In this paper, we present an innovative method for multi-label text classification. Our method uses Lucene to index texts and then assigns one or more classes to a new text based on its similarity relative to an annotated corpus. For finer granularity, we split the text into phrases, and then we focus on the noun phrases. Instead of classifying the entire text, we classify each noun phrase. The...

In this study, we describe the use of back-channelling patterns extracted from a dialogue corpus as a mean to characterising text-based dialogue systems. Our goal was to provide system users with the feeling that they are interacting with distinct individuals rather than artificially created characters. An analysis of the corpus revealed that substantial difference exists among speakers regardi...

During the last decade we have attended to an impressive development of mobile communications which, unfortunately, deaf and hearing-impaired community cannot (in principle) take advantage of. In order to favour this people to take part in the Information Society, we have designed and developed some PC-based systems and applications which will provide several text-based services to them, such a...

Tools for mining information from data can create added value for the Iqternet. As the majority of electronic documents available over the network are in unstructured textual form, extracting useful information from a document usually involves information retrieval techniques or manual processing. This paper presents a novel approach to mining information from HTML documents using tree-structur...

Detection of discourse structure is crucial in many text-based applications. This paper presents an original framework for describing textual parallelism which allows us to generalize various discourse phenomena and to propose a unique method to recognize them. With this prospect, we discuss several methods in order to identify the most appropriate one for the problem, and evaluate them based o...

Recent work has shown that the integration of visual information into text-based models can substantially improve model predictions, but so far only visual information extracted from static images has been used. In this paper, we consider the problem of grounding sentences describing actions in visual information extracted from videos. We present a general purpose corpus that aligns high qualit...

Nowadays, plagiarism detection becomes as one of major problems in the text mining field. New coming technologies have made plagiarisation easy and more feasible. Therefore, it is vital to develop automatic system to detect plagiarisation in different contents. In this paper, we propose a trie to compare source and suspicious text documents. We use PersianPlagDet text documents as a case study....

In this paper we investigate the task of text simplification for Brazilian Portuguese. Our purpose is three-fold: to introduce a simplification tool for such language and its underlying development methodology, to present an on-line authoring system of simplified text based on the previous tool, and finally to discuss the potentialities of such technology for education. The resources and tools ...

This paper describes the model we designed for the word segmentation bakeoff on Chinese micro-blog data in the 2nd CIPS-SIGHAN joint conference on Chinese language processing. We presented a linear-time incremental model for word segmentation where rich features including character-based features, word-based features as well as other possible features can be easily employed. We report the perfo...

Use of highlighting is a prevalent study strategy among students, but evidence regarding its benefit for learning is mixed. We examined highlighting in relation to distributed study and students’ attitudes about highlighting as a study strategy. Participants read a text passage twice while highlighting or not, with their readings either distributed or massed, and followed by a week-delayed test...