Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammar

A usage-based Construction Grammar (CxG) posits that slot-constraints generalize from common exemplar constructions. But what is the best model of constraint generalization? This paper evaluates competing frequency-based and association-based models across eight languages using a metric derived from the Minimum Description Length paradigm. The experiments show that association-based models produce better generalizations across all languages by a significant margin

Adaptive Neuro-Fuzzy Inference System for Dynamic Load Balancing in 3GPP LTE

ANFIS is applicable in modeling of key parameters when investigating the performance and functionality of wireless networks. The need to save both capital and operational expenditure in the management of wireless networks cannot be over-emphasized. Automation of network operations is a veritable means of achieving the necessary reduction in CAPEX and OPEX. To this end, next generations networks such WiMAX and 3GPP LTE and LTE-Advanced provide support for self-optimization, self-configuration and self-healing to minimize human-to-system interaction and hence reap the attendant benefits of automation. One of the most important optimization tasks is load balancing as it affects network operation right from planning through the lifespan of the network. Several methods for load balancing have been proposed. While some of them have a very buoyant theoretical basis, they are not practically implementable at the current state of technology. Furthermore, most of the techniques proposed employ iterative algorithm, which in itself is not computationally efficient. This paper proposes the use of soft computing, precisely adaptive neuro-fuzzy inference system for dynamic QoS-aware load balancing in 3GPP LTE. Three key performance indicators (i.e. number of satisfied user, virtual load and fairness distribution index) are used to adjust hysteresis task of load balancing

Structure emerges faster during cultural transmission in children than in adults

How does children’s limited processing capacity affect cultural transmission of complex information? We show that over the course of iterated reproduction of two-dimensional random dot patterns transmission accuracy increased to a similar extent in 5- to 8-year-old children and adults whereas algorithmic complexity decreased faster in children. Thus, children require more structure to render complex inputs learnable. In line with the Less-Is-More hypothesis, we interpret this as evidence that children’s processing limitations affecting working memory capacity and executive control constrain the ability to represent and generate complexity, which, in turn, facilitates emergence of structure. This underscores the importance of investigating the role of children in the transmission of complex cultural traits

The Missing Link between Morphemic Assemblies and Behavioral Responses:a Bayesian Information-Theoretical model of lexical processing

We present the Bayesian Information-Theoretical (BIT) model of lexical processing: A mathematical model illustrating a novel approach to the modelling of language processes. The model shows how a neurophysiological theory of lexical processing relying on Hebbian association and neural assemblies can directly account for a variety of effects previously observed in behavioural experiments. We develop two information-theoretical measures of the distribution of usages of a morpheme or word, and use them to predict responses in three visual lexical decision datasets investigating inflectional morphology and polysemy. Our model offers a neurophysiological basis for the effects of morpho-semantic neighbourhoods. These results demonstrate how distributed patterns of activation naturally result in the arisal of symbolic structures. We conclude by arguing that the modelling framework exemplified here, is a powerful tool for integrating behavioural and neurophysiological results

Психолінгвальні маркери автобіографічної й травматичної пам’яті

This study examines psycholinguistic structure of autobiographical and traumatic narratives representing positive emotional and stressful traumatic life events. The research applied the cross sectional, between subjects design utilizing the independent variables of external agent they, space and time and dependent variable of word number in traumatic narratives for multiple regression analysis. The approval letter to recruit the participants through SONA system in 2015– 2016 academic year was obtained from Institutional Review Board of Oklahoma State University (USA). 64 undergraduates of nonclinical setting, females (n=37), males (n=27), mean age was 19.43 (SD=1.37) were recruited. PTSD-8: A Short PTSD Inventory assesses PTSD, the Linguistic Inquiry and Word Count (LIWC) analyzes traumatic and autobiographical narratives in terms of linguistic units and psychological meaningful categories. The results indicate that there are significant differences between pronoun they as external agent of proposition and psychological categories of negative emotions and anxiety in traumatic and autobiographical narratives. The frequency of these categories is higher in traumatic narratives compared with autobiographical narratives. External agent they, category of time and space taken together significantly contribute to word number in traumatic narrative. There is a negative correlation between focus on the past and word count, and positive correlation between social category and word count in traumatic narrative in nonclinical sample. To sum up, propositional structure of traumatic memory of individuals without PTSD is represented by external agent and context (place and time) taken together. Considering time as a significant negative predictor of creating traumatic narrative, temporal processing without overestimation of time is an important factor of avoiding PTSD. The principal theoretical implication of this study is that traumatic memory might be examined through psycholinguistic markers represented by propositional structures and psychological meaningful categories of traumatic narratives in individuals from nonclinical and clinical settings.Мета дослідження полягала в теоретичному й емпіричному вивченні пропозиційної структури автобіографічної й травматичної пам’яті як сховища позитивних та травматичних життєвих подій. Дослідження використовує вивчення наративів незалежних вибірок із використанням регресійного аналізу, де категорії екстернального агента вони, часу і місця є залежними змінними, а кількість слів травматичного наративу – незалежною змінною. Дослідження здійснювалося за згодою Комісії з етики проведення психологічних досліджень Державного університету Оклахоми впродовж 2015–2016 навчального року. У дослідженні взяло учать 64 студенти, дівчат (n=37), хлопців (n=27), середній вік 19,43 (SD=1,37). Для емпіричного дослідження використовувався експрес-опитувальник ПТСР (PTSD-8: A Short PTSD Inventory), а також комп’ютерна програма Linguistic Inquiry and Word Count (LIWC) для визначення лінгвальних і психологічних категорій у тексті. У результаті, встановлено значущі відмінності у показниках категорій екстернального агента вони та психологічних категорій негативних емоцій та тривожності у травматичному та автобіографічному наративах. Травматичні наративи мають вищу частотність цих категорій, так само як і більшу кількість слів наративу загалом. Результати регресійного аналізу показують, що категорії екстернального агента, часу і місця є значущими предикторами кількості слів травматичного наративу, тому ми можемо вважати ці категорії як одиниці пропозиційної структури, і відповідно, психолінгвальні маркери травматичної пам’яті. Також встановлено негативний кореляційний зв’язок між кількістю слів у травматичному наративі і фокусом на минулому часові, та позитивний кореляційий зв’язок між соціальною категорією та кількістю слів у травматичному наративі. Отже, отримані результати можуть використовуватися для клінічних і неклінічних досліджень травматичної пам’яті на основі пропозиційних структур, представлених у травматичних наративах. Коректне темпоральне сприймання, уникання переоцінки минулого та переважання екстернальних над інтернальними агентами становлять пропозиційну структуру травматичної пам’яті індивіда, травматичний досвід якого не розвинувся у ПТСР

Syntax-Aware Multi-Sense Word Embeddings for Deep Compositional Models of Meaning

Deep compositional models of meaning acting on distributional representations of words in order to produce vectors of larger text constituents are evolving to a popular area of NLP research. We detail a compositional distributional framework based on a rich form of word embeddings that aims at facilitating the interactions between words in the context of a sentence. Embeddings and composition layers are jointly learned against a generic objective that enhances the vectors with syntactic information from the surrounding context. Furthermore, each word is associated with a number of senses, the most plausible of which is selected dynamically during the composition process. We evaluate the produced vectors qualitatively and quantitatively with positive results. At the sentence level, the effectiveness of the framework is demonstrated on the MSRPar task, for which we report results within the state-of-the-art range.Comment: Accepted for presentation at EMNLP 201