886 resultados para semantic retrieval


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Previous studies have shown both declining and stable semantic-memory abilities during healthy aging. There is consistent evidence that semantic processes involving controlled mechanisms weaken with age. In contrast, results of aging studies on automatic semantic retrieval are often inconsistent, probably due to methodological limitations and differences. The present study therefore examines age-related alterations in automatic semantic retrieval and memory structure with a novel combination of critical methodological factors, i.e., the selection of subjects, a well-designed paradigm, and electrophysiological methods that result in unambiguous signal markers. Healthy young and elderly participants performed lexical decisions on visually presented word/non-word pairs with a stimulus onset asynchrony (SOA) of 150 ms. Behavioral and electrophysiological data were measured, and the N400-LPC complex, an event-related potential component sensitive to lexical-semantic retrieval, was analyzed by power and topographic distribution of electrical brain activity. Both age groups exhibited semantic priming (SP) and concreteness effects in behavioral reaction time and the electrophysiological N400-LPC complex. Importantly, elderly subjects did not differ significantly from the young in their lexical decision and SP performances as well as in the N400-LPC SP effect. The only difference was an age-related delay measured in the N400-LPC microstate. This could be attributed to existing age effects in controlled functions, as further supported by the replicated age difference in word fluency. The present results add new behavioral and neurophysiological evidence to earlier findings, by showing that automatic semantic retrieval remains stable in global signal strength and topographic distribution during healthy aging.

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A number of neuroimaging findings have been interpreted as evidence that the left inferior frontal gyrus (IFG) subserves retrieval of semantic knowledge. We provide a fundamentally different interpretation, that it is not retrieval of semantic knowledge per se that is associated with left IFG activity but rather selection of information among competing alternatives from semantic memory. Selection demands were varied across three semantic tasks in a single group of subjects. Functional magnetic resonance imaging signal in overlapping regions of left IFG was dependent on selection demands in all three tasks. In addition, the degree of semantic processing was varied independently of selection demands in one of the tasks. The absence of left IFG activity for this comparison counters the argument that the effects of selection can be attributed solely to variations in degree of semantic retrieval. Our findings suggest that it is selection, not retrieval, of semantic knowledge that drives activity in the left IFG.

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Functional MRI was used to investigate the role of medial temporal lobe and inferior frontal lobe regions in autobiographical recall. Prior to scanning, participants generated cue words for 50 autobiographical memories and rated their phenomenological properties using our autobiographical memory questionnaire (AMQ). During scanning, the cue words were presented and participants pressed a button when they retrieved the associated memory. The autobiographical retrieval task was interleaved in an event-related design with a semantic retrieval task (category generation). Region-of-interest analyses showed greater activation of the amygdala, hippocampus, and right inferior frontal gyrus during autobiographical retrieval relative to semantic retrieval. In addition, the left inferior frontal gyrus showed a more prolonged duration of activation in the semantic retrieval condition. A targeted correlational analysis revealed pronounced functional connectivity among the amygdala, hippocampus, and right inferior frontal gyrus during autobiographical retrieval but not during semantic retrieval. These results support theories of autobiographical memory that hypothesize co-activation of frontotemporal areas during recollection of episodes from the personal past.

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This paper presents a domain ontology, the FeelingTheMusic Ontology - FTMOntology. FTMOntology is designed to represent the complex domain of music and how it relates to other domains like mood, personality and physiology. This includes representing the main concepts and relations of music domain with each of the above-mentioned domains. The concepts and relations between music, mood, personality and physiology. The main contribution of this work is to model and relate these different domains in a consistent ontology. © 2011 Springer-Verlag.

