scholarly journals The relationship between acoustic structure and semantic information in Diana monkey alarm vocalization

2003 ◽  
Vol 114 (2) ◽  
pp. 1132-1142 ◽  
Author(s):  
Tobias Riede ◽  
Klaus Zuberbühler
Keyword(s):  
Semantic Information ◽  
Acoustic Structure ◽  
The Relationship ◽  
Diana Monkey

scholarly journals R-KG: A Novel Method for Implementing a Robot Intelligent Service

AI ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 117-140 ◽  
Author(s):  
Wu Hao ◽  
Jiao Menglin ◽  
Tian Guohui ◽  
Ma Qing ◽  
Liu Guoliang
Keyword(s):  
Semantic Information ◽  
Environmental Information ◽  
Knowledge Graph ◽  
Markov Logic ◽  
Main Work ◽  
Knowledge Reasoning ◽  
Novel Method ◽  
Markov Logic Network ◽  
The Relationship ◽  
Different Sources

Aiming to solve the problem of environmental information being difficult to characterize when an intelligent service is used, knowledge graphs are used to express environmental information when performing intelligent services. Here, we specially design a kind of knowledge graph for environment expression referred to as a robot knowledge graph (R-KG). The main work of a R-KG is to integrate the diverse semantic information in the environment and pay attention to the relationship at the instance level. Also, through the efficient knowledge organization of a R-KG, robots can fully understand the environment. The R-KG firstly integrates knowledge from different sources to form a unified and standardized representation of a knowledge graph. Then, the deep logical relationship hidden in the knowledge graph is explored. To this end, a knowledge reasoning model based on a Markov logic network is proposed to realize the self-developmental ability of the knowledge graph and to further enrich it. Finally, as the strength of environment expression directly affects the efficiency of robots performing services, in order to verify the efficiency of the R-KG, it is used here as the semantic map that can be directly used by a robot for performing intelligent services. The final results prove that the R-KG can effectively express environmental information.

AN APPROACH OF EXCITING EVENTS DETECTION IN SOCCER SPORTS VIDEOS

2010 ◽  
Vol 07 (01) ◽  
pp. 15-30
Author(s):  
WEI WANG ◽  
WEI GAO ◽  
YAJUAN LIU ◽  
RUNSHENG WANG
Keyword(s):  
Semantic Information ◽  
Temporal Structure ◽  
Classification Models ◽  
Hierarchical Tree ◽  
Low Level ◽  
Video Frames ◽  
Temporal Structures ◽  
Events Detection ◽  
The Relationship ◽  
Sports Videos

In this paper, an approach with both the hierarchical tree and the clips temporal structure is proposed for exciting events (such as free kicks near the goal box, corner kicks, etc.) detection in broadcast soccer videos. In this approach, video frames are firstly divided into sections. Then these sections are divided further into clips which have specifically semantic information so that we can use the low-level descriptors to classify the clips and analyze the relationship between them. Low-level descriptors include color, motion descriptors and edge descriptors. To detect the exciting events, the simple classification models are constructed by combining the fixed temporal structures of clips with motion vectors and other low-level descriptors. Experiments on real soccer video programs show the encouraging results.

scholarly journals TOWARDS THE QUANTIFICATION OF THE SEMANTIC INFORMATION ENCODED IN WRITTEN LANGUAGE

2010 ◽  
Vol 13 (02) ◽  
pp. 135-153 ◽  
Author(s):  
MARCELO A. MONTEMURRO ◽  
DAMIÁN H. ZANETTE
Keyword(s):  
Semantic Information ◽  
Semantic Content ◽  
Characteristic Size ◽  
Written Language ◽  
Local Order ◽  
Large Database ◽  
Word Usage ◽  
Complex Information ◽  
Communication Signal ◽  
The Relationship

Written language is a complex communication signal capable of conveying information encoded in the form of ordered sequences of words. Beyond the local order ruled by grammar, semantic and thematic structures affect long-range patterns in word usage. Here, we show that a direct application of information theory quantifies the relationship between the statistical distribution of words and the semantic content of the text. We show that there is a characteristic scale, roughly around a few thousand words, which establishes the typical size of the most informative segments in written language. Moreover, we find that the words whose contributions to the overall information is larger, are the ones more closely associated with the main subjects and topics of the text. This scenario can be explained by a model of word usage that assumes that words are distributed along the text in domains of a characteristic size where their frequency is higher than elsewhere. Our conclusions are based on the analysis of a large database of written language, diverse in subjects and styles, and thus are likely to be applicable to general language sequences encoding complex information.

