No, it changed a bit.And it does work, that’s why it changed. It generates the cite key for newly added items, as the preference choice says.
Christiaan > On 16 May 2023, at 18:59, M. Tamer Özsu via Bibdesk-users > <[email protected]> wrote: > > Yes, Christian, that is the case. It never occurred to me that it could be a > problem; I’ve always had it turned on and it used to work (I think). Perhaps > I was temporarily turning it off previously. > > Many thanks. > > ==Tamer > >> On May 16, 2023, at 10:13 AM, Christiaan Hofman <[email protected]> wrote: >> >> 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 >>> <[email protected]> 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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