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Paper Citation Record · LEDGER

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction

As of 7 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2607.25751.

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

pith.paper-citation-record.v1
2607.25751 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T01:37:24.039411Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e27b157a-f081-4daf-85ed-8eca963ec3f3 · outbound

This paper cites Random forests.Machine learning, 45(1):5–32, 2001.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Random forests.Machine learning, 45(1):5–32, 2001

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T01:37:24.003539Z digest=sha256:99039db3bb85195844da1fff0d66f1d95a12fa146953462557f272bb1c9cb053

Observation 8964bd5f-4968-4c0a-82e1-b4478c258f46 · outbound

This paper cites Similarity encod- ing for learning with dirty categorical variables.Machine Learning, 107(8):1477–1494, 2018.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Similarity encod- ing for learning with dirty categorical variables.Machine Learning, 107(8):1477–1494, 2018

Reference 2

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no resolver link, observed 2026-08-01T01:37:24.006889Z

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source=pdf_text observed=2026-08-01T01:37:24.006889Z digest=sha256:3a608e2eafc1d33b2d8f561bd890f6187dc7792b448b43d04b387187e8c790e3

Observation 825f9f9f-520f-4d7d-81f1-ef75c2ce87e2 · outbound

This paper cites Amiri, and B.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Amiri, and B

Reference 3

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source=pdf_text observed=2026-08-01T01:37:24.009495Z digest=sha256:f61fab27566399b73bdc1084221fb7d924f3135e27e0905597eeec12b07ffb93

Observation 1b753f68-93de-457d-843d-330d75b7ee2c · outbound

This paper cites Will you come back / check-in again? understanding characteristics leading to urban revisitation and re-check- in.Proc.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Will you come back / check-in again? understanding characteristics leading to urban revisitation and re-check- in.Proc

Reference 4

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source=pdf_text observed=2026-08-01T01:37:24.011818Z digest=sha256:c0b9f9c18be8b1596a7ffdb63dc719894cfdc2782d149bf3ad5fb7628abf6a8d

Observation e7d5fe14-301f-4c57-b584-cbd30da76879 · outbound

This paper cites Myers, and Jure Leskovec.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Myers, and Jure Leskovec

Reference 5

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source=pdf_text observed=2026-08-01T01:37:24.014392Z digest=sha256:c206a8445c5880b65d23359e5aa6c0616741cf63f635da64e302f00b2698c1bc

Observation 37ac76ec-ca96-475d-b87f-19592562d98a · outbound

This paper cites Measuring and recommending time-sensitive routes from location-based data.ACM Trans.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Measuring and recommending time-sensitive routes from location-based data.ACM Trans

Reference 6

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source=pdf_text observed=2026-08-01T01:37:24.016676Z digest=sha256:359a4681e260901cc87b105b71da88eaf38fdf8f0bd739d5a1595abbec8a5a8a

Observation 585c8a34-a324-45b6-aa7d-dfcd1b7ac633 · outbound

This paper cites Pseudo-PFLOW: Development of nationwide synthetic open dataset for people movement based on limited travel survey and open statistical data.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Pseudo-PFLOW: Development of nationwide synthetic open dataset for people movement based on limited travel survey and open statistical data

Reference 7

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source=pdf_text observed=2026-08-01T01:37:24.018902Z digest=sha256:5cc2302844c295b0d040e2e3be8d619b33947766791b4212f25eaa5639b249ab

Observation d7648cf7-f4da-4885-b1ec-122e495f87c7 · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Lightgbm: A highly efficient gradient boosting decision tree

Reference 8

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source=pdf_text observed=2026-08-01T01:37:24.021361Z digest=sha256:fc086d81bf759327866e30dff1ce29aba65a56b2b54d3f59b4581872fa248244

Observation e9bd8e83-8fff-40aa-b52c-f42a64126606 · outbound

This paper cites On route planning by inferring visiting time, modeling user preferences, and mining representative trip patterns.Knowledge and Information Systems, 56(3):581–611, 2018.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction On route planning by inferring visiting time, modeling user preferences, and mining representative trip patterns.Knowledge and Information Systems, 56(3):581–611, 2018

