Command line:
```bash
jupyter nbconvert --to latex --TagRemovePreprocessor.remove_cell_tags='{"skip"}' --TagRemovePreprocessor.enabled=True 'nb.ipynb'
```
Also, to use it via python you need to enable the `TagRemoveProcessor` manually.
See: [source](https://stackoverflow.com/q/58564376/991496)
%A Author
%B Secondary Title (of a Book or Conference Name)
%C Place Published
%D Year
%E Editor /Secondary Author
%F Label
%G Language
%H Translated Author
%I Publisher
%J Journal Name
%K Keywords
%L Call Number
%M Accession Number
%N Number (Issue)
%O Alternate Title
%P Pages
%Q Translated Title
%R DOI
%S Tertiary Title
%T Title
%U URL
%V Volume
%W Database Provider
%X Abstract
%Y Tertiary Author / Translator
%Z Notes
%0 Reference Type
%1 Custom 1
%2 Custom 2
%3 Custom 3
%4 Custom 4
%6 Number of Volumes
%7 Edition
%8 Date
%9 Type of Work
%? Subsidiary Author
%@ ISBN/ISSN
%! Short Title
%# Custom 5
%$ Custom 6
%] Custom 7
%& Section
%( Original Publication
%) Reprint Edition
%* Reviewed Item
%+ Author Address
%^ Caption
%> File Attachments
%< Research Notes
%[ Access Date
%= Custom 8
%~ Name of Database
Tags - for some, one of the best ideas on the web, for others, merely a visual distraction. Yes, we’re talking about those loosely defined categories which are usually organized into cute little clouds. Looking for tag-related resources can be tough, so
Part of the allure of classifying things by assigning tags to them is that the user can give free reign to sloppiness. There is no authority —human or computational— passing judgment on the appropriateness or validity of tags, because tags have to mak
Part of the allure of classifying things by assigning tags to them is that the user can give free reign to sloppiness. There is no authority —human or computational— passing judgment on the appropriateness or validity of tags, because tags have to mak
The goal of this ontology is to model the relationship between an agent, an arbitrary resource, and one or more tags. This relationship is embodied in one or more taggings, which are temporal events associating the actors.
The goal of this ontology is to model the relationship between an agent, an arbitrary resource, and one or more tags. This relationship is embodied in one or more taggings, which are temporal events associating the actors.
The Tagging 2.0 panel I organized at South by SouthWest 2006 in March is now a Tagging 2.0 podcast among the many SXSW 2006 podcasts you can download.The Tagging 2.0 panel was one of the “highly-rated panels” this year, tied for first place with a num
TagCloud is an automated Folksonomy tool. Essentially, TagCloud searches any number of RSS feeds you specify, extracts keywords from the content and lists them according to prevalence within the RSS feeds.
As I <a href="http://blog.pietrosperoni.it/2005/04/12/technorati-tag-rss/">predicted</a>, a service that offers rss feed of technorati tag blog entries has appeared.
D. Skoutas, and M. Alrifai. In Proc. of 20th ACM international conference on Information and knowledge management (CIKM '11), ACM, New York, NY, USA, 221-230., (2011)
M. Magableh, A. Cau, H. Zedan, and M. Ward. Proceedings of the IADIS International Conferences Collaborative Technologies 2010 and Web Based Communities 2010, page 178--182. (July 2010)
R. Abbasi, M. Grzegorzek, and S. Staab. Semantic Multimedia, volume 5887 of Lecture Notes in Computer Science, page 65--76. Springer Berlin / Heidelberg, (2009)