This study focuses on the effect of user-friendly, impersonal, and hybrid texts on the reading comprehension ability of Iranian foreign language learners. Forty-five students of AlzahraUniversity were selected on the basis of their performance in a recent TOEFL. They were given three different texts (each group of 15 students was given one type) describing the same area of English usage, w...

This commentary responds to Eric Magrane’s welcome focus on the possibilities of ‘climate geopoetics’ as a way accessing and thinking environmental crisis differently. It explores problem approaching general through particular affordances that poetry provides in making this leap. In addition, it questions veneration poet poem and, building experiments both poets academics, argues for embrace hy...

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 ...

In this paper, we propose a document vector space model where weights of noun terms vary depending on positions within the texts of blog entries as search results. We extend “extended anchor texts” (i.e., extra texts surrounding anchor texts) with the exponential potential such that the weight of a noun term decreases exponentially as the distance between the term and link increases. In order t...

Gender Identification is a task where we have to identify the gender of the author for written texts. An hybrid approach has been designed by combining deep neural network and a rule-based classifier for russian texts. LSTM and BiLSTM have been used as a part of Neural Network due to their capability to learn long-term dependencies.

In this article we present a hybrid approach for automatic summarization of Spanish medical texts. There are a lot of systems for automatic summarization using statistics or linguistics, but only a few of them combining both techniques. Our idea is that to reach a good summary we need to use linguistic aspects of texts, but as well we should benefit of the advantages of statistical techniques. ...

We present an experimental study of the performance of a hybrid semantic and linguistic system for recognizing and linking entities from formal and informal texts. In the current literature, systems are generally tailored to one or a few types of textual documents (e.g. narrative texts, newswire articles, informal text such as microposts). In contrast, we assess the performance of a hybrid appr...