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Paper Citation Record · LEDGER

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets

As of 18 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 3 inbound Pith citation observations for arXiv:2412.19420.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.19420 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:39:35.568317Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:57:30.313371Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-08T16:19:18.720719Z

Reference resolution

25 of 25 outbound references displayed

  • verified exact2
  • verified fuzzy10
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 69dc9dcb-5a26-4062-b8ae-4601f1da5765 · outbound

This paper cites Dynamic Risk Control and Asset Allocation Using Q-Learning in Financial Markets.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Dynamic Risk Control and Asset Allocation Using Q-Learning in Financial Markets

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-11T00:39:36.392566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T00:39:35.389815Z digest=sha256:fed5b9dd61f223c54e697f6767ad7131f2611b8d789f63432f78eca568f82e4c

Observation 99d7ecbc-3bd7-4923-b3b8-0b4fab0c19f7 · outbound

This paper cites Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-11T00:39:36.062295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T00:39:35.398187Z digest=sha256:c286a028b55790b311c82e36f3879c80b51988387ed59b7cf6c2675f09692006

Observation 0631f532-8d41-4566-b1b3-b42e19a3d068 · outbound

This paper cites Harnessing LLMs for API Interactions: A Framework for Classification and Synthetic Data Generation.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Harnessing LLMs for API Interactions: A Framework for Classification and Synthetic Data Generation

Reference 3

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no resolver link, observed 2026-08-11T00:39:35.405830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.405830Z digest=sha256:b503084100304e494160328ac0190562115939942545a9982319efb3a9e04452

Observation 84224822-e140-4e6e-9e38-9bc3805b3c69 · outbound

This paper cites Comparison of Tree-Based Feature Selection Algorithms on Biological Omics Dataset,.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Comparison of Tree-Based Feature Selection Algorithms on Biological Omics Dataset,

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T00:39:35.413585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.413585Z digest=sha256:865ed70af069a5c1608a9233420c3e2c92770fe3f5f85ccbb0a5e06ceacfc3f2

Observation aba7aa23-bc8f-49ff-b9c5-8d3ef1f887e0 · outbound

This paper cites Probabilistic Support Prediction: Fast frequent itemset mining in dense data,.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Probabilistic Support Prediction: Fast frequent itemset mining in dense data,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:39:36.355665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T00:39:35.420766Z digest=sha256:6d4d757469fa0f698460b0d3a0fa8aaffc50fe70f2122831ee9fa59aac69480e

Observation 27b3922b-0071-4dad-9cc1-e35232acba8e · outbound

This paper cites Data Heterogeneity's Impact on the Performance of Frequent Itemset Mining Algorithms,.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Data Heterogeneity's Impact on the Performance of Frequent Itemset Mining Algorithms,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:39:36.326775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T00:39:35.427501Z digest=sha256:248dd1de3335bf7cc7d6ab3f3ab5d3474c65d9f43c8e5a1fb88054c2ebba3e3b

Observation ea2c9ae8-84a1-4979-8cc2-7998b017cfc8 · outbound

This paper cites Secure Two-Party Frequent Itemset Mining with Guaranteeing Differential Privacy,.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Secure Two-Party Frequent Itemset Mining with Guaranteeing Differential Privacy,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:39:36.303235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T00:39:35.442633Z digest=sha256:b89dd676118936c7702d2c470dfa5f9ddc984d14c70a29a799c284d7a3adee05

Observation 9dc8a286-ba9e-48d8-a695-c87778dcf296 · outbound

This paper cites Optimization of frequent itemset mining parallelization algorithm based on spark platform,.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Optimization of frequent itemset mining parallelization algorithm based on spark platform,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:39:36.267071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T00:39:35.451551Z digest=sha256:b79a81d8c8c5eb5680b71ac8f0c6b7940c7f8078d98bf4d02466e6fb54f7e3d9

Observation 7e62a591-12fe-4ee4-8813-e3942905327c · outbound

This paper cites Optimizing Gesture Recognition for Seamless UI Interaction Using Convolutional Neural Networks.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Optimizing Gesture Recognition for Seamless UI Interaction Using Convolutional Neural Networks

