Multiple sequence alignment techniques have recently gained popularity in the Natural Language community, especially for tasks such as machine translation, text generation, and paraphrase identification. Prior work falls into two categories, depending on the type of input used: (a) parallel corpora (e.g., multiple translations of the same text) or (b) comparable texts (non-parallel but on the s...

This paper presents computational work to detect satire/sarcasm in long commentaries on Italian politics. It uses the lexica extracted from the manual annotation based on Appraisal Theory, of some 30K word texts. The underlying hypothesis is that using this framework it is possible to precisely pinpoint ironic content through the deep semantic analysis of evaluative judgement and appreciation. ...

This paper presents a successful approach for domain adaptation of a dependency parser via self-training. We improve parsing accuracy for out-of-domain texts with a self-training approach that uses confidence-based methods to select additional training samples. We compare two confidence-based methods: The first method uses the parse score of the employed parser to measure the confidence into a ...

In this position paper we describe the actual state of the development of an integrated set of tools (called EXCOM) for automatic semantic annotation. Annotation is generally used as an operation for marking textual segments to express some morphological and syntactic information. Establishing the semantic web on a large scale implies the widespread annotation of web documents with ontologybase...

In this paper we show how a vector representation of words based on word embeddings can help to improve the results in tasks focused on the semantic similarity of texts. Thus we have experimented with two methods that rely on the vector representation of words to calculate the degree of similarity of two texts, one based on the aggregation of vectors and the other one based on the calculation o...

This paper presents the first results on detecting informality, machine and human translations in the Finnish Internet Parsebank, a project developing a large-scale, web-based corpus with full morphological and syntactic analyses. The paper aims at classifying the Parsebank according to these criteria, as well as studying the linguistic characteristics of the classes. The features used include ...

The similarity relation of a number of texts is important not only for congress organizers (who need to group the proposed contributions to meaningful sessions) but to everybody who wants to find certain information within a larger number of texts. Existing information retrieval methods compare texts according to their similarity. Because these methods mostly remain on the surface of the words,...

Optical Character recognition is used to digitize and reproduce texts that have been produced with non-computerized system. Digitizing texts also helps reduce storage space. Editing and Reprinting of Text document that were printed on paper are time consuming and labour intensive. Optical Character recognition is also useful for visually impaired people who cannot read Text document, but need t...

This paper deals with the problem of automatic language identification of noisy texts, which represents an important task in natural language processing. Actually, there exist several works in this field, which are based on statistical and machine learning approaches for different categories of texts. Unfortunately, most of the proposed methods work fine on clean texts or long texts, but often ...