Pith Number

pith:2XAYFRGY

pith:2025:2XAYFRGYFKHMSECSFJHVWABHYX

not attested not anchored not stored refs resolved

Combining Abstract Argumentation and Machine Learning for Efficiently Analyzing Low-Level Process Event Streams

Bettina Fazzinga, Filippo Furfaro, Francesco Scala, Luigi Pontieri, Sergio Flesca

A neuro-symbolic approach uses machine learning to suggest event interpretations and argumentation to refine them with prior knowledge.

arxiv:2505.05880 v2 · 2025-05-09 · cs.AI · cs.LG

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{2XAYFRGYFKHMSECSFJHVWABHYX}

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 open · sign in to claim

4 Citations open

5 Replications open

✓ 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.

Claims

C1strongest claim

The proposed data-efficient neuro-symbolic approach, where candidate interpretations returned by the example-driven sequence tagger are refined by the AAF-based reasoner, allows leveraging prior knowledge to compensate for the scarcity of example data, as confirmed by experimental results.

C2weakest assumption

That the sequence-tagging model produces sufficiently accurate candidate interpretations even with limited training data, and that the AAF reasoner can reliably improve those candidates in highly uncertain mapping scenarios without introducing new inconsistencies.

C3one line summary

A neuro-symbolic approach trains a sequence tagger on limited examples to propose event interpretations and refines them via an Abstract Argumentation Framework to handle uncertain mappings in process streams.

References

35 extracted · 35 resolved · 1 Pith anchors

[1] J., Mannhardt, F., de Leoni, M 2021

[2] Tax, N. Human activity prediction in smart home environments with LSTM neural networks.14th International Conference on Intelligent Environments, IE 2018, Roma, Italy, June 25-28, 201840–47 (2018) 2018

[3] & van der Aalst, W 2016

[4] Fazzinga, B., Flesca, S., Furfaro, F. & Pontieri, L. Process mining meets argumen- tation: Explainable interpretations of low-level event logs via abstract argumentation. Information Systems107(2022) 2022

[5] Baier, T., Di Ciccio, C., Mendling, J. & Weske, M. Gaaloul, K., Schmidt, R., Nurcan, S., Guerreiro, S. & Ma, Q. (eds)Matching of events and activities - an approach using declarative modeling constrai 2015

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-26T02:03:50.372746Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d5c182c4d82a8ec910522a4f5b0027c5f32cd1e963cf5282ca1ef209df31f4a1

Aliases

arxiv: 2505.05880 · arxiv_version: 2505.05880v2 · doi: 10.48550/arxiv.2505.05880 · pith_short_12: 2XAYFRGYFKHM · pith_short_16: 2XAYFRGYFKHMSECS · pith_short_8: 2XAYFRGY

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/2XAYFRGYFKHMSECSFJHVWABHYX \
  | 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: d5c182c4d82a8ec910522a4f5b0027c5f32cd1e963cf5282ca1ef209df31f4a1

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "c3933094513bc2a8419dbab177294d5984405968742eb03175583e80fb5e4e82",
    "cross_cats_sorted": [
      "cs.LG"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2025-05-09T08:45:07Z",
    "title_canon_sha256": "71ca52edf8d9debf7024b56057cf535444c07964e19d19b65ee8105d3a22ae94"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2505.05880",
    "kind": "arxiv",
    "version": 2
  }
}