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T00:39:35.462006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.462006Z digest=sha256:02775fad01eaa80fa73dd0f51a40291d1c6de7342ec09e7525d1968debbf96f4

Observation 728f9c3f-627c-43a9-9d61-290fbb2495d1 · outbound

This paper cites Calibration Learning for Few-shot Novel Product Description,.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Calibration Learning for Few-shot Novel Product Description,

Reference 10

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unresolved
no resolver link, observed 2026-08-11T00:39:35.469292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.469292Z digest=sha256:9f00e81f168cdc2b3c187f391675c2551d165e4a58170f196419e796977a0a82

Observation b1b0bcf1-dd42-44a0-b139-ab6bc6b914d9 · outbound

This paper cites Advanced Risk Prediction and Stability Assessment of Banks Using Time Series Transformer Models.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Advanced Risk Prediction and Stability Assessment of Banks Using Time Series Transformer Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T00:39:35.476565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.476565Z digest=sha256:5e442da7a5c36b7b487357ab49a18be10f486b0047a148b605b3280d1d0c7461

Observation 02c4cdf8-9bee-4602-9848-decdab8ebf66 · outbound

This paper cites Graph Neural Network-Based Entity Extraction and Relationship Reasoning in Complex Knowledge Graphs.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Graph Neural Network-Based Entity Extraction and Relationship Reasoning in Complex Knowledge Graphs

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T00:39:35.483572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.483572Z digest=sha256:ce648b971957050bee9929292c755a4de91d39a4753b9753828d8286df52d13d

Observation 4d96a41d-8ce4-4f59-861f-1765a46bb8e7 · outbound

This paper cites Stock Type Prediction Model Based on Hierarchical Graph Neural Network.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Stock Type Prediction Model Based on Hierarchical Graph Neural Network

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T00:39:35.491963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.491963Z digest=sha256:f5d6e37bcd195ec0e8838556eab54c58d2a8436782bd8d34899792a53a1546f8

Observation 04b7bf51-a852-4162-83e7-64b8bb6360cf · outbound

This paper cites Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Mining.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Mining

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T00:39:35.499130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.499130Z digest=sha256:9ccb1151f98d40e231ba32fbe4ee93f30c4793a78651922f761d9416ddd7df83

Observation f08225f2-6c1d-4a96-a5bf-32c59ee5002d · outbound

This paper cites An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T00:39:35.504950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.504950Z digest=sha256:e6134ee7758fb9cc8c8ea3247db7884e1f897fed33f3769b375b06cfb7371ea9

Observation b5b00f41-c46e-41bd-ae1d-035dafbd8b1a · outbound

This paper cites Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T00:39:35.511499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.511499Z digest=sha256:65d71e2c03304ae4168c7490fb014cf7e2fd8ffd39ea7b06586200c85c2fef8c

Observation f298d99f-1a9b-4d6a-a141-15a2386e2f62 · outbound

This paper cites Self-Supervised Credit Scoring with Masked Autoencoders: Addressing Data Gaps and Noise Robustly,.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Self-Supervised Credit Scoring with Masked Autoencoders: Addressing Data Gaps and Noise Robustly,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:39:36.212993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T00:39:35.519868Z digest=sha256:4c7afcc4d50d810354712900fbfa575f70a79ab2a0cbb2cfd1b5c361df7c98e7

Observation 717bd985-2a73-47b0-b487-1f800df7c4b9 · outbound

This paper cites Self- Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks,.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Self- Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:39:36.183398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T00:39:35.526123Z digest=sha256:0cd7c58fb5c36ff991747a77ca22e605277297ae0431a3974a68b10e21c7d318

Observation 64556f6e-1148-41f3-84a7-d4a2db550347 · outbound

This paper cites Optimizing Multi-Task Learning for Enhanced Performance in Large Language Models.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Optimizing Multi-Task Learning for Enhanced Performance in Large Language Models

Reference 19

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unresolved
no resolver link, observed 2026-08-11T00:39:35.531977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.531977Z digest=sha256:400f22843a345facd7a334587739ae672e9853769a3925c1f25efc234c2443b5

Observation be00fb9f-d4c7-4821-a4ba-033bc2fa26ae · outbound

This paper cites Adaptive Optimization for Enhanced Efficiency in Large-Scale Language Model Training.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Adaptive Optimization for Enhanced Efficiency in Large-Scale Language Model Training