HCMSL: Hybrid Cross-modal Similarity Learning for Cross-modal Retrieval

2021 ◽  
Vol 17 (1s) ◽  
pp. 1-22
Author(s):  
Chengyuan Zhang ◽  
Jiayu Song ◽  
Xiaofeng Zhu ◽  
Lei Zhu ◽  
Shichao Zhang
Keyword(s):  
Semantic Information ◽  
State Of The Art ◽  
Similarity Learning ◽  
Retrieval Method ◽  
Feature Representations ◽  
High Level ◽  
Fully Connected ◽  
The Relationship ◽  
Hybrid Cross ◽  
Fully Connected Networks

The purpose of cross-modal retrieval is to find the relationship between different modal samples and to retrieve other modal samples with similar semantics by using a certain modal sample. As the data of different modalities presents heterogeneous low-level feature and semantic-related high-level features, the main problem of cross-modal retrieval is how to measure the similarity between different modalities. In this article, we present a novel cross-modal retrieval method, named Hybrid Cross-Modal Similarity Learning model (HCMSL for short). It aims to capture sufficient semantic information from both labeled and unlabeled cross-modal pairs and intra-modal pairs with same classification label. Specifically, a coupled deep fully connected networks are used to map cross-modal feature representations into a common subspace. Weight-sharing strategy is utilized between two branches of networks to diminish cross-modal heterogeneity. Furthermore, two Siamese CNN models are employed to learn intra-modal similarity from samples of same modality. Comprehensive experiments on real datasets clearly demonstrate that our proposed technique achieves substantial improvements over the state-of-the-art cross-modal retrieval techniques.

scholarly journals Mind, Matter, Meaning and Information

2012 ◽  
Vol 11 (1) ◽  
pp. 36-45
Author(s):  
Robin Faichney
Keyword(s):  
Philosophy Of Mind ◽  
Semantic Information ◽  
Mental Content ◽  
Intentional Stance ◽  
Broad Term ◽  
Physical Information ◽  
The Relationship ◽  
Material Form

This article aims to show how mind, matter and meaning might be united in one theory using certain concepts of information, building on ideas of empathy and intentionality. The concept of intentionality in philosophy of mind (“aboutness”), which is “the ineliminable mark of the mental” according to Brentano, can be viewed as the relationship between model and object, and empathy can be viewed as a form of mental modelling, so that the inclination to attribute mentality can be identified with the inclination to empathise with the relevant entity. Physical information, a concept quite well established within the discipline of physics, is basically a reconceptualization of material form. Daniel Dennett's concept of the intentional stance allows the development of a concept of “intentional information,” a broad term that encompasses mental content and semantic information generally, as encoded within physical information/material form.

scholarly journals An individual differences approach to semantic cognition: Divergent effects of age on representation, retrieval and selection

2017 ◽  
Author(s):  
Paul Hoffman
Keyword(s):  
Older People ◽  
Executive Control ◽  
Semantic Information ◽  
Later Life ◽  
Semantic Knowledge ◽  
Semantic Representations ◽  
Semantic Cognition ◽  
Control Processes ◽  
The Relationship ◽  
Representation Of Knowledge

AbstractSemantic cognition refers to the appropriate use of acquired knowledge about the world. This requires representation of knowledge as well as control processes which ensure that currently-relevant aspects of knowledge are retrieved and selected. Although these abilities can be impaired selectively following brain damage, the relationship between them in healthy individuals is unclear. It is also commonly assumed that semantic cognition is preserved in later life, because older people have greater reserves of knowledge. However, this claim overlooks the possibility of decline in semantic control processes. Here, semantic cognition was assessed in 100 young and older adults. Despite having a broader knowledge base, older people showed specific impairments in semantic control, performing more poorly than young people when selecting among competing semantic representations. Conversely, they showed preserved controlled retrieval of less salient information from the semantic store. Breadth of semantic knowledge was positively correlated with controlled retrieval but was unrelated to semantic selection ability, which was instead correlated with non-semantic executive function. These findings indicate that three distinct elements contribute to semantic cognition: semantic representations that accumulate throughout the lifespan, processes for controlled retrieval of less salient semantic information, which appear age-invariant, and mechanisms for selecting task-relevant aspects of semantic knowledge, which decline with age and may relate more closely to domain-general executive control.

scholarly journals When scenes speak louder than words: Verbal encoding does not mediate the relationship between scene meaning and visual attention

2019 ◽  
Author(s):  
Gwendolyn L Rehrig ◽  
Taylor Hayes ◽  
John M. Henderson ◽  
Fernanda Ferreira
Keyword(s):  
Visual Attention ◽  
Articulatory Suppression ◽  
Semantic Information ◽  
Recall Task ◽  
Visual World ◽  
Attentional Guidance ◽  
Saliency Maps ◽  
Scene Viewing ◽  
Guidance Theory ◽  
The Relationship

