Targeted Keyword Filtering for Accelerated Spoken Topic Identification

2021 ◽  
Author(s):  
Jonathan Wintrode
Keyword(s):  
Topic Identification

Automatic Speech Recognition and Topic Identification from Speech for Almost-Zero-Resource Languages

2018 ◽  
Author(s):  
Matthew Wiesner ◽  
Chunxi Liu ◽  
Lucas Ondel ◽  
Craig Harman ◽  
Vimal Manohar ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Topic Identification

Tracking the dynamics of co-word networks for emerging topic identification

2021 ◽  
Vol 170 ◽  
pp. 120944
Author(s):  
Lu Huang ◽  
Xiang Chen ◽  
Xingxing Ni ◽  
Jiarun Liu ◽  
Xiaoli Cao ◽  
...  
Keyword(s):  
Topic Identification

scholarly journals Evaluating Cultural Impact in Discursive Space through Digital Footprints

2021 ◽  
Vol 13 (7) ◽  
pp. 4043 ◽  
Author(s):  
Jesús López Baeza ◽  
Jens Bley ◽  
Kay Hartkopf ◽  
Martin Niggemann ◽  
James Arias ◽  
...  
Keyword(s):  
Social Media ◽  
Language Processing ◽  
Social Activity ◽  
Test Site ◽  
Cultural Discourse ◽  
Discursive Space ◽  
Topic Identification ◽  
Small Test ◽  
The Impact ◽  
The City

The research presented in this paper describes an evaluation of the impact of spatial interventions in public spaces, measured by social media data. This contribution aims at observing the way a spatial intervention in an urban location can affect what people talk about on social media. The test site for our research is Domplatz in the center of Hamburg, Germany. In recent years, several actions have taken place there, intending to attract social activity and spotlight the square as a landmark of cultural discourse in the city of Hamburg. To evaluate the impact of this strategy, textual data from the social networks Twitter and Instagram (i.e., tweets and image captions) are collected and analyzed using Natural Language Processing intelligence. These analyses identify and track the cultural topic or “people talking about culture” in the city of Hamburg. We observe the evolution of the cultural topic, and its potential correspondence in levels of activity, with certain intervention actions carried out in Domplatz. Two analytic methods of topic clustering and tracking are tested. The results show a successful topic identification and tracking with both methods, the second one being more accurate. This means that it is possible to isolate and observe the evolution of the city’s cultural discourse using NLP. However, it is shown that the effects of spatial interventions in our small test square have a limited local scale, rather than a city-wide relevance.

Automatic new topic identification in search engine transaction logs

2006 ◽  
Vol 16 (3) ◽  
pp. 323-338 ◽  
Author(s):  
H. Cenk Ozmutlu ◽  
Fatih Cavdur ◽  
Seda Ozmutlu
Keyword(s):  
Search Engine ◽  
Topic Identification

Text Summarization

2012 ◽  
Author(s):  
Eduard Hovy
Keyword(s):  
Research And Development ◽  
Evaluation Studies ◽  
Text Summarization ◽  
Single Measurement ◽  
Document Summarization ◽  
Topic Identification ◽  
Evaluation Strategies ◽  
And Performance

This article describes research and development on the automated creation of summaries of one or more texts. It defines the concept of summary and presents an overview of the principal approaches in summarization. It describes the design, implementation, and performance of various summarization systems. The stages of automated text summarization are topic identification, interpretation, and summary generation, each having its sub stages. Due to the challenges involved, multi-document summarization is much less developed than single-document summarization. This article reviews particular techniques used in several summarization systems. Finally, this article assesses the methods of evaluating summaries. This article reviews evaluation strategies, from previous evaluation studies, to the two-basic measures method. Summaries are so task and genre specific; therefore, no single measurement covers all cases of evaluation

scholarly journals Factors associated with reporting of abuse against children and adolescents by nurses within Primary Health Care

2014 ◽  
Vol 22 (6) ◽  
pp. 1048-1055 ◽  
Author(s):  
Ana Carine Arruda Rolim ◽  
Gracyelle Alves Remigio Moreira ◽  
Sarah Maria Mendes Gondim ◽  
Soraya da Silva Paz ◽  
Luiza Jane Eyre de Souza Vieira
Keyword(s):  
Health Care ◽  
Primary Health Care ◽  
Children And Adolescents ◽  
Demographic Data ◽  
Cross Sectional Study ◽  
Graduate Studies ◽  
Cross Sectional ◽  
Topic Identification ◽  
Factors Associated ◽  
Primary Health

OBJECTIVE: to analyze the factors associated with the underreporting on the part of nurses within Primary Health Care of abuse against children and adolescents.METHOD: cross-sectional study with 616 nurses. A questionnaire addressed socio-demographic data, profession, instrumentation and knowledge on the topic, identification and reporting of abuse cases. Bivariate and multivariate logistic regression was used.RESULTS: female nurses, aged between 21 and 32 years old, not married, with five or more years since graduation, with graduate studies, and working for five or more years in PHC predominated. The final regression model showed that factors such as working for five or more years, having a reporting form within the PHC unit, and believing that reporting within Primary Health Care is an advantage, facilitate reporting.CONCLUSION: the study's results may, in addition to sensitizing nurses, support management professionals in establishing strategies intended to produce compliance with reporting as a legal device that ensures the rights of children and adolescents.

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