Web-based question-answering service of a family physician—the characteristics of queries in a non-commercial open forum

2007 ◽  
Vol 32 (2) ◽  
pp. 123-129 ◽  
Author(s):  
Shlomo Vinker ◽  
Michael Weinfass ◽  
Lior M. Kasinetz ◽  
Eliezer Kitai ◽  
Igor Kaiserman
2010 ◽  
Vol 2010 ◽  
pp. 1-17 ◽  
Author(s):  
Werner Bailer ◽  
Wolfgang Weiss ◽  
Gert Kienast ◽  
Georg Thallinger ◽  
Werner Haas

We propose an interactive video browsing tool for supporting content management and selection in postproduction. The approach is based on a process model for multimedia content abstraction. A software framework based on this process model and desktop and Web-based client applications are presented. For evaluation, we apply two TRECVID style fact finding approaches (retrieval and question answering tasks) and a user survey to the evaluation of the video browsing tool. We analyze the correlation between the results of the different methods, whether different aspects can be evaluated independently with the survey, and if a learning effect can be measured with the different methods, and we also compare the full-featured desktop and the limited Web-based user interface. The results show that the retrieval task correlates better with the user experience according to the survey. The survey rather measures the general user experience while different aspects of the usability cannot be analyzed independently.


2021 ◽  
Author(s):  
Nathan Ji ◽  
Yu Sun

The digital age gives us access to a multitude of both information and mediums in which we can interpret information. A majority of the time, many people find interpreting such information difficult as the medium may not be as user friendly as possible. This project has examined the inquiry of how one can identify specific information in a given text based on a question. This inquiry is intended to streamline one's ability to determine the relevance of a given text relative to his objective. The project has an overall 80% success rate given 10 articles with three questions asked per article. This success rate indicates that this project is likely applicable to those who are asking for content level questions within an article.


Author(s):  
Rosy Madaan ◽  
Sharma A.K ◽  
Ashutosh Dixit ◽  
Deepti Kapri ◽  
Renu Mudgal

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