Pith Number
pith:P4RXUAK2
pith:2010:P4RXUAK2TQH6FWP6CHMCUOLJZJ
not attested
not anchored
not stored
refs pending
A Probabilistic Approach for Learning Folksonomies from Structured Data
arxiv:1011.3557 v1 · 2010-11-16 · cs.AI · cs.CY · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{P4RXUAK2TQH6FWP6CHMCUOLJZJ}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
Author claim
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claim
4
Citations
5
Replications
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Portable graph bundle live · download bundle · merged
state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same
current state with the deterministic merge algorithm.
Receipt and verification
| First computed | 2026-05-18T02:23:36.584678Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
7f237a015a9c0fe2d9fe11d82a3969ca7e2f76a4995a18074d4f9c6303b2f9b1
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/P4RXUAK2TQH6FWP6CHMCUOLJZJ \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 7f237a015a9c0fe2d9fe11d82a3969ca7e2f76a4995a18074d4f9c6303b2f9b1
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "1408acf0ec83a42bcc2ff4167930591d52f1fa1a96f22afb8ac75a80eb8b9d61",
"cross_cats_sorted": [
"cs.CY",
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.AI",
"submitted_at": "2010-11-16T00:46:31Z",
"title_canon_sha256": "079ff059b4870d69c1d44a46ddfffae2b631773c41642f2c550c51d21b11e3ed"
},
"schema_version": "1.0",
"source": {
"id": "1011.3557",
"kind": "arxiv",
"version": 1
}
}