MLego: Interactive and Scalable Topic Exploration Through Model Reuse | Paper Citation Record

Observation 9c570954-4ec5-4143-8ecf-928255482a78 · outbound

This paper cites KY k=1 qD (βk | λk) # ·.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse KY k=1 qD (βk | λk) # ·

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.971301Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6c4a12a4-4ff4-4954-a84c-c3234a79e002 · outbound

This paper cites Merge conducts model merging, while Train handles online training for uncovered data.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Merge conducts model merging, while Train handles online training for uncovered data

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.921735Z

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Observation 05fbbb9d-d5c9-43c3-8fec-ab04cec2153e · outbound

This paper cites The main challenge of such a ”generate- and-rank” method is that there are an exponential number of candidate plans, and the plan generation is time-consuming.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse The main challenge of such a ”generate- and-rank” method is that there are an exponential number of candidate plans, and the plan generation is time-consuming

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.941364Z

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This paper cites push down.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse push down

Reference 4

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Observation a1abda85-e9df-4af0-bf81-9c777e10315e · outbound

This paper cites Each point in Figure 3 represents the average value of all points within that interval.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Each point in Figure 3 represents the average value of all points within that interval

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.902911Z

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Observation c6f5addd-32f8-4a59-92fd-9389c8aae77d · outbound

This paper cites For a fixed plan p, the training time cost is quadratic to the data uncovered by the models in p.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse For a fixed plan p, the training time cost is quadratic to the data uncovered by the models in p

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.884120Z

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Observation 7a34bece-8f71-4095-8f4e-771690633951 · outbound

This paper cites Theorem 1.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Theorem 1

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.866805Z

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Observation eb53196e-126c-467c-a220-60c60131085b · outbound

This paper cites To further speed up plan searching, we consider reducing the number of lists (line 8 to 9).

MLego: Interactive and Scalable Topic Exploration Through Model Reuse To further speed up plan searching, we consider reducing the number of lists (line 8 to 9)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.836730Z

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Observation 90c98fa2-e7a4-4357-ae3b-40d7d9c66bb3 · outbound

This paper cites Streaming Gibbs Sampling for LDA Model.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Streaming Gibbs Sampling for LDA Model

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-05T22:02:21.300485Z

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Observation abb556fb-8eab-42b6-b38c-16bb553c0f18 · outbound

This paper cites A survey of top-k query processing techniques in relational database systems,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse A survey of top-k query processing techniques in relational database systems,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.820184Z

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Observation 677f1286-e86c-4f03-8623-83520c7aea38 · outbound

This paper cites Culda: Solving large-scale lda problems on gpus,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Culda: Solving large-scale lda problems on gpus,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.803630Z

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Observation 2702a0ef-74c7-4d4e-826a-763046fdf698 · outbound

This paper cites Lda*: A robust and large-scale topic modeling system,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Lda*: A robust and large-scale topic modeling system,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.787836Z

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Observation dc0625cc-7ed9-4582-8c99-679fd8bf3cb9 · outbound

This paper cites Warplda: A cache efficient o(1) algorithm for latent dirichlet allocation,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Warplda: A cache efficient o(1) algorithm for latent dirichlet allocation,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.772422Z

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Observation 946eaf36-7bf5-47d3-88c4-42c2e9779555 · outbound

This paper cites Reducing the sampling complexity of topic models,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Reducing the sampling complexity of topic models,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.757201Z

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Observation feea7344-929a-4364-93b1-b6f96b823011 · outbound

This paper cites A scalable asynchronous distributed algorithm for topic modeling,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse A scalable asynchronous distributed algorithm for topic modeling,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.741743Z

Source-reported events for the cited work

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Observation bc25e0f4-6f62-4e1f-ad1e-d11fbf6e5396 · outbound

This paper cites Lightlda: Big topic models on modest computer clusters,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Lightlda: Big topic models on modest computer clusters,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.726139Z

Source-reported events for the cited work

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Observation bbeec0d5-0142-499a-ac5c-33e0283490aa · outbound

