this study was motivated by three factors, which also contribute to its significance for today’s academic writing. first, research articles are the significant means of communication between the writers all over the world. second, persuasion and organization are crucial notions in academic writing where the authors have to consider the academic audiences and their needs.  third, some writers ar...

This paper examines how object-oriented extensions to the Petri Net formalism provide flexible structuring primitives which can aid the modelling of network protocols. A key benefit is the support for incremental modelling. As a result, a protocol can be modelled as a collection of services, each of which can be expressed as the enhancement of a basic service, in which case, both the structure ...

In open source development, software evolution tasks are usually managed with a bug tracker system, such as Bugzilla [1], and a versioning system, such as CVS [2]. This provides for a huge amount of historical data regarding bug resolutions and new enhancement feature implementations. We discuss how software repositories can help developers in managing a new change request, either a bug or an e...

In this paper we investigate the relation between positive and negative pairs in Textual Entailment (TE), in order to highlight the role of contradiction in TE datasets. We base our analysis on the decomposition of Text-Hypothesis pairs into monothematic pairs, i.e. pairs where only one linguistic phenomenon at a time is responsible for entailment judgment and we argue that such a deeper inspec...

This paper introduces the methods employed by University of Houston team participating in the CL-SciSumm 2017 Shared Task at BIRNDL 2017 to identify reference spans in a reference document given sentences from citing papers. The following approaches were investigated: structural correspondence learning, positional language models, and textual entailment. In addition, we refined our methods from...

We propose new parse-free event-based features to be used in conjunction with lexical, syntactic, and semantic features of texts and hypotheses for Machine Learning-based Recognizing Textual Entailment. Our new similarity features are extracted without using shallow semantic parsers, but still lexical and compositional semantics are not left out. Our experimental results demonstrate that these ...

This paper presents the first round of the task on Cross-lingual Textual Entailment for Content Synchronization, organized within SemEval-2012. The task was designed to promote research on semantic inference over texts written in different languages, targeting at the same time a real application scenario. Participants were presented with datasets for different language pairs, where multi-direct...

In this paper we report the results obtained in the Semantic Textual Similarity (STS) task, with a system primarily developed for textual entailment. Our results are quite promising, getting a run ranked 39 in the official results with overall Pearson, and ranking 29 with the Mean metric.