scholarly journals Citation cascade and the evolution of topic relevance

2020 ◽  
Vol 72 (1) ◽  
pp. 110-127 ◽  
Author(s):  
Chao Min ◽  
Qingyu Chen ◽  
Erjia Yan ◽  
Yi Bu ◽  
Jianjun Sun
Keyword(s):  
Topic Relevance

scholarly journals Topic Relevance of Public Health Emergencies Influence on Internet Public Opinion Resonance: Simulation Based on Langevin’s Equation

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Quan Cheng ◽  
Yan-gang Zhang ◽  
Yi-quan Li
Keyword(s):  
Public Health ◽  
Public Opinion ◽  
Stochastic Resonance ◽  
Resonance Phenomenon ◽  
The Internet ◽  
Resonance Model ◽  
Mutual Correlation ◽  
The Public ◽  
Public Health Emergencies ◽  
Topic Relevance

Public health emergencies occurred frequently, which usually result in the negative Internet public opinion events. In the complex network information ecological environment, multiple public opinion events may be aggregated to generate public opinion resonance due to the topic category, the mutual correlation of the subject involved, and the compound accumulation of specific emotions. In order to reveal the phenomenon and regulations of the public opinion resonance, we firstly analyze the influence factors of the Internet public opinion events in the public health emergencies. Then, based on Langevin’s equation, we propose the Internet public opinion stochastic resonance model considering the topic relevance. Furthermore, three exact public health emergencies in China are provided to reveal the regulations of evoked events “revival” caused by original events. We observe that the Langevin stochastic resonance model considering topic relevance can effectively reveal the resonance phenomenon of Internet public opinion caused by public health emergencies. For the original model without considering the topic relevance, the new model is more sensitive. Meanwhile, it is found that the degree of topic relevance between public health emergencies has a significant positive correlation with the intensity of Internet public opinion resonance.

Topic relevance as the basic structuration of the field of consciousness

2021 ◽  
pp. 37-51
Author(s):  
Carlos Belvedere
Keyword(s):  
Passive Synthesis ◽  
Topic Relevance ◽  
Different Levels ◽  
Selective Activity

My aim is to depict Schutz's theory of topic relevance as his own distinctive phenomenology of consciousness. I will show that his conception of consciousness is elaborated from at least three types of elements. First, I will disclose Husserl's influence on Schutz in this matter. I will list a few Husserlian terms that Schutz takes into consideration such as noema, horizon, parts and wholes, attentional ray and passive synthesis. Second, I will show that Schutz turns to Gurwitsch's idea that consciousness is a field of experience where the previously listed elements are held together and find their relational meaning. Third, I will expose how all these elements taken from Husserl and Gurwitsch are reinterpreted by Schutz as being relative to relevance as a basic phenomenon of our mind's selective activity which puts at work different levels of our personality according to the schizophrenic ego hypothesis.

Heterogeneous-Graph-Based Video Search Reranking Using Topic Relevance

2020 ◽  
Vol E103.A (12) ◽  
pp. 1529-1540
Author(s):  
Soh YOSHIDA ◽  
Mitsuji MUNEYASU ◽  
Takahiro OGAWA ◽  
Miki HASEYAMA
Keyword(s):  
Video Search ◽  
Topic Relevance

Topic relevance and retrieval effectiveness

1983 ◽  
Vol 10 (1) ◽  
pp. 9-14
Author(s):  
Florence E. DeHart
Keyword(s):  
Retrieval Effectiveness ◽  
Topic Relevance

Topic relevance and BSO switching effectiveness

1982 ◽  
Vol 9 (2) ◽  
pp. 71-76
Author(s):  
Florence E. DeHart
Keyword(s):  
Topic Relevance

A Method to Review Expert Recommendation Using Topic Relevance and Expert Relationship

2018 ◽  
Vol 27 (01) ◽  
pp. 1741004 ◽  
Author(s):  
Shengxiang Gao ◽  
Zhengtao Yu ◽  
Linbin Shi ◽  
Xin Yan ◽  
Haixia Song
Keyword(s):  
New Method ◽  
Markov Network ◽  
Expert Recommendation ◽  
Maximum Cliques ◽  
Topic Relevance ◽  
The Relationship ◽  
Relevant Degree

In the process of recommending review experts to projects, in order to effectively make use of the relevance among topics and the relationship among experts, a new method is proposed for review expert recommendation using topic relevance and expert relationship. In this method, firstly, the relevance among topics and the relationships among experts are used to respectively construct the Markov network of topics and the Markov network of experts. Next, the maximum topic clique is extracted from the topic Markov network and the maximum expert clique is extracted from the expert Markov network; then, with the information of the two maximum cliques, the relevance between experts and projects is calculated. After that, according to the descending order of the relevant degree, the candidates are ranked. Finally, the experts, who are the top N to projects, are recommended. The experiments on five domain datasets are made and the results show that the proposed method can improve the effect of review expert recommendation, and the F-value increases by an average of 5% than without considering the relevance among topics and the relationship among experts.

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