scholarly journals ENRICHMENT AND POPULATION OF A GEOSPATIAL ONTOLOGY FOR SEMANTIC INFORMATION EXTRACTION

Author(s):  
M. Kokla ◽  
V. Papadias ◽  
E. Tomai

<p><strong>Abstract.</strong> The massive amount of user-generated content available today presents a new challenge for the geospatial domain and a great opportunity to delve into linguistic, semantic, and cognitive aspects of geographic information. Ontology-based information extraction is a new, prominent field in which a domain ontology guides the extraction process and the identification of pre-defined concepts, properties, and instances from natural language texts. The paper describes an approach for enriching and populating a geospatial ontology using both a top-down and a bottom-up approach in order to enable semantic information extraction. The top-down approach is applied in order to incorporate knowledge from existing ontologies. The bottom-up approach is applied in order to enrich and populate the geospatial ontology with semantic information (concepts, relations, and instances) extracted from domain-specific web content.</p>

2013 ◽  
Vol 347-350 ◽  
pp. 3764-3768 ◽  
Author(s):  
Zhuo Zhang ◽  
Xin Nan Fan ◽  
Xue Wu Zhang ◽  
Hai Yan Xu ◽  
Min Li

Inspired by the research of human visual system in neuroanatomy and psychology, the paper proposes a two-way collaborative visual attention model for target detection.In this new method , bottom-up attention information cooperates with top-down attention information to detect a target rapidly and accuractly. Firstly,the statistical prior knowledge of target and background is applied to optimize bottom-up attention information in different feature space and scale space.Secondly, after the SNR of salience difference between target and interference is computed ,the bottom-up gain factor is obtained.Thirdly, the gain factor is applied to adjust bottom up attention information extraction and then to maximize the salience contrast of target and background.Finally, target is detected by adjusted saliency.Experimental results shows that the proposed model in this paper can improve the real-time capability and reliability of target detection.


2019 ◽  
Vol 9 (7) ◽  
pp. 169 ◽  
Author(s):  
Susana Silva ◽  
Carolina Dias ◽  
São Luís Castro

The acoustic cues that guide the assignment of phrase boundaries in music (pauses and pitch movements) overlap with those that are known for speech prosody. Based on this, researchers have focused on highlighting the similarities and neural resources shared between music and speech prosody segmentation. The possibility that music-specific expectations add to acoustic cues in driving the segmentation of music into phrases could weaken this bottom-up view, but it remains underexplored. We tested for domain-specific expectations in music segmentation by comparing the segmentation of the same set of ambiguous stimuli under two different instructions: stimuli were either presented as speech prosody or as music. We measured how segmentation differed, in each instruction group, from a common reference (natural speech); thus, focusing on how instruction affected delexicalization effects (natural speech vs. transformed versions with no phonetic content) on segmentation. We saw interactions between delexicalization and instruction on most segmentation indices, suggesting that there is a music mode, different from a speech prosody mode in segmentation. Our findings highlight the importance of top-down influences in segmentation, and they contribute to rethinking the analogy between music and speech prosody.


Author(s):  
Senthil Kumar Narayanasamy ◽  
Dinakaran Muruganantham

The exponential growth of data emerging out of social media is causing challenges in decision-making systems and poses a critical hindrance in searching for the potential information. The major objective of this chapter is to convert the unstructured data in social media into the meaningful structure format, which in return brings the robustness to the information extraction process. Further, it has the inherent capability to prune for named entities from the unstructured data and store the entities into the knowledge base for important facts. In this chapter, the authors explain the methods to identify all the critical interpretations taken over to find the named entities from Twitter streams and the techniques to proportionally link it with appropriate knowledge sources such as DBpedia.


2021 ◽  
Author(s):  
Katrin Rentzsch ◽  
Michela Schröder-Abé

Classical theoretical perspectives have implied that either global self-esteem has an impact on domain-specific self-esteem (top-down) or domain-specific self-esteem affects global self-esteem (bottom-up). The goal of the present research was to investigate whether classical top-down and bottom-up approaches could withstand a thorough test. To do so, we applied elaborate analytical methods in a 4-wave longitudinal study across 6 years with preregistered hypotheses and data analyses. We analyzed data from N = 1,417 German participants (30.6% men, median of 12 to 13 years of education) with an average age of 47.0 years (SD = 12.4, Range 18 to 88) at intake. Analyses using latent variable approaches for modeling intraindividual change provided evidence of top-down effects only. For example, participants with higher global self-esteem exhibited an increase in performance self-esteem but not vice versa. Our results also provided evidence of “vertical” associations between global and domain-specific self-esteem, that is, parallel development within the same time frame. In addition, the analyses revealed high rank order stability and a substantial trait component in global self-esteem and the self-esteem domains. The present findings have important theoretical and practical implications for the stability and development of self-esteem in adulthood and advance the understanding of global and domain-specific self-esteem in personality theory.


Author(s):  
Rachel Winter ◽  
Julia DeCook

Social media platforms play an increasing role in politics, facilitating the circulation of populist texts disseminated by politicians, official campaign media, and user-generated content, all of which contribute to voters’ perceptions of politicians and political issues. The networks and affordances of social media platforms allow for the development of an individualized, affective connection with voters, which is a particularly important strategy for far-right politicians, who are often stigmatized. Furthermore, social media enables the circulation of user-generated materials in a form of digital political participation, allowing citizens to respond in real-time to political developments. While digital political participation ostensibly offers the potential for the expression of marginalized perspectives, digital texts predominantly emphasize and enforce existing hierarchies, particularly the supremacy of whiteness. This panel explores visuals and memes circulated on social media through the lenses of platform studies, whiteness studies, nostalgia, and Critical Discourse Analysis. By examining both “top-down” media disseminated by public figures and “bottom-up” user-generated content, this panel provides an in-depth understanding of the social media ecosystems that work to preserve and extend far-right values and white supremacy. Rachel Winter focuses on the influence of official campaign materials on user-generated content, as well as the impacts of both on candidate image management and the racial hierarchy of the United States. An analysis of representations of race in user-generated Rafael “Ted” Cruz and Robert “Beto” O’Rourke memes reveals an embedded valuation of whiteness and white supremacy to the detriment of other racial demographics. Political memes collected from Facebook, Twitter, Instagram, Tumblr, and Reddit uphold the importance of the white racial identity of candidates and, in so doing, attempt to preserve White American identities from the perceived threat of multiculturalism embodied in racially diverse politicians and their constituents. Julia DeCook examines nostalgia and chronotopes in alt-right memes, contending that the emphasis on “tradition” over “progress” is an attempt to unify the alt-right and preserve white identity and supremacy from threats of globalization and feminism. The alt-right creates virtual nation-states that use consistent linguistic strategies to enable these groups to engage in a form of collective action. Examining white supremacist memes from Reddit and Instagram, Panelist 2 explores the ways that time, memory, and the abstract conception of “the past” are used in digital propaganda to appeal to younger voters and emphasize the myth that whiteness must be protected from the threat of multiculturalism.


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