Assisting blog publication: annotation, model transformation, and crossblogging techniques

Although blogs exist from the beginning of the Internet, their use has considerablybeen increased in the last decade. Nowadays, they are ready for being used bya broad range of people. From teenagers to multinationals, everyone can have aglobal communication space.Companies know blogs are a valuable publicity tool to share information withthe participants, and the importance of creating consumer communities aroundthem: participants come together to exchange ideas, review and recommend newproducts, and even support each other. Also, companies can use blogs for differentpurposes, such as a content management system to manage the content of websites,a bulletin board to support communication and document sharing in teams,an instrument in marketing to communicate with Internet users, or a KnowledgeManagement Tool. However, an increasing number of blog content do not findtheir source in the personal experiences of the writer. Thus, the information cancurrently be kept in the user¿s desktop documents, in the companies¿ catalogues,or in another blogs. Although the gap between blog and data source can be manuallytraversed in a manual coding, this is a cumbersome task that defeats the blog¿seasiness principle. Moreover, depending on the quantity of information and itscharacterisation (i.e., structured content, unstructured content, etc.), an automaticapproach can be more effective.Based on these observations, the aim of this dissertation is to assist blog publicationthrough annotation, model transformation and crossblogging techniques.These techniques have been implemented to give rise to Blogouse, Catablog, andBlogUnion. These tools strive to improve the publication process considering theaforementioned data sources.

Semi-automatic generation of learning domain modules for technology supported learning systems

In a time when Technology Supported Learning Systems are being widely used, there is a lack of tools that allows their development in an automatic or semi-automatic way. Technology Supported Learning Systems require an appropriate Domain Module, ie. the pedagogical representation of the domain to be mastered, in order to be effective. However, content authoring is a time and effort consuming task, therefore, efforts in automatising the Domain Module acquisition are necessary.Traditionally, textbooks have been used as the main mechanism to maintain and transmit the knowledge of a certain subject or domain. Textbooks have been authored by domain experts who have organised the contents in a means that facilitate understanding and learning, considering pedagogical issues.Given that textbooks are appropriate sources of information, they can be used to facilitate the development of the Domain Module allowing the identification of the topics to be mastered and the pedagogical relationships among them, as well as the extraction of Learning Objects, ie. meaningful fragments of the textbook with educational purpose.Consequently, in this work DOM-Sortze, a framework for the semi-automatic construction of Domain Modules from electronic textbooks, has been developed. DOM-Sortze uses NLP techniques, heuristic reasoning and ontologies to fulfill its work. DOM-Sortze has been designed and developed with the aim of automatising the development of the Domain Module, regardless of the subject, promoting the knowledge reuse and facilitating the collaboration of the users during the process.

Digging into signs: Developing standard annotation practices for cross-linguistic, quantitative analysis of sign language data. Final Report.

For sign languages used by deaf communities, linguistic corpora have until recently been unavailable, due to the lack of a writing system and a written culture in these communities, and the very recent advent of digital video. Recent improvements in video and computer technology have now made larger sign language datasets possible; however, large sign language datasets that are fully machine-readable are still elusive. This is due to two challenges. 1. Inconsistencies that arise when signs are annotated by means of spoken/written language. 2. The fact that many parts of signed interaction are not necessarily fully composed of lexical signs (equivalent of words), instead consisting of constructions that are less conventionalised. As sign language corpus building progresses, the potential for some standards in annotation is beginning to emerge. But before this project, there were no attempts to standardise these practices across corpora, which is required to be able to compare data crosslinguistically. This project thus had the following aims: 1. To develop annotation standards for glosses (lexical/word level) 2. To test their reliability and validity 3. To improve current software tools that facilitate a reliable workflow Overall the project aimed not only to set a standard for the whole field of sign language studies throughout the world but also to make significant advances toward two of the world’s largest machine-readable datasets for sign languages – specifically the BSL Corpus (British Sign Language, http://bslcorpusproject.org) and the Corpus NGT (Sign Language of the Netherlands, http://www.ru.nl/corpusngt).

From words to images and then to one image: the poster in Spielberg' s translations of literary works

Eterio Pajares, Raquel Merino y José Miguel Santamaría (eds.)