Discriminant Context Information Analysis for Post-Ranking Person Re-Identification

2017 ◽  
Vol 26 (4) ◽  
pp. 1650-1665 ◽  
Keyword(s):  
Context Information ◽  
Information Analysis

scholarly journals Interactive Evolution of Multidimensional Information in Social Media for Public Emergency: A Perspective from Optics Scattering

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Xiaoyue Ma ◽  
Xiao Meng ◽  
Hao Ma
Keyword(s):  
Social Media ◽  
Interface Design ◽  
Theoretical Explanation ◽  
Context Information ◽  
Information Analysis ◽  
Practical Support ◽  
Multidimensional Information ◽  
Public Emergency ◽  
Information Components ◽  
The Impact

Abstract Most of the current research on the information analysis of social media (SM) for public emergency focused on a single dimension such as emotion while neglecting the interaction between multidimensional information. Therefore, in this study, an information dispersing–superimposing model is proposed to explain the implicit regularity of the impact within a symbol, sentiment, and context information and their dependent evolution on the SM. Information hue, saturation, and flux (HSF) are defined to measure the interaction process. An online event was selected to verify the concept and hypothesis of this study. The results proved that the interaction among multidimensional information did exist on the SM for a public emergency. The turning points of information dispersing–superimposing often emerged when the number of online users involved had significant changes, and sentiment and context information were showed to have a strong interaction relationship and tended to be spread at the same time. It was also manifested that the dominant information component was varied at each stage of the emergency. This paper is one of the first to study the interaction of multidimensional information on the SM derived from optics scattering. The findings of the study will try to provide a theoretical explanation for why certain information components may be enhanced during the online dissemination and suggest practical support for the information predictions and interface design for SM.

scholarly journals Contextual Approach to Industrial Situation Recognition

TEM Journal ◽  
2020 ◽  
pp. 944-950
Author(s):  
V.N. Shepel` ◽  
N.V. Speshilova ◽  
V.A. Tripkosh ◽  
R.R. Rakhmatullin
Keyword(s):  
Recognition Algorithm ◽  
Management Systems ◽  
Context Information ◽  
Theory Method ◽  
Analysis Framework ◽  
Information Analysis ◽  
Recognition Error ◽  
Situation Recognition ◽  
Combination Theory ◽  
Recognition Systems

The article describes the development of multifaceted and efficient approaches to the context information analysis for synthesis of industrial situations context recognition algorithm in automated management systems within the enterprises. The probability theory method and method of statistical analysis, decision theory method, methods of algorithm and combination theory were used while researching. The research resulted in the development of new approaches to the context information analysis framework for pattern recognition which enables us to identify the procedure of contextual recognition for synthesis of working industrial situation recognition algorithm. A correspondence between the recognition error rate and the guaranteed recognition threshold, which can be used for setting up the automated context-based recognition systems, was analytically obtained during the research.

Automatic Stereotype Activation Is Context Dependent

2010 ◽  
Vol 41 (3) ◽  
pp. 131-136 ◽  
Author(s):  
Catharina Casper ◽  
Klaus Rothermund ◽  
Dirk Wentura
Keyword(s):  
Lexical Decision ◽  
Context Information ◽  
Decision Task ◽  
Social Categories ◽  
Priming Effects ◽  
Stereotype Activation ◽  
Social Stereotypes ◽  
Priming Paradigm ◽  
Automatic Activation ◽  
Mental Schemas

Processes involving an automatic activation of stereotypes in different contexts were investigated using a priming paradigm with the lexical decision task. The names of social categories were combined with background pictures of specific situations to yield a compound prime comprising category and context information. Significant category priming effects for stereotypic attributes (e.g., Bavarians – beer) emerged for fitting contexts (e.g., in combination with a picture of a marquee) but not for nonfitting contexts (e.g., in combination with a picture of a shop). Findings indicate that social stereotypes are organized as specific mental schemas that are triggered by a combination of category and context information.

Impact of Context Information on Metaphor Elaboration

2018 ◽  
Vol 65 (6) ◽  
pp. 370-384 ◽  
Author(s):  
Veronika Lerche ◽  
Ursula Christmann ◽  
Andreas Voss
Keyword(s):  
Diffusion Model ◽  
Processing Speed ◽  
A Priori ◽  
Model Fit ◽  
Verbal Task ◽  
Context Information ◽  
Speed Of Processing ◽  
Good Account ◽  
Dependent Variables ◽  
Decision Settings

Abstract. In experiments by Gibbs, Kushner, and Mills (1991) , sentences were supposedly either authored by poets or by a computer. Gibbs et al. (1991) concluded from their results that the assumed source of the text influences speed of processing, with a higher speed for metaphorical sentences in the Poet condition. However, the dependent variables used (e.g., mean RTs) do not allow clear conclusions regarding processing speed. It is also possible that participants had prior biases before the presentation of the stimuli. We conducted a conceptual replication and applied the diffusion model ( Ratcliff, 1978 ) to disentangle a possible effect on processing speed from a prior bias. Our results are in accordance with the interpretation by Gibbs et al. (1991) : The context information affected processing speed, not a priori decision settings. Additionally, analyses of model fit revealed that the diffusion model provided a good account of the data of this complex verbal task.

User modelling for intent prediction in information analysis

2003 ◽  
Author(s):  
Eugene Santos ◽  
Hien Nguyen ◽  
Qunhua Zhao ◽  
Hua Wang
Keyword(s):  
User Modelling ◽  
Information Analysis ◽  
Intent Prediction

Lifelog using Mobility Context Information in Urban City Area

2019 ◽  
Author(s):  
Yanlei Gu ◽  
Dailin Li ◽  
Yoshihiko Kamiya ◽  
Shunsuke Kamijo
Keyword(s):  
Context Information ◽  
City Area ◽  
Urban City
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