Adaptive text mining: Inferring structure from sequences

Text mining is about inferring structure from sequences representing natural language text, and may be defined as the process of analyzing text to extract information that is useful for particular purposes. Although hand-crafted heuristics are a common practical approach for extracting information from text, a general, and generalizable, approach requires adaptive techniques. This paper studies the way in which the adaptive techniques used in text compression can be applied to text mining. It develops several examples: extraction of hierarchical phrase structures from text, identification of keyphrases in documents, locating proper names and quantities of interest in a piece of text, text categorization, word segmentation, acronym extraction, and structure recognition. We conclude that compression forms a sound unifying principle that allows many text mining problems to be tacked adaptively

Clui: A Platform for Handles to Rich Objects

On the desktop, users are accustomed to having visible handles to objects that they want to organize, share, or manipulate. Web applications today feature many classes of such objects, like flight itineraries, products for sale, people, recipes, and businesses, but there are no interoperable handles for high-level semantic objects that users can grab. This paper proposes Clui, a platform for exploring a new data type, called a Webit, that provides uniform handles to rich objects. Clui uses plugins to 1) create Webits on existing pages by extracting semantic data from those pages, and 2) augmenting existing sites with drag and drop targets that accept and interpret Webits. Users drag and drop Webits between sites to transfer data, auto-fill search forms, map associated locations, or share Webits with others. Clui enables experimentation with handles to semantic objects and the standards that underlie them

B2C electronic marketplace based in intelligent and mobile agents

Several architectures were proposed in the literature for the modeling of the interactions between agents.Within the framework of this article, we describe three architectures based on the multi agents design. In these systems, Buyer and Seller agents interact in an environment comparable to an electronic market in order to sell and buy goods.We propose then an electronic architecture of commerce based on intelligent and mobile agents called VEMMA.We present the formal model of this architecture as well as an implementation using the Java language and the RMI technology

Developing teachers’ digital identity: towards the pedagogic design principles of digital environments to enhance students’ learning in the 21st century

Digitalisation provides valuable opportunities for learning; however, it imposes demands on teachers. Teachers are expected not only to be profound users of educational technologies but also to engage in the design of digital environments such as online courses, learning management systems, and mobile applications. This article argues that originated in cultural-historical traditions, Galperin’s pedagogical theory might offer an approach to outline the pedagogic design principles of digital environments to empower teachers to develop their digital identity, enhance students’ learning and their development as learners. Two empirical snapshots are presented to exemplify the use of Galperin’s theory to design assignments and modules in digital learning environments. By engaging in learning and design of digital environments based on the suggested design principles, teachers and students may reposition themselves as active agents in knowledge practices to nurture teacher digital identity and enhance students’ capacity in learning to learn.publishedVersio

From the web of data to a world of action

This is the author’s version of a work that was accepted for publication in Web Semantics: Science, Services and Agents on the World Wide Web. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Web Semantics: Science, Services and Agents on the World Wide Web 8.4 (2010): 10.1016/j.websem.2010.04.007This paper takes as its premise that the web is a place of action, not just information, and that the purpose of global data is to serve human needs. The paper presents several component technologies, which together work towards a vision where many small micro-applications can be threaded together using automated assistance to enable a unified and rich interaction. These technologies include data detector technology to enable any text to become a start point of semantic interaction; annotations for web-based services so that they can link data to potential actions; spreading activation over personal ontologies, to allow modelling of context; algorithms for automatically inferring 'typing' of web-form input data based on previous user inputs; and early work on inferring task structures from action traces. Some of these have already been integrated within an experimental web-based (extended) bookmarking tool, Snip!t, and a prototype desktop application On Time, and the paper discusses how the components could be more fully, yet more openly, linked in terms of both architecture and interaction. As well as contributing to the goal of an action and activity-focused web, the work also exposes a number of broader issues, theoretical, practical, social and economic, for the Semantic Web.Parts of this work were supported by the Information Society Technologies (IST) Program of the European Commission as part of the DELOS Network of Excellence on Digital Libraries (Contract G038- 507618). Thanks also to Emanuele Tracanna, Marco Piva, and Raffaele Giuliano for their work on On Time