Search results for "Natural Language Processing"
showing 10 items of 413 documents
Using Attribute Grammars for Description of Inductive Inference Search Space
1998
The problem of practically feasible inductive inference of functions or other objects that can be described by means of an attribute grammar is studied in this paper. In our approach based on attribute grammars various kinds of knowledge about the object to be found can be encoded, ranging from usual input/output examples to assumptions about unknown object's syntactic structure to some dynamic object's properties. We present theoretical results as well as describe the architecture of a practical inductive synthesis system based on theoretical findings.
The Application of Optimal Topic Sequence in Adaptive e-Learning Systems
2016
In an adaptive e-learning system an opportunity to choose a course topic sequence is given to ensure personalization. The topic sequence can be obtained from three sources: teacher-offered topic sequence that is based on teacher’s pedagogical experience; learner’s free choice that is based on indicated links between topics, and, finally, the optimal topic sequence acquisition method described in this article. The optimal topic sequence is based on previous learners’ experience. With the help of the optimal topic sequence method, data about previous learners’ course topic sequence and course results are obtained. After the data analysis the optimal topic sequence for the specific course is o…
The Expressibility of Languages and Relations by Word Equations
1997
Classically, several properties and relations of words, such as being a power of a same word, can be expressed by using word equations. This paper is devoted to study in general the expressive power of word equations. As main results we prove theorems which allow us to show that certain properties of words are not expressible as components of solutions of word equations. In particular, the primitiveness and the equal length are such properties, as well as being any word over a proper subalphabet.
New Areas of Application of Comparable Corpora
2019
This chapter describes several approaches of using comparable corpora beyond the area of MT for under-resourced languages, which is the primary focus of the ACCURAT project. Section 7.1, which is based on Rapp and Zock (Automatic dictionary expansion using non-parallel corpora. In: A. Fink, B. Lausen, W. Seidel, & A. Ultsch (Eds.) Advances in Data Analysis, Data Handling and Business Intelligence. Proceedings of the 32nd Annual Meeting of the GfKl, 2008. Springer, Heidelberg, 2010), addresses the task of creating resources for bilingual dictionaries using a seed lexicon; Sect. 7.2 (based on Rapp et al., Identifying word translations from comparable documents without a seed lexicon. Proceedi…
An Introduction to Ontology Based Structured Knowledge Base System: Knowledge Acquisition Module
2013
The following text presents the method of supplementing and verifying information stored in a framework system of the semantic knowledge base. The indicated method refers to the knowledge of ontological character, in other words to information about definitions of concepts and relationships among them. The aim of the method is the constant supplementing and verifying of the knowledge, and making more precise and detailed information about existing connections between concepts. The key aspect of the method is questions generating strictly dependent on the preconceived structure of stored knowledge.
An Innovative Similarity Measure for Sentence Plagiarism Detection
2016
We propose and experimentally assess Semantic Word Error Rate (SWER), an innovative similarity measure for sentence plagiarism detection. SWER introduces a complex approach based on latent semantic analysis, which is capable of outperforming the accuracy of competitor methods in plagiarism detection. We provide principles and functionalities of SWER, and we complement our analytical contribution by means of a significant preliminary experimental analysis. Derived results are promising, and confirm to use the goodness of our proposal.
Probing neural mechanisms of music perception, cognition, and performance using multivariate decoding.
2012
Recent neuroscience research has shown increasing use of multivariate decoding methods and machine learning. These methods, by uncovering the source and nature of informative variance in large data sets, invert the classical direction of inference that attempts to explain brain activity from mental state variables or stimulus features. However, these techniques are not yet commonly used among music researchers. In this position article, we introduce some key features of machine learning methods and review their use in the field of cognitive and behavioral neuroscience of music. We argue for the great potential of these methods in decoding multiple data types, specifically audio waveforms, e…
Conceptual Ontological Object Knowledge Base and Language
2008
This paper deals with AI in aspect of knowledge acquisition and ontology base structure. The core of the system was designed in an object model to optimize it for further processing. Direct concept linking was used to assure fast semantic network processing. Predefined attributes used in the core minimize the number of basic connections within the ontology and help in inference. The system is assumed to generate questions and to specify the knowledge. The AI system defined in this way opens a possibility for better understanding of such basic human mind mechanisms as learning or analyzing.
Validation of Semantic Analyses of Unstructured Medical Data for Research Purposes
2019
BACKGROUND: In secondary data there are often unstructured free texts. The aim of this study was to validate a text mining system to extract unstructured medical data for research purposes. METHODS: From a radiological department, 1,000 out of 7,102 CT findings were randomly selected. These were manually divided into defined groups by 2 physicians. For automated tagging and reporting, the text analysis software Averbis Extraction Platform (AEP) was used. Special features of the system are a morphological analysis for the decomposition of compound words as well as the recognition of noun phrases, abbreviations and negated statements. Based on the extracted standardized keywords, findings rep…