This paper cites Streaming variational bayes,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Streaming variational bayes,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.711192Z

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Observation 217a2285-13dc-4e3c-a225-b84912060bee · outbound

This paper cites BY b=1 A (Cb, p(Θ)) p(Θ)−1 # p(Θ) ∝ exp (.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse BY b=1 A (Cb, p(Θ)) p(Θ)−1 # p(Θ) ∝ exp (

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.956349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1bcb9146-7d36-41f8-9acb-f1a862458b0f · outbound

This paper cites Topic modeling using latent dirichlet allo- cation: A survey,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Topic modeling using latent dirichlet allo- cation: A survey,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.694750Z

Source-reported events for the cited work

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Observation b9d7aa29-bd69-4217-aba8-dfbf278b4601 · outbound

This paper cites A survey of topic modeling in text mining,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse A survey of topic modeling in text mining,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.671640Z

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Observation a01a412e-d387-4ce2-930d-30cba76c41a7 · outbound

This paper cites Streaming, dis- tributed variational inference for bayesian nonparametrics,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Streaming, dis- tributed variational inference for bayesian nonparametrics,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.654056Z

Source-reported events for the cited work

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Observation d2817173-5bfd-4f28-981a-d867088419cf · outbound

This paper cites Sharing clusters among related groups: Hierarchical dirichlet processes,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Sharing clusters among related groups: Hierarchical dirichlet processes,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.628159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f5dea494-e854-458b-b7df-de2fc0fd4e74 · outbound

This paper cites Online learning for latent dirichlet allocation,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Online learning for latent dirichlet allocation,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.602097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 06dde6de-1ff7-4570-b542-4014a48ff0dc · outbound

This paper cites Latent dirichlet allocation,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Latent dirichlet allocation,

Reference 37

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Observation dd0a6129-3e6f-44a4-acdb-f39853092df1 · outbound

This paper cites Online but accurate inference for latent variable models with local gibbs sampling,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Online but accurate inference for latent variable models with local gibbs sampling,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.561419Z

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Observation d210e539-3774-4d71-8bb7-b5046ace119f · outbound

This paper cites News Category Dataset.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse News Category Dataset

Reference 39

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Source-reported events for the cited work

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This paper cites Misra and J.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Misra and J

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.536274Z

Source-reported events for the cited work

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Observation d9115c04-c239-4e6c-817c-8011ca3a52a0 · outbound

This paper cites Defending against neural fake news,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Defending against neural fake news,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.514759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d99b84eb-52a6-46c0-a208-17e7fdb8cb41 · outbound

This paper cites Efficient computation of top-k frequent terms over spatio-temporal ranges,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Efficient computation of top-k frequent terms over spatio-temporal ranges,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.491360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 60d2eb7a-e337-4435-8ea5-08f59adc25da · outbound

This paper cites Auto- mated phrase mining from massive text corpora,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Auto- mated phrase mining from massive text corpora,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.473271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2b6af60f-153b-47fa-b8be-08cc8a760675 · outbound

This paper cites Efficiently answering top-k frequent term queries in temporal-categorical range,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Efficiently answering top-k frequent term queries in temporal-categorical range,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.455550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b261775a-c924-4d2f-acc2-8235e2187db0 · outbound

This paper cites Scikit-learn: Machine learning in python,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Scikit-learn: Machine learning in python,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.437489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6b90afa9-eaf3-4afc-bcc6-e47c515165a9 · outbound

This paper cites Efficient methods for topic model inference on streaming document collections,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Efficient methods for topic model inference on streaming document collections,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.419181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bba6d9be-5008-46d8-b463-94bea6d1dfde · outbound

This paper cites Fast collapsed gibbs sampling for latent dirichlet allo- cation,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Fast collapsed gibbs sampling for latent dirichlet allo- cation,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.399542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2584a4fe-dced-4d12-ad6d-854b2c037ed5 · outbound

This paper cites Distributed infer- ence for latent dirichlet allocation,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Distributed infer- ence for latent dirichlet allocation,

