Non-Standard Words as Features for Text Categorization

This paper presents categorization of Croatian texts using Non-Standard Words (NSW) as features. Non-Standard Words are: numbers, dates, acronyms, abbreviations, currency, etc. NSWs in Croatian language are determined according to Croatian NSW taxonomy. For the purpose of this research, 390 text documents were collected and formed the SKIPEZ collection with 6 classes: official, literary, informative, popular, educational and scientific. Text categorization experiment was conducted on three different representations of the SKIPEZ collection: in the first representation, the frequencies of NSWs are used as features; in the second representation, the statistic measures of NSWs (variance, coefficient of variation, standard deviation, etc.) are used as features; while the third representation combines the first two feature sets. Naive Bayes, CN2, C4.5, kNN, Classification Trees and Random Forest algorithms were used in text categorization experiments. The best categorization results are achieved using the first feature set (NSW frequencies) with the categorization accuracy of 87%. This suggests that the NSWs should be considered as features in highly inflectional languages, such as Croatian. NSW based features reduce the dimensionality of the feature space without standard lemmatization procedures, and therefore the bag-of-NSWs should be considered for further Croatian texts categorization experiments.Comment: IEEE 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2014), pp. 1415-1419, 201

The Debate Over the Efficacy of Federal Hate Crime Legislation: A Look at Arlen Specter’s Senatorial Efforts and its Legacy

Bias-motivated violence is considered especially heinous in the United States of America. This research examines the Federal legislation that cements that value into law. Hate crimes are criminal acts where the target was specifically chosen because of their race, sexual orientation, gender expression, ethnicity, or religion. These crimes, whether intentionally or not, have a ripple effect on societal values, and especially spread fear within oppressed minority groups. This research begins by examining the context that precipitated a need for hate crime laws to begin with and then looks at federal developments as a reaction to landmark hate crime cases. One of Senator Arlen Specter’s key areas of policy impact lies right here in hate crimes. Through means of the Arlen Specter Senatorial Papers his contributions in both Washington, D.C. and Pennsylvania are explored. Finally, the debate over hate crime legislation as it exists today is had. This research is expected to analyze bias motivated crime through a contextualizing historical lens of Arlen Specter’s work and then use that analysis to work through the current debate over legislation

The development of metaphorical language comprehension in typical development and in Williams syndrome

The domain of figurative language comprehension was used to probe the developmental relation between language and cognition in typically developing individuals and individuals with Williams syndrome. Extending the work of Vosniadou and Ortony, the emergence of nonliteral similarity and category knowledge was investigated in 117 typically developing children between 4 and 12 years of age, 19 typically developing adults, 15 children with Williams syndrome between 5 and 12 years of age, and 8 adults with Williams syndrome. Participants were required to complete similarity and categorization statements by selecting one of two words (e.g., either “The sun is like ___” or “The sun is the same kind of thing as ___”) with word pairs formed from items that were literally, perceptually, or functionally similar to the target word or else anomalous (e.g., moon, orange, oven, or chair, respectively). Results indicated that individuals with Williams syndrome may access different, less abstract knowledge in figurative language comparisons despite the relatively strong verbal abilities found in this disorder

Conceptual Spaces in Object-Oriented Framework

The aim of this paper is to show that the middle level of mental representations in a conceptual spaces framework is consistent with the OOP paradigm. We argue that conceptual spaces framework together with vague prototype theory of categorization appears to be the most suitable solution for modeling the cognitive apparatus of humans, and that the OOP paradigm can be easily and intuitively reconciled with this framework. First, we show that the prototypebased OOP approach is consistent with Gärdenfors’ model in terms of structural coherence. Second, we argue that the product of cloning process in a prototype-based model is in line with the structure of categories in Gärdenfors’ proposal. Finally, in order to make the fuzzy object-oriented model consistent with conceptual space, we demonstrate how to define membership function in a more cognitive manner, i.e. in terms of similarity to prototype

Symbol Emergence in Robotics: A Survey

Humans can learn the use of language through physical interaction with their environment and semiotic communication with other people. It is very important to obtain a computational understanding of how humans can form a symbol system and obtain semiotic skills through their autonomous mental development. Recently, many studies have been conducted on the construction of robotic systems and machine-learning methods that can learn the use of language through embodied multimodal interaction with their environment and other systems. Understanding human social interactions and developing a robot that can smoothly communicate with human users in the long term, requires an understanding of the dynamics of symbol systems and is crucially important. The embodied cognition and social interaction of participants gradually change a symbol system in a constructive manner. In this paper, we introduce a field of research called symbol emergence in robotics (SER). SER is a constructive approach towards an emergent symbol system. The emergent symbol system is socially self-organized through both semiotic communications and physical interactions with autonomous cognitive developmental agents, i.e., humans and developmental robots. Specifically, we describe some state-of-art research topics concerning SER, e.g., multimodal categorization, word discovery, and a double articulation analysis, that enable a robot to obtain words and their embodied meanings from raw sensory--motor information, including visual information, haptic information, auditory information, and acoustic speech signals, in a totally unsupervised manner. Finally, we suggest future directions of research in SER.Comment: submitted to Advanced Robotic

Opening up terrorism talk: The sequential and categorical production of discursive power within the call openings of a talk radio broadcast

The current research undertakes a combined CA/MCA approach to analyse the unfolding moral business of ‘talk radio’ discourse, and situates this analysis within a critical discourse studies framework. In a case study analysis of a talk radio broadcast on the topic of terrorism, the sequencing and membership categorization work that is accomplished during the call openings of its contributors is examined. Local manifestations of discursive power allied to the ‘host’ role are identified, along with the data-driven distinction of ‘lay’ and ‘elite’ callers. The empowering versus disempowering consequences of sequential turn allocation and identity categorization are explored, leading to some reflections on security versus human rights advocacy within terrorism talk. The contribution of this research to two research enterprises is then outlined. Firstly, we highlight the benefit that a combined CA/MCA approach, which foregrounds powerplay, offers to analysis of talk-in-interaction. Following which, we underline how placing such a micro-level spotlight on the seemingly mundane details of talk in context can offer valuable insights for critical terrorism studies