Research on clothing product reviews mining based on the maximum entropy
EAI Endorsed Transactions on Energy Web, ISSN: 2032-944X, Vol: 15, Issue: 4, Page: 1-4
2015
- 1Citations
- 5Captures
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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.
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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.
Conference Paper Description
this paper excavated the review theme of clothing products by method of association rules, and built a maximum entropy model for the reviews classification. Then this paper did experimental verification to large-scale clothing product reviews classification, which verified the practical effect that maximum entropy model had in the comment text classification problems. In the process of classification, the maximum entropy model had a good effect, of which accuracy was over 90%.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84981194117&origin=inward; http://dx.doi.org/10.4108/eai.19-8-2015.2260919; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84962367281&origin=inward; http://eudl.eu/doi/10.4108/eai.19-8-2015.2260919; https://dx.doi.org/10.4108/eai.19-8-2015.2260919; https://eudl.eu/doi/10.4108/eai.19-8-2015.2260919
European Alliance for Innovation n.o.
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