The complexity of the visual world requires that we constrain visual attention and prioritize some regions of the scene for attention over others. The current study investigated whether verbal encoding processes influence how attention is allocated in scenes. Specifically, we asked whether the advantage of scene meaning over image salience in attentional guidance is modulated by verbal encoding, given that we often use language to process information. Sixty subjects studied 30 scenes for 12 seconds each in preparation for a scene recall task. Thirty of the subjects engaged in a secondary articulatory suppression task (digit repetition) concurrent with scene viewing. Meaning and saliency maps were quantified for each of the 30 scenes. In both conditions we found that meaning explained more of the variance in visual attention than image salience did, particularly when we controlled for the overlap between meaning and salience. Based on these results, verbal encoding processes do not appear to modulate the relationship between scene meaning and visual attention, or to play a role in encoding scenes for later recall. Our findings suggest that semantic information in the scene steers the attentional ship, consistent with cognitive guidance theory.

scholarly journals Information packaging correlates of semantic information structure categories

2020 ◽  
Vol 22 (1) ◽  
pp. 5-27
Author(s):  
Doina Jitcă
Keyword(s):  
Information Structure ◽  
Semantic Information ◽  
Contour Analysis ◽  
Model Based ◽  
Information Packaging ◽  
Intonational Meaning ◽  
F0 Contour ◽  
Accent Identification ◽  
The Relationship ◽  
Model Based Analysis

This paper presents an Information Structure (IS) model at the information packaging (IPk) level and its usage in utterance partitioning and in explaining semantic IS category realizations at the pragmatic level. The IPk model proposes a hierarchical view of F0 contours that transforms utterances into binary contrast unit (CU) hierarchies. CUs have binary IPk partitions with two independent and overlapping structures and a nuclear element which project its IPk functions to the whole units it belongs to. Two nuclear accent identification rules are formulated in this paper in order to be used in decoding IPk partition hierarchy by F0 contour analysis. In the second part of the paper several intonational contours of English sentences, having different semantic IS events, are interpreted by correlating semantic IS analysis results with those of the IPk model-based analysis. By decoding IPk structure and functional constituents from F0 contours we can advance our knowledge about the relationship between prosody and intonational meaning.

scholarly journals A Framework for Service Semantic Description Based on Knowledge Graph

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1017
Author(s):  
Qitong Sun ◽  
Jun Han ◽  
Dianfu Ma
Keyword(s):  
Service Discovery ◽  
Large Scale ◽  
Semantic Information ◽  
Knowledge Graph ◽  
Data Sets ◽  
Accuracy Rate ◽  
Data Set ◽  
File Storage ◽  
Representation Method ◽  
The Relationship

To construct a large-scale service knowledge graph is necessary. We propose a method, namely semantic information extension, for service knowledge graphs. We insist on the information of services described by Web Services Description Language (WSDL) and we design the ontology layer of web service knowledge graph and construct the service graph, and using the WSDL document data set, the generated service knowledge graph contains 3738 service entities. In particular, our method can give a full performance to its effect in service discovery. To evaluate our approach, we conducted two sets of experiments to explore the relationship between services and classify services that develop by service descriptions. We constructed two experimental data sets, then designed and trained two different deep neural networks for the two tasks to extract the semantics of the natural language used in the service discovery task. In the prediction task of exploring the relationship between services, the prediction accuracy rate reached 95.1%, and in the service classification experiment, the accuracy rate of TOP5 reached 60.8%. Our experience shows that the service knowledge graph has additional advantages over traditional file storage when managing additional semantic information is effective and the new service representation method is helpful for service discovery and composition tasks.

scholarly journals The relationship between the typical errors in the translation of business idioms and their lexicographical treatment

2007 ◽  
pp. 65 ◽  
Author(s):  
Esther Fraile Vicente
Keyword(s):  
Semantic Information ◽  
Semantic Content ◽  
Language Level ◽  
The Relationship

This essay is based on the complexity involved in the translation of English business idioms into Spanish, due to the fact that these linguistic constructions are created with metaphors and based on associations of meaning that have not yet been studied sufficiently. By performing a translation experiment with my students, some conclusions are drawn regarding the difficulties inexperienced translators face and how dictionaries should cope with them. It is suggested that, most general and specialized dictionaries do not offer exact translation equivalents for idioms, but present versions that either belong to a different language level, show a lost of semantic content, have a different frequency, are archaic or erroneous. To solve these limitations, the lexicographical resources should not only include idioms as lemmas, but also offer more syntactic-semantic information with them and to structure it more systematically.

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