In this paper, we propose a novel strategy at an abstract level by combining textual and visual clustering results to retrieve images using semantic keywords and auto-annotate images based on similarity with existing keywords. Our main hypothesis is that images that fall in to the same textcluster can be described with common visual features of those images. In this approach, images are first c...

This contribution focuses on documentation of model-to-model transformation, respectively on converting model represented by BORM notation (Business Object Relation Modelling) to a HTML-based textual report. The transformation is from the management-level business process model into the operation-level business process model. The operation-level model should be textual and tailored for each ind...

Recognition of textual entailment is not an easy task. In fact, early experimental evidences in [1] seems to demonstrate that even human judges often fail in reaching an agreement on the existence of entailment relation between two expressions. We aim to contribute to the theoretical and practical setting of textual entailment, through both a linguistic inspection of the textual entailment phen...

This paper describes our work in NTCIR-11 on RITE-3 Binary-class (BC) subtask and Multi-class (MC) subtask in Simplified Chinese. We proposed a textual entailment system using a hybrid approach that integrates many features. The performance of the proposed method in the formal run achieved Macro-F1’s of 59.71% in BC subtask and only 23.19% in MC subtask

This paper presents a system for automatically generating discourse structures from written text. The system is divided into two levels: sentence-level and text-level. The sentence-level discourse parser uses syntactic information and cue phrases to segment sentences into elementary discourse units and to generate discourse structures of sentences. At the text-level, constraints about textual a...

Traditional database Systems provide efficient transaction oriented processing of structured data. However, usually, processing of textual data in a database system has either no or only limited support. For example, while it may be possible to build index structures over textual data, in practice, the resulting bottlenecks make this impracticable. The reason for these bottlenecks are pseudo co...

This paper presents an approach to computer-assisted teaching of reading abilities using corpus data. The approach is supported by a set of tools for automatically selecting and classifying texts retrieved from the Internet. The approach is based on a linguistic model of textual cohesion which describes relations between larger textual units that go beyond the sentence level. We show that textu...

The use of textual domain-specific modeling languages is an important trend in model-driven software engineering. Just like any other primary development artifact, textual models are subject to continuous change and evolve heavily over time. Consequently, MDE tool chain developers and integrators are faced with the task to select and provide appropriate tools supporting the versioning of textua...

The identification of different nominal phrases in a discourse as used to refer to the same (discourse) entity is essential for achieving robust natural language understanding (NLU). The importance of this task is directly amplified by the field of Natural Language Processing (NLP) currently moving towards high-level linguistic tasks requiring NLU capabilities such as e.g. recognizing textual e...