Synonymy and Translation

This paper is meant to give some insight into the interaction between on the one hand theoretical concepts in the field of formal semantics, and on the other hand linguistic research directed towards an application, more specifically, the research in the machine translation project Rosetta. The central notion is ‘synonymy’. It will be used to discuss sameness of meaning for expressions belonging to different languages

Formalizing Cyber--Physical System Model Transformation via Abstract Interpretation

Model transformation tools assist system designers by reducing the labor--intensive task of creating and updating models of various aspects of systems, ensuring that modeling assumptions remain consistent across every model of a system, and identifying constraints on system design imposed by these modeling assumptions. We have proposed a model transformation approach based on abstract interpretation, a static program analysis technique. Abstract interpretation allows us to define transformations that are provably correct and specific. This work develops the foundations of this approach to model transformation. We define model transformation in terms of abstract interpretation and prove the soundness of our approach. Furthermore, we develop formalisms useful for encoding model properties. This work provides a methodology for relating models of different aspects of a system and for applying modeling techniques from one system domain, such as smart power grids, to other domains, such as water distribution networks.Comment: 8 pages, 4 figures; to appear in HASE 2019 proceeding

“You say potato, I say potato” Mapping Digital Preservation and Research Data Management Concepts towards Collective Curation and Preservation Strategies

This paper explores models, concepts and terminology used in the Research Data Management and Digital Preservation communities. In doing so we identify several overlaps and mutual concerns where the advancements of one professional field can apply to and assist another. By focusing on what unites rather than divides us, and by adopting a more holistic approach we advance towards collective curation and preservation strategies. &nbsp

“You say potato, I say potato” Mapping Digital Preservation and Research Data Management Concepts towards Collective Curation and Preservation Strategies

This paper explores models, concepts and terminology used in the Research Data Management and Digital Preservation communities. In doing so we identify several overlaps and mutual concerns where the advancements of one professional field can apply to and assist another. By focusing on what unites rather than divides us, and by adopting a more holistic approach we advance towards collective curation and preservation strategies. &nbsp

A review and comparison of ontology-based approaches to robot autonomy

Within the next decades, robots will need to be able to execute a large variety of tasks autonomously in a large variety of environments. To relax the resulting programming effort, a knowledge-enabled approach to robot programming can be adopted to organize information in re-usable knowledge pieces. However, for the ease of reuse, there needs to be an agreement on the meaning of terms. A common approach is to represent these terms using ontology languages that conceptualize the respective domain. In this work, we will review projects that use ontologies to support robot autonomy. We will systematically search for projects that fulfill a set of inclusion criteria and compare them with each other with respect to the scope of their ontology, what types of cognitive capabilities are supported by the use of ontologies, and which is their application domain.Peer ReviewedPostprint (author's final draft

WHAT IS INFORMATION SUCH THAT THERE CAN BE INFORMATION SYSTEMS?

Information systems, as a discipline, is concerned with the generation, storage and transmission of information, generally by technological means. As such, it would seem to be fundamental that it has a clear and agreed conceptualization of its core subject matter – namely “information”. Yet, we would claim, this is clearly not the case. As McKinney and Yoos point out, in a recent survey of the term information within information systems: “This is the IS predicament – using information as a ubiquitous label whose meaning is almost never specified. Virtually all the extant IS literature fails to explicitly specify meaning for the very label that identifies it.” We live in an information age and the vast majority of information (whatever it may be) is made available through a wide range of computer systems and one would expect therefore that information systems would in fact be one of the leading disciplines of the times rather than one that appears to hide itself in the shadows. Governments nowadays routinely utilize many academic experts to advise them in a whole range of areas but how many IS professors ever get asked? So, the primary purpose of this paper is to stimulate a debate within IS to discuss, and try to establish, a secure foundation for the discipline in terms of its fundamental concept – information. The structure of the paper is that we will firstly review the theories of information used (generally implicitly) within IS. Then we will widen the picture to consider the range of theories available more broadly within other disciplines. We will then suggest a particular approach that we consider most fruitful and discuss some of the major contentious issues. We will illustrate the theories with examples from IS

Computer-Assisted Language Learning and the Revolution in Computational Linguistics

For a long period, Computational Linguistics (CL) and Computer-Assisted Language Learning (CALL) have developed almost entirely independently of each other. A brief historical survey shows that the main reason for this state of affairs was the long preoccupation in CL with the general problem of Natural Language Understanding (NLU). As a consequence, much effort was directed to fields such as Machine Translation (MT), which were perceived as incorporating and testing NLU. CALL does not fit this model very well so that it was hardly considered worth pursuing in CL. In the 1990s the realization that products could not live up to expectations, even in the domain of MT, led to a crisis. After this crisis the dominant approach to CL has become much more problem-oriented. From this perspective, many of the earlier differences disadvantaging CALL with respect to MT have now disappeared. Therefore the revolution in CL offers promising perspectives for CALL

Exploring Sparse Spatial Relation in Graph Inference for Text-Based VQA

Text-based visual question answering (TextVQA) faces the significant challenge of avoiding redundant relational inference. To be specific, a large number of detected objects and optical character recognition (OCR) tokens result in rich visual relationships. Existing works take all visual relationships into account for answer prediction. However, there are three observations: (1) a single subject in the images can be easily detected as multiple objects with distinct bounding boxes (considered repetitive objects). The associations between these repetitive objects are superfluous for answer reasoning; (2) two spatially distant OCR tokens detected in the image frequently have weak semantic dependencies for answer reasoning; and (3) the co-existence of nearby objects and tokens may be indicative of important visual cues for predicting answers. Rather than utilizing all of them for answer prediction, we make an effort to identify the most important connections or eliminate redundant ones. We propose a sparse spatial graph network (SSGN) that introduces a spatially aware relation pruning technique to this task. As spatial factors for relation measurement, we employ spatial distance, geometric dimension, overlap area, and DIoU for spatially aware pruning. We consider three visual relationships for graph learning: object-object, OCR-OCR tokens, and object-OCR token relationships. SSGN is a progressive graph learning architecture that verifies the pivotal relations in the correlated object-token sparse graph, and then in the respective object-based sparse graph and token-based sparse graph. Experiment results on TextVQA and ST-VQA datasets demonstrate that SSGN achieves promising performances. And some visualization results further demonstrate the interpretability of our method.Comment: Accepted by TIP 202