Cristina Vertan

A Structured Way to Use Channels for Communication in X-Machine Systems

Abstract. This paper presents a new model for passing messages in communicating stream X-machine systems (CSXMS). The components are stream X-machines with ε-transitions, acting simultaneously. The states are partitioned into processing and communicating states. Passing messages between the X-machines involves only communicating states. A communication matrix is used as a common memory. It is shown that a structured way of using channels, namely via select constructs with guarded alternatives and terminate clause, may be implemented. An automatic scheme for writing concurrent programs in an Ada-like style, starting from a CSXMS, is proposed.

Improving the search for learning objects with keywords and ontologies

We report on an ongoing project which aims at improving the effectiveness of retrieval and accessibility of learning object within learning management systems and learning object repositories. The project Language Technology for eLearning approaches this task by providing Language Technology based functionalities and by integrating semantic knowledge through domain-specific ontologies. We will report about the development of a keyword extractor and a domain-specific ontology, the integration of these modules into the learning management system ILIAS and the validation of these tools which assesses their added value in the scenario of searching learning objects across different languages.

Summarizing Short Texts Through a Discourse-Centered Approach in a Multilingual Context

The chapter presents the architecture of a system targeting summaries of short texts in six languages. At the core of a summary, which comprises clauses and sentences extracted from the original text, is the structure of the discourse and its relationship with its coreferential links. The approach shows a uniform design for all languages, while language specificity is attributed to the resources that fuel the component modules. The design described here includes a number of feedback loops used to fine-tune the parameters by comparing the output of the modules against annotated corpora. “Average” summaries over some human-produced ones are used to evaluate the accuracy of each of the monolingual systems. The study also presents some quantitative data on the corpora used, showing a comparison among languages and results that, mostly, prove to be above the state of the art.

Crosslingual Retrieval in an eLearning Environment

In this paper we are reporting about an ongoing project LT4eL (Language Technolohy for eLearning) aiming at improving the effectiveness of retrieval and accessibility of learning objects within a learning management system. We elaborate the process of building the domain ontology and present the multilingual support offered to the application.

Language resources for the Semantic Web: perspectives for machine translation

In this paper we present a possible solution for improving the quality of on-line translation systems, using mechanisms and standards from Semantic Web. We focus on Example based machine translation and the automatization of the translation examples extraction by means of RDF-repositories.

Making historical texts accessible to everybody

In this paper we discuss the degree of readability of historical texts for a broad public. We argue that text simplification methods can improve significantly this aspect and bring an added value to historical texts. We present a specific example, a genuine multilingual historical texts, which should be available at least to r e s a r h e r r m d i f r n t f i e l s a n d p r p o s a mechanism for simplifying the text.

On the annotation of vague expressions: a case study on Romanian historical texts

Current approaches in Digital .Humanities tend to ignore a central as-pect of any hermeneutic introspection: the intrinsic vagueness of analyzed texts. Especially when dealing with his-torical documents neglecting vague-ness has important implications on the interpretation of the results. In this pa-per we present current limitation of an-notation approaches and describe a current methodology for annotating vagueness for historical Romanian texts.

Text Genre – An Unexplored Parameter in Statistical Machine Translation

It is generally accepted that the performance of a statistical machine translation (SMT) system depends significantly on the concordance between the domain of training and test data. During the last years several methods have been proposed in order to deal with out- of-domain words. Less to no attention has been paid however to text genre within the same domain. In this paper we demonstrate that the style of the training corpus may influence the quality of the translation output even when the domain of the training and test data remains al- most unchanged, but the text genre changes. We use as training data the JRC-Acquis and as test data the Europarl corpus. We include also experiments with an out-of-domain test data, as comparison for the variation of performance of the SMT system.

ProLiV - a Tool for Teaching by Viewing Computational Linguistics

ProLiV - Animated Process-modeler of Complex (Computational) Linguistic Methods and Theories - is a fully modular, flexible, XML-based stand-alone Java application, used for computer-assisted learning in Natural Language Processing (NLP) or Computational Linguistics (CL). Having a flexible and extendible architecture, the system presents the students, by means of text, of visual elements (such as pictures and animations) and of interactive parameter set-up, the following topics: Latent Semantics Analysis (LSA), (computational) lexicons, question modeling, Hidden-Markov-Models (HMM), and Topic-Focus. These topics are addressed to first-year students in computer science and/or linguistics.