The study investigated whether the facilitating effect of high text comprehensibility on lay recipients’ inclination to rely on their own decision about scientific claims is mitigated if the presented information is controversial. Moreover, it was assessed whether the impact of both information features is mediated by perceptions of topic complexity. Lay readers read medical text information va...

The NP-complete Permutation Pattern Matching problem asks whether a permutation P (the pattern) can be matched into a permutation T (the text). A matching is an order-preserving embedding of P into T . In the Generalized Permutation Pattern Matching problem one can additionally enforce that certain adjacent elements in the pattern must be mapped to adjacent elements in the text. This paper stud...

Domains such as text, images etc contain large amounts of redundancies and ambiguities among the attributes which result in considerable noise effects (i.e. the data is high dimension). Retrieving the data from high dimensional datasets is a big challenge. Dimensionality reduction techniques have been a successful avenue for automatically extracting the latent concepts by removing the noise and...

Text embedded in video sequences is very important to semantic indexing and content-based retrieval system, especially for large scale news collection. However, its detection and extraction is still an open problem due to the variety of its size and the complexity of the backgrounds. In this paper, we propose an approach for automatic Arabic-text localization based on a novel method for text-li...

Computational approaches to readability assessment are generally built and evaluated using gold standard corpora labeled by publishers or teachers rather than being grounded in observations about human performance. Considering that both the reading process and the outcome can be observed, there is an empirical wealth that could be used to ground computational analysis of text readability. This ...

In this paper we explore to what extent the difficulty of listening items in an English language proficiency test can be predicted by the textual properties of the item text. We show that a system based on multiple text complexity features can predict item difficulty for several different item types and for some items achieves higher accuracy than human estimates of item difficulty.

This paper reviews the processes involved in Natural Language Processing (NLP). It then demonstrates the various kinds of choices that need be taken during the execution of the word morphology, the syntactic text analysis, or text generation components. It compares the time complexity of traditional serial algorithms and examines the possible expected gain in some corresponding parallel counter...