Using qualia information to identify lexical semantic classes in an unsupervised clustering task

Acquiring lexical information is a complex problem, typically approached by relying on a number of contexts to contribute information for classification. One of the first issues to address in this domain is the determination of such contexts. The work presented here proposes the use of automatically obtained FORMAL role descriptors as features used to draw nouns from the same lexical semantic class together in an unsupervised clustering task. We have dealt with three lexical semantic classes (HUMAN, LOCATION and EVENT) in English. The results obtained show that it is possible to discriminate between elements from different lexical semantic classes using only FORMAL role information, hence validating our initial hypothesis. Also, iterating our method accurately accounts for fine-grained distinctions within lexical classes, namely distinctions involving ambiguous expressions. Moreover, a filtering and bootstrapping strategy employed in extracting FORMAL role descriptors proved to minimize effects of sparse data and noise in our task.

Automatic Lexical Semantic Classification of Nouns

The work we present here addresses cue-based noun classification in English and Spanish. Its main objective is to automatically acquire lexical semantic information by classifying nouns into previously known noun lexical classes. This is achieved by using particular aspects of linguistic contexts as cues that identify a specific lexical class. Here we concentrate on the task of identifying such cues and the theoretical background that allows for an assessment of the complexity of the task. The results show that, despite of the a-priori complexity of the task, cue-based classification is a useful tool in the automatic acquisition of lexical semantic classes.

Semantic web adoption: online tools for web evaluation and metadata extraction

This work briefly analyses the difficulties to adopt the Semantic Web, and in particular proposes systems to know the present level of migration to the different technologies that make up the Semantic Web. It focuses on the presentation and description of two tools, DigiDocSpider and DigiDocMetaEdit, designed with the aim of verifYing, evaluating, and promoting its implementation.

Frame detection over the semantic web

In the past, research in ontology learning from text has mainly focused on entity recognition, taxonomy induction and relation extraction. In this work we approach a challenging research issue: detecting semantic frames from texts and using them to encode web ontologies. We exploit a new generation Natural Language Processing technology for frame detection, and we enrich the frames acquired so far with argument restrictions provided by a super-sense tagger and domain specializations. The results are encoded according to a Linguistic MetaModel, which allows a complete translation of lexical resources and data acquired from text, enabling custom transformations of the enriched frames into modular ontology components.

Consumers’ Demand for Pork Quality: Applying Semantic Network Analysis, May 2006

Abstract Consideration of consumers’ demand for food quality entails several aspects. Quality itself is a complex and dynamic concept, and constantly evolving technical progress may cause changes in consumers’ judgment of quality. To improve our understanding of the factors influencing the demand for quality, food quality must be defined and measured from the consumer’s perspective (Cardello, 1995). The present analysis addresses the issue of food quality, focusing on pork—the food that respondents were concerned about. To gain insight into consumers’ demand, we analyzed their perception and evaluation and focused on their cognitive structures concerning pork quality. In order to more fully account for consumers’ concerns about the origin of pork, in 2004 we conducted a consumer survey of private households. The qualitative approach of concept mapping was used to uncover the cognitive structures. Network analysis was applied to interpret the results. In order to make recommendations to enterprises, we needed to know what kind of demand emerges from the given food quality schema. By establishing the importance and relative positions of the attributes, we find that the country of origin and butcher may be the two factors that have the biggest influence on consumers’ decisions about the purchase of pork.

Desarrollo CUDA en Java y Python

Análisis de desarrollo paralelo CUDA en lenguajes Java y Python, utilizando JCuda, RootBeer, PyCuda y Anaconda Accelerate. Cómo desarrollar, pros y contras de las herramientas analizadas.

Les damnés de Java. Tome 2 / par Méry...

Collection : Collection Hetzel

Les damnés de Java. Tome 1 / par Méry...

Collection : Collection Hetzel

Les damnés de Java. Tome 3 / par Méry...

Collection : Collection Hetzel

Perceptual and semantic contributions to repetition priming of environmental sounds.

Repetition of environmental sounds, like their visual counterparts, can facilitate behavior and modulate neural responses, exemplifying plasticity in how auditory objects are represented or accessed. It remains controversial whether such repetition priming/suppression involves solely plasticity based on acoustic features and/or also access to semantic features. To evaluate contributions of physical and semantic features in eliciting repetition-induced plasticity, the present functional magnetic resonance imaging (fMRI) study repeated either identical or different exemplars of the initially presented object; reasoning that identical exemplars share both physical and semantic features, whereas different exemplars share only semantic features. Participants performed a living/man-made categorization task while being scanned at 3T. Repeated stimuli of both types significantly facilitated reaction times versus initial presentations, demonstrating perceptual and semantic repetition priming. There was also repetition suppression of fMRI activity within overlapping temporal, premotor, and prefrontal regions of the auditory "what" pathway. Importantly, the magnitude of suppression effects was equivalent for both physically identical and semantically related exemplars. That the degree of repetition suppression was irrespective of whether or not both perceptual and semantic information was repeated is suggestive of a degree of acoustically independent semantic analysis in how object representations are maintained and retrieved.