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Intelligent personalized systems often ignore the affective aspectof human behavior and focus more on tactile cues of the useractivity. A complete user modeling, though, should also incorporatecues such as facial expressions, speech prosody and gesture orbody posture expressivity features, in order to dynamically profile the user, fusing all available modalities since these qualitative affective cues...
Recently, a novel "completely automated public Turing test to tell computers and humans apart (CAPTCHA)'' system has been proposed, in which users are asked to separate natural faces of humans and artificial faces of virtual world avatars. The system is based on the assumption that computers cannot separate them while it is an easy task for humans. Conventional digital forensics approaches to...
The contribution describes the application of the Team 'Computational Intelligence Group' from the University of Applied Sciences Mittweida (Germany) to the ICMLA Face Recognition Challenge 2012. In particular we explain the data preprocessing and feature extraction, which was applied before classification learning. Further we give details about the used classification algorithm - the enhanced generalized...
This concept paper suggests a new way of thinking about the origin, growth, and spread of a general-purpose "scientific habit of mind" in humans, and discusses how intelligent coaching agents may help. The argument begins with a description of the role of the cognitive cycle in animal thinking. We then examine critical differences between non-human and human cognition, especially in respect...
Although research in the areas of human mobility and social networks is extensive, our knowledge of the relationship between the mobility and the social network of an individual is very limited, mainly due to the complexity of accessing adequate data to be able to capture both mobility and social interactions. In this paper we present and characterize some of the spatio-temporal features of social...
OCCAMS is a new algorithm for the Multi-Document Summarization (MDS) problem. We use Latent Semantic Analysis (LSA) to produce term weights which identify the main theme(s) of a set of documents. These are used by our heuristic for extractive sentence selection which borrows techniques from combinatorial optimization to select a set of sentences such that the combined weight of the terms covered is...
Variation in the Human Leukocyte Antigen (HLA) gene system is very important. It is one of the most polymorphic regions of the human genome and one of the most extensively studied regions due to its association with autoimmune, infectious, and inflammatory diseases, such as rheumatoid arthritis, celiac disease, multiple sclerosis and Type I diabetes. The HLA gene system also plays a crucial role in...
In this paper we introduce an algorithmic approach, capable of creating a semantic network with concatenated terms and phrases (hash tags) from collectively postings on the Twitter sphere. This network could be exploited for query expansion provision in respect to users¢ information needs, without considering any other prior knowledge or access in search logs or browsing history records. For evaluation...
In this paper we propose a novel system design approach to improve the performance of large-scale interacting user communities towards a collective goal. The proposed approach has been applied on the example case of social network information diffusion and results show that it helped the participating community achieve less spam and improved information coverage.
Context-aware information retrieval received a significant attention last years. This paper addresses some of the challenges in context acquisition. It is focused on a method for inference of unavailable contextual information using machine learning. The method for context inference is based on observed behaviour of individual user and virtual communities of similar users. We work with contextual...
The ramp-up process is a significant bottleneck during the development of manufacturing systems. The effort and time required to ramp-up a system is largely dependent on the effectiveness of the human decision making process to select the most promising action and improve the system. Although existing work has identified significant factors influencing ramp-up performance, little has been done to...
Semantic similarity measures aim at computing a value that represents to what extent two semantic resources are similar. This paper proposes an extension of a semantic similarity measure for large linked data sources such as DBPedia. In order to evaluate and compare similarity measures, an experiment is described to collect human evaluations of the similarity between pairs of movies. A correlation...
Space-filling visualization techniques have proved their capability in visualizing large hierarchical structured data. However, most existing techniques restrict their partitioning process in vertical and horizontal direction only, which cause problem with identifying hierarchical structures. According to Gestalt research, limiting tree map visualisation to rectangles blocks the utilisation of human...
Convolutional neural network models have covered a broad scope of computer vision applications, achieving competitive performance with minimal domain knowledge. In this work, we apply such a model to a task designed to deter automated systems. We trained a convolutional neural network to distinguish between images of human faces from computer generated avatars as part of the ICMLA 2012 Face Recognition...
Captchas are frequently used on the modern world wide web to differentiate human users from automated bots by giving tests that are easy for humans to answer but difficult or impossible for algorithms. As artificial intelligence algorithms have improved, new types of Captchas have had to be developed. Recent work has proposed a new system called Avatar Captcha, in which a user is asked to distinguish...
A significant proportion of Web traffic is now attributed to Web robots, and this proportion is likely to grow over time. These robots may threaten the security, privacy, functionality, and performance of a Web server due to their unregulated crawling behavior. Therefore, to assess their impact, it must be possible to accurately detect Web robot requests. Contemporary detection approaches, however,...
An important task of aging research is to find genes that regulate lifespan. Wet-lab identification of aging genes is tedious and labor-intensive activity. Developing an algorithm to predict aging genes will be greatly helpful. In this paper, we systematically analyzed topological features of proteins encoded by Drosophila melanogaster aging genes versus those encoded by non-aging genes in protein-protein...
Web entities are the building blocks of human knowledge and users are making decisions among vast varieties of entities. For example, recommendation systems generate lists of entities to users, but seldom show the reasons of recommendation such as the uniqueness of each item to assist user decision making. In this paper, we mathematically define Web entity uniqueness and uniqueness patterns, based...
Tandem repeats in DNA sequences are extremely relevant in biological phenomena and diagnostic tools. Computational programs that discover these tandem repeats generate a huge volume of data, which is often difficult to decipher without further organization. In this paper, we describe a new method for post-processing tandem repeats through clustering. Our work presents multiple ways of expressing tandem...
We are now developing a Japanese speaking test called SCAT, which is part of J-CAT (Japanese Computerized Adaptive Test), a free online proficiency test for Japanese language learners. In this paper, we focus on the sentence-reading-aloud task and the sentence generation task in SCAT, and propose an automatic scoring method for estimating the overall score of answer speech, which is holistically determined...
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