Reference 48

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1e271d5e-5927-423a-b735-60f7e4dd533f · outbound

This paper cites An architecture for parallel topic models,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse An architecture for parallel topic models,

Reference 49

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Source-reported events for the cited work

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This paper cites Plda: Paral- lel latent dirichlet allocation for large-scale applications,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Plda: Paral- lel latent dirichlet allocation for large-scale applications,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.348594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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MLego: Interactive and Scalable Topic Exploration Through Model Reuse Elda: Lda made efficient via algorithm-system codesign submission,

Reference 51

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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MLego: Interactive and Scalable Topic Exploration Through Model Reuse Approximate query processing: Taming the terabytes,

Reference 52

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Source-reported events for the cited work

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Observation f2d63fe2-a7bb-49b1-9b07-bc83d25839fe · outbound

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MLego: Interactive and Scalable Topic Exploration Through Model Reuse Data cube: a relational aggregation operator generalizing group-by, cross-tab, and sub-totals,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.298335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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This paper cites Efficient scalable accurate re- gression queries in in-dbms analytics,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Efficient scalable accurate re- gression queries in in-dbms analytics,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.280841Z

Source-reported events for the cited work

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Observation 0d52759e-ba38-408a-9db5-1c5b116b2f18 · outbound

This paper cites Prediction cubes,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Prediction cubes,

Reference 55

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Source-reported events for the cited work

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Observation c469eb01-7077-4bd3-a21e-48f363917289 · outbound

This paper cites Scalable k -means clustering via lightweight coresets,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Scalable k -means clustering via lightweight coresets,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.242531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e73da277-499b-4973-be6a-d57953e25c7e · outbound

This paper cites Turning big data into tiny data: Constant-size coresets for k-means, pca and projective clustering,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Turning big data into tiny data: Constant-size coresets for k-means, pca and projective clustering,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.224913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 67d74281-5607-4361-a3f7-1bcfa4b3488d · outbound

This paper cites On coresets for k-means and k-median clustering,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse On coresets for k-means and k-median clustering,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.209009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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This paper cites Fast and accurate k-means for large datasets,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Fast and accurate k-means for large datasets,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.192000Z

Source-reported events for the cited work

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Observation d1e7c1d5-ff94-42af-badc-6cdf4828b52f · outbound

This paper cites Modelhub: Deep learning lifecycle management,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Modelhub: Deep learning lifecycle management,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:22.043713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 44566534-1685-48e3-bb90-5924d946d8da · outbound

This paper cites Towards unified data and lifecycle management for deep learning,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Towards unified data and lifecycle management for deep learning,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:21.836540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 85fcbbe9-0ec7-44b8-ad69-9be814c0d044 · outbound

This paper cites Mistique: A system to store and query model intermediates for model diagnosis,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Mistique: A system to store and query model intermediates for model diagnosis,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:21.614467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2408f493-d16b-4cd0-819a-362af10bc48a · outbound

This paper cites Modeldb: A system for machine learning model management,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Modeldb: A system for machine learning model management,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:21.427823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9035452f-fe46-49a9-832e-3960b3727e4b · outbound

This paper cites Applying data mining techniques for descriptive phrase extraction in digital document collections,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Applying data mining techniques for descriptive phrase extraction in digital document collections,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:21.375671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d7c5662e-33bc-48a6-ad85-a3241ce585c5 · outbound

This paper cites Location-aware top-k term publish/subscribe,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Location-aware top-k term publish/subscribe,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:21.353941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 875efeb3-b82f-4d3f-abc7-dc7683f865e0 · outbound

This paper cites Optimal aggregation algorithms for middleware,.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Optimal aggregation algorithms for middleware,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:21.335907Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0405378e-b1ab-430d-b50a-881813a64082 · outbound

This paper cites Combining fuzzy information from multiple systems (ex- tended abstract),.

MLego: Interactive and Scalable Topic Exploration Through Model Reuse Combining fuzzy information from multiple systems (ex- tended abstract),

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T22:02:21.318159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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