We describe here the technical details of our participation to PAN 2012’s “traditional” authorship attribution tasks. The main originality of our approach lies in the use of a large quantity of varied features to represent textual data, processed by a maximum entropy machine learning tool. Most of these features make an intensive use of natural language processing annotation techniques as well ...

Tsonis and Tsonis [1] study rank-ordered distributions of the number of occurrences of protein domains in four different organisms, and they argue that the power-law decay, f ϰ 1/r, of the number f of occurrences of a protein domain with its rank r suggests the presence of linguistic features in eukaryotic genomes, and that this finding " may lead to important clues about the evolution of langu...

In this paper a combination of linguistic and structural information is used for the extraction of Dutch definitions. The corpus used is a collection of Dutch texts on computing and elearning containing 603 definitions. The extraction process consists of two steps. In the first step a parser using a grammar defined on the basis of the patterns observed in the definitions is applied on the compl...

This paper explores two linguistically motivated restrictions on the set of words used for topic tracking on newspaper articles: named entities and headline words. We assume that named entities is one of the linguistic features for topic tracking, since both topic and event are related to a specific place and time in a story. The basic idea to use headline words for the tracking task is that he...

This paper proposes a method to acquire linguistic features from a corpus of short sentences by extracting analogous sentences like what ’s the next station ? : where ’s the bus station ? :: what is the next stop ? : where is the bus stop ? The procedures used to construct clusters of analogous sentences are presented. Experiments performed on roughly 40,000 short sentences from the tourism dom...

This article investigates the effect of a set of linguistically motivated features on argument disambiguation in data-driven dependency parsing of Swedish. We present results from experiments with gold standard features, such as animacy, definiteness and finiteness, as well as corresponding experiments where these features have been acquired automatically and show significant improvements both ...

Recent studies (e.g., Graesser et al., 2011; McNamara, 2013) have used Coh-Metrix, an automated text analyzer, to assess differences in language use across different academic disciplines. McNamara (2013) reported that texts in the natural sciences were characterized by lower narrativity and word concreteness than texts in the language arts, while being higher in syntactic simplicity and referen...

Neural machine translation has recently achieved impressive results, while using little in the way of external linguistic information. In this paper we show that the strong learning capability of neural MT models does not make linguistic features redundant; they can be easily incorporated to provide further improvements in performance. We generalize the embedding layer of the encoder in the att...

This paper explores a new approach to speech recognition in which sub-word units are modeled in terms of linguistic features. Specifically, we have adopted a scheme of modeling separately the manner and place of articulation for these units. A novelty of our work is the use of a generalized definition of place of articulation that enables us to map both vowels and consonants into a common lingu...

The paper focuses on neologisms and medical terms related to COVID-19, which affects almost all elements of life, including social linguistic spheres. Evidently, the COVID-19 pandemic has affected speech communication behavior people in society. This resulted introduction novel terminology, specialized language abbreviations, that allow individuals articulate their emotions ideas. These have ga...