Finding an adequate paraphrase representation formalism is a challenging issue in Natural Language Processing. In this paper, we analyse the performance of Tree Edit Distance as a paraphrase representation baseline. Our experiments using Edit Distance Textual Entailment Suite show that, as Tree Edit Distance consists of a purely syntactic approach, paraphrase alternations not based on structura...

In general, diagrams and text are both considered to have their advantages and disadvantages for the representation of use case models, but this is rarely investigated experimentally. This paper describes a controlled experiment where we compare safety hazard identification by means of misuse cases based on use case diagrams and textual use cases. The experiment participants found use case diag...

In this paper, we present a metamodel for textual use case descriptions, structurally conforming to the UML, to specify the behavior of use cases in a flow-oriented manner. While being primarily targeted at supporting requirements engineers in creating consistent use case models, the metamodel defines a textual representation of use case behavior that is easily understandable for readers, who a...

Textual CBR systems solve problems by reusing experiences that are in textual form. Knowledge-rich comparison of textual cases remains an important challenge for these systems. However mapping text data into a structured case representation requires a significant knowledge engineering effort. In this paper we look at automated acquisition of the case indexing vocabulary as a two step process in...

Determining semantic textual similarity is a core research subject in natural language processing. Since vector-based models for sentence representation often use shallow information, capturing accurate semantics is difficult. By contrast, logical semantic representations capture deeper levels of sentence semantics, but their symbolic nature does not offer graded notions of textual similarity. ...

This paper presents a direct semantic analysis method for learning the correlation matrix between visual and textual words from socially tagged images. In the literature, to improve the traditional visual bag-of-words (BOW) representation, latent semantic analysis has been studied extensively for learning a compact visual representation, where each visual word may be related to multiple latent ...

A Scheme representation of Standard MIDI Files is proposed. The Scheme expressions are defined and constrained by an XML-language, which in the starting point is inspired by a MIDI XML event language made by the MIDI Manufactures Association. The representation of Standard MIDI Files in Scheme makes it possible to carry out systematic modifications and transformations of MIDI contents with use ...

The digital mediation resources used in Distance Education can hinder the teacher’s perception about the student’s state of mind. However, the textual expression in natural language is widely encouraged in most Distance Education courses, through the use of Virtual Learning Environments and other digital tools. This fact has motivated research efforts in order to identify feelings expressed by ...

In previous publications we have reported on the development of Bayesian Network models for the preoperative discrimination between malignant and benign ovarian mass. The models incorporated both medical background knowledge and patient data, which required the traceability of the incorporated prior medical knowledge. For this purpose, we followed a particular annotation method for Bayesian Net...

Tremendous growth in the number of textual documents has produced daily requirements for effective development to explore, analyze, and discover knowledge from these textual documents. Conventional text mining and managing systems mainly use the presence or absence of key words to discover and analyze useful information from textual documents. However, simple word counts and frequency distribut...