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T00:39:35.538864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.538864Z digest=sha256:1a26f7ce59fe215e32517851f8a1f7e28f2d8900680b73299ec20dcd6698732e

Observation 78ba4ada-4ac6-4d01-be08-53337ea864f5 · outbound

This paper cites Multi-Source Data-Driven LSTM Framework for Enhanced Stock Price Prediction and Volatility Analysis,.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Multi-Source Data-Driven LSTM Framework for Enhanced Stock Price Prediction and Volatility Analysis,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:39:36.157145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T00:39:35.544652Z digest=sha256:8756e1f7d98d4a5e6271157f73bc46fe2373ac3f06040d94b18f8ab6d6a7d1f5

Observation b3447239-ddc9-40ee-9eb4-4b2ddb81ccb8 · outbound

This paper cites Dynamic User Interface Generation for Enhanced Human-Computer Interaction Using Variational Autoencoders.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Dynamic User Interface Generation for Enhanced Human-Computer Interaction Using Variational Autoencoders

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-11T00:39:35.550447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:39:35.550447Z digest=sha256:3ef9d6835327c465e507a57105e9f9453d33eb35b3a74bbaa68a3e3d0794bbfd

Observation 90d46598-cfcd-4a99-80fa-3c364cefd242 · outbound

This paper cites Investigation of Creating Accessibility Linked Data Based on Publicly Available Accessibility Datasets,.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Investigation of Creating Accessibility Linked Data Based on Publicly Available Accessibility Datasets,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:39:36.119232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T00:39:35.556584Z digest=sha256:72f8bc7669adff8c8bfa0f30508e0d7432e2d3c5be1d35c6804f17c4e66dda48

Observation 68813e7e-3de3-4b1a-9c3f-ae3374d79bc4 · outbound

This paper cites Enhancing Few-Shot Learning with Integrated Data and GAN Model Approaches.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets Enhancing Few-Shot Learning with Integrated Data and GAN Model Approaches

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-11T00:39:35.648515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T00:39:35.562107Z digest=sha256:fad7501ce334e61067b5cc6c924335d2f36f500dbf6e9bbd0fb9ad46bdf3cab5

Observation 3d052795-50a5-4a93-a79f-b7411fe0b727 · outbound

This paper cites New spark solutions for distributed frequent itemset and association rule mining algorithms,.

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets New spark solutions for distributed frequent itemset and association rule mining algorithms,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T00:39:36.091342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-11T00:39:35.568317Z digest=sha256:b421e06117831e4f308f4b89e2e85b74a208ebec1a34ce7a462b44c2631f3db0

Pith citing papers

Observation 88a83fde-d0fa-4298-8296-a475f84a7c22 · inbound

Multi-Level Attention and Contrastive Learning for Enhanced Text Classification with an Optimized Transformer cites this paper.

Multi-Level Attention and Contrastive Learning for Enhanced Text Classification with an Optimized Transformer A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets

Reference 9

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unresolved
no resolver link, observed 2026-08-10T15:57:30.313371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:57:30.313371Z digest=sha256:ea659fb656c5602a013eec471121ed33aac3c324e0b245b8f873f9746eaae852

Observation 2590dbea-fc8b-42b7-9406-065bd20e7ecd · inbound

Dynamic Adaptation of LoRA Fine-Tuning for Efficient and Task-Specific Optimization of Large Language Models cites this paper.

Dynamic Adaptation of LoRA Fine-Tuning for Efficient and Task-Specific Optimization of Large Language Models A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T14:55:04.110839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:55:04.110839Z digest=sha256:5d50b5db3378c2284c02dfa707b7b58b0fbbcdc1e36f2d29e5deaa03c6fa34a1

Observation 32d1a750-0460-42eb-b7ae-a936708cc833 · inbound

Multi-Scale Transformer Architecture for Accurate Medical Image Classification cites this paper.

Multi-Scale Transformer Architecture for Accurate Medical Image Classification A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-08T16:19:18.724208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-08T16:19:18.499654Z digest=sha256:27593f01c977d3b17c89dc4a40a5565fa60cbcbb69a896b221fa42e51834cace