Mapping an automated survey coding task into a probabilistic text categorization framework
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), ISSN: 0302-9743, Vol: 2389, Page: 115-124
2002
- 6Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures6
- Readers6
Conference Paper Description
This paper describes how to applya probabilistic Text Categorization method to a different and new domain where documents are answers to open end questionnaires and codes viewed as categories consist of a hierarchical model. A reduced size training set mayb e used taking advantage of the hierarchical organization of categories. The system developed in this framework aims at helping psychologists in the evaluation of open end surveys inquiring about job candidates' competencies.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84943226044&origin=inward; http://dx.doi.org/10.1007/3-540-45433-0_18; http://link.springer.com/10.1007/3-540-45433-0_18; http://link.springer.com/content/pdf/10.1007/3-540-45433-0_18; https://dx.doi.org/10.1007/3-540-45433-0_18; https://link.springer.com/chapter/10.1007/3-540-45433-0_18
Springer Nature
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