Do you have automatic cite key generation turned on (and is your cite key
format %a1:%Y%u2)?
Christiaan
> On 16 May 2023, at 16:03, M. Tamer Özsu via Bibdesk-users
> <bibdesk-users@lists.sourceforge.net> wrote:
>
> I have run into an interesting issue with Bibdesk (1.8.16) that I had not
> encountered before. I have a .bib file that has entries like the following.
> The relevant part of this is the @inproceedings{icde22_Wang:2022aa line. When
> I copy them into my master Bibdesk library, it loses the “icde22_” and shows
> the Cite Key as "Wang:2022aa”. If I manually go in and update the Cite key,
> it shows the “icde22_” but not when I copy/paste it the bibtex record. Any
> ideas as to why this might be happening would be appreciated. In the
> meantime, I’ll try on another machine to see if it something with my setup.
>
> @inproceedings{icde22_Wang:2022aa,
> author = {Wang, Haibo and Ma, Chaoyi and Chen, Shigang and Wang,
> Yuanda},
> booktitle = ICDE22,
> date-added = {2023-05-16 09:11:03 -0400},
> date-modified = {2023-05-16 09:11:04 -0400},
> doi = {10.1109/ICDE53745.2022.00005},
> issn = {2375-026X},
> keywords = {ICDE22,Measurement;Estimation error;Art;Social networking
> (online);Throughput;Data engineering;Servers;Cardinality
> Estimationi;Online;Self morphing;Bitmap},
> pages = {1--13},
> title = {Online Cardinality Estimation by Self-morphing Bitmaps},
> year = {2022},
> abstract = {Estimating the cardinality of a data stream is a
> fundamental problem underlying numerous applications such as traffic
> monitoring in a network or a datacenter, popularity tracking on social media,
> and cache optimization in proxy servers. Existing solutions suffer from high
> processing/query overhead or memory in-efficiency, which prevents them from
> operating online for data streams with very high arrival rates. This paper
> takes a new solution path different from the prior art and proposes a
> self-morphing bitmap, which combines operational simplicity with structural
> dynamics, allowing the bitmap to be morphed in a series of steps with an
> evolving sampling probability that automatically adapts to different stream
> sizes. We evaluate the self-morphing bitmap theoretically and experimentally.
> The results demonstrate that it significantly outperforms the prior art.},
> bdsk-url-1 = {https://doi.org/10.1109/ICDE53745.2022.00005}}
>
>
> ==Tamer
> --
> M. Tamer Özsu
> University of Waterloo
> Cheriton School of Computer Science
> https://cs.uwaterloo.ca/~tozsu
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