Search results for " latent semantic analysis"
showing 4 items of 14 documents
An architecture with a mobile phone interface for the interaction of a human with a humanoid robot expressing emotions and personality
2011
In this paper is illustrated the cognitive architecture of a humanoid robot based on the proposed paradigm of Latent Semantic Analysis (LSA). This paradigm is a step towards the simulation of an emotional behavior of a robot interacting with humans. The LSA approach allows the creation and the use of a data driven high-dimensional conceptual space. We developed an architecture based on three main areas: Sub-conceptual, Emotional and Behavioral. The first area analyzes perceptual data coming from the sensors. The second area builds the sub-symbolic representation of emotions in a conceptual space of emotional states. The last area triggers a latent semantic behavior which is related to the h…
Automatic concept maps generation in support of educational processes
2014
A VLE is a system where three main actors can be devised: the teacher in the role of instructional designer, the tutor, and the stu- dent. Instructional designers need easy interaction for specifying the course domain structure to the system, and for controlling how well the learning materials agree to such a structure. Tutors need tools for having a holistic perception of the evolution of single students and/or groups in the VLE during the learning process. Finally, students need self regulation in terms of controlling their learning rate, reflect on their learning strategies, and comparing with other people in the class. In this work we claim that sharing an implicit representation of the…
Automatic Dictionary Creation by Sub-symbolic Encoding of Words
2006
This paper describes a technique for automatic creation of dictionaries using sub-symbolic representation of words in cross-language context. Semantic relationship among words of two languages is extracted from aligned bilingual text corpora. This feature is obtained applying the Latent Semantic Analysis technique to the matrices representing terms co-occurrences in aligned text fragments. The technique allows to find the “best translation” according to a properly defined geometric distance in an automatically created semantic space. Experiments show an interesting correctness of 95% obtained in the best case.
Image classification based on 2D feature motifs
2013
The classification of raw data often involves the problem of selecting the appropriate set of features to represent the input data. In general, various features can be extracted from the input dataset, but only some of them are actually relevant for the classification process. Since relevant features are often unknown in real-world problems, many candidate features are usually introduced. This degrades both the speed and the predictive accuracy of the classifier due to the presence of redundancy in the candidate feature set. In this paper, we study the capability of a special class of motifs previously introduced in the literature, i.e. 2D irredundant motifs, when they are exploited as feat…