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Background: Semantic memory processes have been well described in literature. However, the available findings are mostly based on relatively young subjects and concrete word material (e.g. tree). Comparatively little information exists about semantic memory for abstract words (e.g. mind) and possible age related changes in semantic retrieval. In this respect, we developed a paradigm that is useful to investigate the implicit (i.e. attentionindependent) access to concrete and abstract semantic memory. These processes were then compared between young and elderly healthy subjects. Methods: A well established tool for investigating semantic memory processes is the semantic priming paradigm, which consists both of semantically unrelated and related word pairs. In our behavioral task these noun-noun word pairs were further divided into concrete, abstract and matched pronounceable non-word conditions. With this premise, the young and elderly participants performed a lexical decision task: they were asked to press a choice of two buttons as an indication for whether the word pair contained a non-word or not. In order to minimize controlled (i.e. attention-dependent) retrieval strategies, a short stimulus onset asynchrony (SOA) of 150ms was set. Reaction time (RT) changes and accuracy to related and unrelated words (priming effect) in the abstract vs. concrete condition (concreteness effect) were the dependent variables of interest. Results and Discussion: Statistical analysis confirmed both a significant priming effect (i.e. shorter RTs in semantically related compared to unrelated words) and a concreteness effect (i.e. RT decrease for concrete compared to abstract words) in the young and elderly subjects. There was no age difference in accuracy. The only age effect was a commonly known general slowing in RT over all conditions. In conclusion, age is not a critical factor in the implicit access to abstract and concrete semantic memory.

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With the progressing course of Alzheimer's disease (AD), deficits in declarative memory increasingly restrict the patients' daily activities. Besides the more apparent episodic (biographical) memory impairments, the semantic (factual) memory is also affected by this neurodegenerative disorder. The episodic pathology is well explored; instead the underlying neurophysiological mechanisms of the semantic deficits remain unclear. For a profound understanding of semantic memory processes in general and in AD patients, the present study compares AD patients with healthy controls and Semantic Dementia (SD) patients, a dementia subgroup that shows isolated semantic memory impairments. We investigate the semantic memory retrieval during the recording of an electroencephalogram, while subjects perform a semantic priming task. Precisely, the task demands lexical (word/nonword) decisions on sequentially presented word pairs, consisting of semantically related or unrelated prime-target combinations. Our analysis focuses on group-dependent differences in the amplitude and topography of the event related potentials (ERP) evoked by related vs. unrelated target words. AD patients are expected to differ from healthy controls in semantic retrieval functions. The semantic storage system itself, however, is thought to remain preserved in AD, while SD patients presumably suffer from the actual loss of semantic representations.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Introduction: In the Web environment, there is a need for greater care with regard to the processing of descriptive and thematic information. The concern with the recovery of information in computer systems precedes the development of the first personal computers. Models of information retrieval have been and are today widely used in databases specific to a field whose scope is known. Objectives: Verify how the issue of relevance is treated in the main computer models of information retrieval and, especially, as the issue is addressed in the future of the Web, the called Semantic Web. Methodology: Bibliographical research. Results: In the classical models studied here, it was realized that the main concern is retrieving documents whose description is closest to the search expression used by the user, which does not necessarily imply that this really needs. In semantic retrieval is the use of ontologies, feature that extends the user's search for a wider range of possible relevant options. Conclusions: The relevance is a subjective judgment and inherent to the user, it will depend on the interaction with the system and especially the fact that he expects to recover in your search. Systems that are based on a model of relevance are not popular, because it requires greater interaction and depend on the user's disposal. The Semantic Web is so far the initiative more efficient in the case of information retrieval in the digital environment.

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Information retrieval has been much discussed within Information Science lately. The search for quality information compatible with the users needs became the object of constant research.Using the Internet as a source of dissemination of knowledge has suggested new models of information storage, such as digital repositories, which have been used in academic research as the main form of autoarchiving and disseminating information, but with an information structure that suggests better descriptions of resources and hence better retrieval.Thus the objective is to improve the process of information retrieval, presenting a proposal for a structural model in the context of the semantic web, addressing the use of web 2.0 and web 3.0 in digital repositories, enabling semantic retrieval of information through building a data layer called Iterative Representation.The present study is characterized as descriptive and analytical, based on document analysis, divided into two parts: the first, characterized by direct observation of non-participatory tools that implement digital repositories, as well as digital repositories already instantiated, and the second with scanning feature, which suggests an innovative model for repositories, with the use of structures of knowledge representation and user participation in building a vocabulary domain. The model suggested and proposed ─ Iterative Representation ─ will allow to tailor the digital repositories using Folksonomy and also controlled vocabulary of the field in order to generate a data layer iterative, which allows feedback information, and semantic retrieval of information, through the structural model designed for repositories. The suggested model resulted in the formulation of the thesis that through Iterative Representation it is possible to establish a process of semantic retrieval of information in digital repositories.

