Acquisition of French adjectives in Quebec French as revealed by elicitation data

This study presents data from an elicitation study on French size and color adjectives in noun phrases (DPs), both early acquired structures. Thirty-two francophone children aged 3–5 years participated in the study. Adjectives were elicited using specially designed puzzles and spontaneous speech corpora. We observed that errors in French variable adjectives are produced in the early acquisition stages, especially in the context of feminine colour DPs. We propose that the source of difficulty for feminine variable adjectives is the retrieval of a lexicalized form that competes with the masculine adjective denoting the same concept

Bayesian unsupervised learning with multiple data types

Copyright © 2009 Walter de Gruyter. The final publication is available at www.degruyter.comWe propose Bayesian generative models for unsupervised learning with two types of data and an assumed dependency of one type of data on the other. We consider two algorithmic ap- proaches, based on a correspondence model where latent variables are shared across datasets. These models indicate the appropriate number of clusters in addition to indicating relevant features in both types of data. We evaluate the model on arti¯cially created data. We then apply the method to a breast cancer dataset consisting of gene expression and microRNA array data derived from the same patients. We assume dependence of gene expression on microRNA expression in this study. The method ranks genes within subtypes which have statistically signi¯cant abnormal expression and ranks associated abnormally expressing mi- croRNA. We report a genetic signature for the basal-like subtype of breast cancer found across a number of previous gene expression array studies. Using the two algorithmic ap- proaches we ¯nd that this signature also arises from clustering on the microRNA expression data and appears derivative from this data

Is Bigger Better? Corpus and Dictionary Use in the Search for Compounds, Collocations, Derived Forms and Fixed Expressions

In the course of the development of a bilingual dictionary, a number of monolingual source language and target language dictionaries, bilingual dictionaries, and text corpora are typically used as tools to create entries. When dealing with words that occur at a high frequency in the corpus, determining which collocations, compounds, derived forms and fixed expressions are to be included in the dictionary is an additional complication. This paper presents the relative merits of using dictionary and corpus sources for searching for this type of information. We present frequency searching as an efficient and useful tool for corpus analysis, especially in the case of high-frequency words.La création d’entrées dans le cadre de l’élaboration d’un dictionnaire bilingue mobilise habituellement des dictionnaires unilingues dans les langues source et cible, des dictionnaires bilingues ainsi que des corpus textuels. En outre, la fréquence élevée de certains mots dans le corpus impose une sélection des collocations, des mots composés, des formes dérivées et des expressions figées à inclure dans le dictionnaire. Le présent article offre un aperçu des avantages découlant de la combinaison de l’usage des sources dictionnairiques et des corpus de données. Nous proposons que la recherche par fréquence est un paramètre particulièrement utile pour résoudre les difficultés posées par l’étude de mots présents dans le corpus à une fréquence élevée

Repeat Victimisation, Retraumatisation and Victim Vulnerability

Abstract: This study explores the contribution that traumatic experiences and psychological post-traumatic stress symptoms make to predicting subsequent revictimisation in a sample of violent crime victims. In addition, the timing of first trauma exposure was also explored. Fifty-four adult victims (27 male and 27 female) of police recorded violent crime were interviewed and their traumatic exposure history, trauma symptomology, age at first trauma exposure as well as psychological and psychosocial functioning were assessed. These victims were followed longitudinally and subsequent revictimisation between six and twelve months post index victimisation measured. A greater number of types of trauma exposure was related lower emotional stability, higher trauma symptomology and revictimisation. Those victims with childhood traumatic exposure reported more trauma symptomology exposure than those without prior exposure. The implications for law enforcement and victim services are discussed

Bayesian Unsupervised Learning with Multiple Data Types

We propose Bayesian generative models for unsupervised learning with two types of data and an assumed dependency of one type of data on the other. We consider two algorithmic approaches, based on a correspondence model where latent variables are shared across datasets. These models indicate the appropriate number of clusters in addition to indicating relevant features in both types of data. We evaluate the model on artificially created data. We then apply the method to a breast cancer dataset consisting of gene expression and microRNA array data derived from the same patients. We assume dependence of gene expression on microRNA expression in this study. The method ranks genes within subtypes which have statistically significant abnormal expression and ranks associated abnormally expressing microRNA. We report a genetic signature for the basal-like subtype of breast cancer found across a number of previous gene expression array studies. Using the two algorithmic approaches we find that this signature also arises from clustering on the microRNA expression data and appears derivative from this data.