri, Farzaneh Fadaei Tirani

Two carboxamide ligands, H(2)bqbenzo {3,4-bis(2-quinolinecarboxamido)benzophenone} and H(2)bqb {N,N-bis[(2-quinolinecarboxamide)-1,2-benzene]}, have been prepared using tetrabutylammonium bromide as an environmentally benign reaction medium. Two new Pd(II) complexes, [Pd-II(bqbenzo)] (1) and [Pd-II(bqb)] (2), have been synthesized, characterized, and their structures determined by single crystal X-ray diffraction. The di-anionic ligands, bqbenzo(2-) and bqb(2-), are coordinated via two N-amide atoms and the nitrogens of the two quinoline rings, with Pd-N-amide

Taylor & Francis Ltd2017

We first present our work in machine translation, during which we used aligned sentences to train a neural network to embed n-grams of different languages into an d-dimensional space, such that n-grams that are the translation of each other are close with respect to some metric. Good n-grams to n-grams translation results were achieved, but full sentences translation is still problematic. We realized that learning semantics of sentences and documents was the key for solving a lot of natural language processing problems, and thus moved to the second part of our work: sentence compression. We introduce a flexible neural network architecture for learning embeddings of words and sentences that extract their semantics, propose an efficient implementation in the Torch framework and present embedding results comparable to the ones obtained with classical neural language models, while being more powerful.

2009

Natural language processing

Natural language processing (NLP) is an interdisciplinary subfield of linguistics and computer science. It is primarily concerned with processing natural language datasets, such as text corpora or sp

Language model

A language model is a probabilistic model of a natural language that can generate probabilities of a series of words, based on text corpora in one or multiple languages it was trained on. Large lang

Speech recognition

Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken

CS-431: Introduction to natural language processing

The objective of this course is to present the main models, formalisms and algorithms necessary for the development of applications in the field of natural language information processing. The concepts introduced during the lectures will be applied during practical sessions.

DH-405: Foundations of digital humanities

This course gives an introduction to the fundamental concepts and methods of the Digital Humanities, both from a theoretical and applied point of view. The course introduces the Digital Humanities circle of processing and interpretation, from data acquisition to new understandings.

CS-423: Distributed information systems

This course introduces the key concepts and algorithms from the areas of information retrieval, data mining and knowledge bases, which constitute the foundations of today's Web-based distributed information systems.