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The present study used positron emission tomography (PET) to examine the cerebral activity pattern associated with auditory imagery forfamiliar tunes. Subjects either imagined the continuation of nonverbaltunes cued by their first few notes, listened to a short sequence of notesas a control task, or listened and then reimagined that short sequence. Subtraction of the activation in the control task from that in the real-tune imagery task revealed primarily right-sided activation in frontal and superior temporal regions, plus supplementary motor area(SMA). Isolating retrieval of the real tunes by subtracting activation in the reimagine task from that in the real-tune imagery task revealedactivation primarily in right frontal areas and right superior temporal gyrus. Subtraction of activation in the control condition from that in the reimagine condition, intended to capture imagery of unfamiliarsequences, revealed activation in SMA, plus some left frontal regions. We conclude that areas of right auditory association cortex, together with right and left frontal cortices, are implicated in imagery for familiartunes, in accord with previous behavioral, lesion and PET data. Retrieval from musical semantic memory is mediated by structures in the right frontal lobe, in contrast to results from previous studies implicating left frontal areas for all semantic retrieval. The SMA seems to be involved specifically in image generation, implicating a motor code in this process.

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The present study used positron emission tomography (PET) to examine the cerebral activity pattern associated with auditory imagery for familiar tunes. Subjects either imagined the continuation of nonverbal tunes cued by their first few notes, listened to a short sequence of notes as a control task, or listened and then reimagined that short sequence. Subtraction of the activation in the control task from that in the real-tune imagery task revealed primarily right-sided activation in frontal and superior temporal regions, plus supplementary motor area (SMA). Isolating retrieval of the real tunes by subtracting activation in the reimagine task from that in the real-tune imagery task revealed activation primarily in right frontal areas and right superior temporal gyrus. Subtraction of activation in the control condition from that in the reimagine condition, intended to capture imagery of unfamiliar sequences, revealed activation in SMA, plus some left frontal regions. We conclude that areas of right auditory association cortex, together with right and left frontal cortices, are implicated in imagery for familiar tunes, in accord with previous behavioral, lesion and PET data. Retrieval from musical semantic memory is mediated by structures in the right frontal lobe, in contrast to results from previous studies implicating left frontal areas for all semantic retrieval. The SMA seems to be involved specifically in image generation, implicating a motor code in this process.

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What are the neural bases of semantic memory? Traditional beliefs that the temporal lobes subserve the retrieval of semantic knowledge, arising from lesion studies, have been recently called into question by functional neuroimaging studies finding correlations between semantic retrieval and activity in left prefrontal cortex. Has neuroimaging taught us something new about the neural bases of cognition that older methods could not reveal or has it merely identified brain activity that is correlated with but not causally related to the process of semantic retrieval? We examined the ability of patients with focal frontal lesions to perform a task commonly used in neuroimaging experiments, the generation of semantically appropriate action words for concrete nouns, and found evidence of the necessity of the left inferior frontal gyrus for certain components of the verb generation task. Notably, these components did not include semantic retrieval per se.

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Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.

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Cultural objects are increasingly generated and stored in digital form, yet effective methods for their indexing and retrieval still remain an important area of research. The main problem arises from the disconnection between the content-based indexing approach used by computer scientists and the description-based approach used by information scientists. There is also a lack of representational schemes that allow the alignment of the semantics and context with keywords and low-level features that can be automatically extracted from the content of these cultural objects. This paper presents an integrated approach to address these problems, taking advantage of both computer science and information science approaches. We firstly discuss the requirements from a number of perspectives: users, content providers, content managers and technical systems. We then present an overview of our system architecture and describe various techniques which underlie the major components of the system. These include: automatic object category detection; user-driven tagging; metadata transform and augmentation, and an expression language for digital cultural objects. In addition, we discuss our experience on testing and evaluating some existing collections, analyse the difficulties encountered and propose ways to address these problems.

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For more than a decade research in the field of context aware computing has aimed to find ways to exploit situational information that can be detected by mobile computing and sensor technologies. The goal is to provide people with new and improved applications, enhanced functionality and better use experience (Dey, 2001). Early applications focused on representing or computing on physical parameters, such as showing your location and the location of people or things around you. Such applications might show where the next bus is, which of your friends is in the vicinity and so on. With the advent of social networking software and microblogging sites such as Facebook and Twitter, recommender systems and so on context-aware computing is moving towards mining the social web in order to provide better representations and understanding of context, including social context. In this paper we begin by recapping different theoretical framings of context. We then discuss the problem of context- aware computing from a design perspective.