A significant body of work on biomedical text mining is aimed at uncovering meaningful associations between biological entities, including genes. This has the potential to offer new insights for research, uncovering hidden links between genes involved in critical pathways and processes. Recently, high-throughput studies have started to unravel the genetic landscape of chronic lymphocytic leukem...

It is generally recognized that many second language learners have difficulties with cohesion in academic texts.  Writing seems to be the most difficult subject for many students. To produce good writing, it is necessary to know how to organize Theme and Rheme in a text. Thematic structure as an important feature in textual metafunction plays a significant role in promoting the textual coherenc...

This paper uses materials from annotation studies of lexical cohesion (Beigman Klebanov and Shamir, 2005) and of definite reference (Poesio and Vieira, 1998; Vieira, 1998) to discuss the complementary nature of the two processes. Juxtaposing the two kinds of annotation provides a unique perspective for observing the workings of the reader’s common-sense knowledge at two levels of text organizat...

Similarity in contextual behavior between words is considered a source of “lexical cohesion,” which is otherwise hard to measure or quantify. Such contextual similarity is used by an implementation for text segmentation, the VecTile system, which uses precompiled vector representations of words to produce similarity curves over texts. The performance of this system is shown to improve over that...

This paper describes the architecture of UAIC 1 ’s Summarization system participating at MultiLing – 2013. The architecture includes language independent text processing modules, but also modules that are adapted for one language or another. In our experiments, the languages under consideration are Bulgarian, German, Greek, English, and Romanian. Our method exploits the cohesion and coherence p...

Current Statistical Machine Translation (SMT) is significantly affected by Machine Translation (MT) evaluation metric. Nowadays the emergence of document-level MT research increases the demand for corresponding evaluation metric. This paper proposes two superior yet low-cost quantitative objective methods to enhance traditional MT metric by modeling document-level phenomena from the perspective...

This paper presents a machine learning approach to find and classify discourse relations between two unseen sentences. It describes the process of training a classifier that aims to determine (i) if there is any discourse relation among two sentences, and, if a relation is found, (ii) which is that relation. The final goal of this task is to insert discourse connectives between sentences seekin...

Situation model theories of text comprehension consider temporality to be one of the critical dimensions for building a coherent mental representation of described events. Using this framework, three continuous scale measures were developed to assess temporal coherence based on tense, aspect, and adverbial relations. Experts in discourse processing evaluated 150 texts, excerpted from science, h...

Information Summarization is one of the key challenges for current and future information systems. In this paper, we will outline a system that comprises modules for summarizing texts and time series to study the link between the two. Summaries of texts are generated using a lexical analysis of cohesion in texts focusing on key sentences that provide cohesion: by implication, these are the sent...

ReaderBench is an automated software framework designed to support both students and tutors by making use of text mining techniques, advanced natural language processing, and social network analysis tools. Read‐ erBench is centered on comprehension prediction and assessment based on a cohesion-based representation of the discourse applied on different sources (e.g., textual materials, behavior ...