Reference 9

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source=pdf_text observed=2026-08-01T01:37:24.023383Z digest=sha256:b5bd3cacf79eb7c74e9cba48027dcc5153230e85e16ebb99678791592f6b0489

Observation d0282467-ea90-4a5b-b590-d8627bb9f41d · outbound

This paper cites Hierarchical multi-task graph recurrent network for next poi recommendation.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Hierarchical multi-task graph recurrent network for next poi recommendation

Reference 10

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source=pdf_text observed=2026-08-01T01:37:24.025365Z digest=sha256:083ab239139edf45b511bd611fcb1d202c92d8b4406b8b157e85a8083468da0a

Observation a35de734-8d0d-4214-81b6-cacdaa05ba36 · outbound

This paper cites Origin-aware next destination recommendation with personalized preference attention.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Origin-aware next destination recommendation with personalized preference attention

Reference 11

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source=pdf_text observed=2026-08-01T01:37:24.027382Z digest=sha256:640e05c6ee44ce371c371d306084698426191388ba34ac8bac8ffe16cf1ce022

Observation cdd66b14-a497-4a28-9162-5c8026341df9 · outbound

This paper cites Predicting the next location: A recurrent model with spatial and temporal contexts.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Predicting the next location: A recurrent model with spatial and temporal contexts

Reference 12

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no resolver link, observed 2026-08-01T01:37:24.029412Z

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source=pdf_text observed=2026-08-01T01:37:24.029412Z digest=sha256:816ac6a7ce67d98287d553a534388c1f982384e67115a9ae06e4e45396afb659

Observation 72f0c5c9-0476-4733-8612-73b968ca9d05 · outbound

This paper cites Stan: Spatio-temporal attention network for next location recommendation.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Stan: Spatio-temporal attention network for next location recommendation

Reference 13

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source=pdf_text observed=2026-08-01T01:37:24.031686Z digest=sha256:c33b27905cd1c43a87e2f4ada8fa61b790bb1c928226e9870616a2e4fe502917

Observation 662bd6a7-e88e-494d-a194-403c24ae61f5 · outbound

This paper cites Graph-flashback network for next location recommendation.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Graph-flashback network for next location recommendation

Reference 14

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source=pdf_text observed=2026-08-01T01:37:24.033570Z digest=sha256:f10f6c79a5327960e04aaff03d5dbda32c62d326ba76fc85c4f91c5e35f42eba

Observation 6ea725ce-eee3-4a81-b009-f462888558fb · outbound

This paper cites Pflow: Reconstructing people flow recycling large-scale social survey data.IEEE Pervasive Computing, 10(4):27–35, 2011.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Pflow: Reconstructing people flow recycling large-scale social survey data.IEEE Pervasive Computing, 10(4):27–35, 2011

Reference 15

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source=pdf_text observed=2026-08-01T01:37:24.035511Z digest=sha256:d10d286e31d06f56a247f3d15634c78ca90e8a54ce1eeb560c719fd059a97b94

Observation 9ce8eb88-d5db-4651-9ff1-bf04318e1caf · outbound

This paper cites an unresolved cited work.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Unresolved cited work

Reference 16

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source=pdf_text observed=2026-08-01T01:37:24.037453Z digest=sha256:345388a553df1c41c6d9e17c030b3993fde0523230907b233cabf1e5b80717b6

Observation b7d88c5e-c411-4d76-95d1-692327c216fe · outbound

This paper cites Spatio-temporal analysis of passenger travel patterns in massive smart card data.IEEE Transactions on Intelligent Transportation Systems, 18(11):3135–3146, 2017.

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction Spatio-temporal analysis of passenger travel patterns in massive smart card data.IEEE Transactions on Intelligent Transportation Systems, 18(11):3135–3146, 2017

Reference 17

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source=pdf_text observed=2026-08-01T01:37:24.039411Z digest=sha256:fdfa03068c738a51d26b592ea0868912ae84faa2327d09d7f524f8eaf5d563d5

Pith citing papers

No inbound Pith citation observations are available.