We present a new context-aware method for lexical simplification that uses two free language resources and real web frequencies. We compare it with the state-of-the-art method for lexical simplification in Spanish and the established simplification baseline, that is, the most frequent synonym. Our method improves upon the other methods in the detection of complex words, in meaning preservation,...

Lexical simplification of scientific terms represents a unique challenge due to the lack of a standard parallel corpora and fast rate at which vocabulary shift along with research. We introduce SimpleScience, a lexical simplification approach for scientific terminology. We use word embeddings to extract simplification rules from a parallel corpora containing scientific publications and Wikipedi...

Abstract Users’ reviews contain valuable information which are not taken into account in most recommender systems. According to the latest studies this field, using review texts could only improve performance of recommendation, but it can also alleviate impact data sparsity and help tackle problem. In paper, we present a neural model recommends items by leveraging user reviews. order predict ra...

According to a recent definition by Dey and Abowd, context is any information that can be used to characterize the situation of an entity. An entity is a person, place or object that is considered relevant to the interaction between a user and an application, including the user and the application themselves. A system is context-aware if it uses context to provide relevant information and/or se...

For a finite group G and a subset S of G which does not contain the identity of G , let Cay(G , S) denote the Cayley graph of G with respect to S. If , for all subsets S , T of G of size m , Cay(G , S) Х Cay(G , T) implies S ␣ ϭ T for some ␣ ෈ Aut(G) , then G is said to have the m-DCI property. In this paper , a classification is presented of the cyclic groups with the m-DCI property , which is...

Text detection in natural scene images is an open and challenging problem due to the significant variations of the appearance of the text itself and its interaction with the context. In this paper, we present a novel text detection method combining two main ingredients: the robust extension of Stroke Width Transform (SWT) and the Deep Belief Network (DBN) based discrimination of text objects fr...

Using revision to produce extended natural language text through a series of drafts provides three significant advantages over a traditional natural language generation system. First, it reduces complexity through task decomposition. Second, it promotes text polishing techniques that benefit from the ability to examine generated text in the context of the underlying knowledge from which it was ...

In this paper we present a survey of some most significant spoken English learner corpora created up to date. Spoken learner corpora which include speech generated by learners are important in many areas of research and practice, in particular, for identifying typical pronunciation errors of learners of English as a second language (ESL), English as a foreign language (EFL), or English as a lin...

With the aim of storing learner corpora as well as information about the Basque language students who wrote the texts, two different but complementary databases were created: ERREUS and IRAKAZI. Linguistic and technical information (error description, error category, tools for detection/correction...) will be stored in ERREUS, while IRAKAZI will be filled in with psycholinguistic information (e...