Paper Citation Record · LEDGER

Fine-Tuning Topics through Weighting Aspect Keywords

As of 22 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 1 inbound Pith citation observation for arXiv:2502.08496.

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

pith.paper-citation-record.v1
2502.08496 v2

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T04:56:13.002659Z

measured 66 of 66 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:23:55.117486Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T18:16:17.926450Z

Reference resolution

65 of 65 outbound references displayed

verified exact4
verified fuzzy55
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a36dc128-6d72-418b-b6b7-57d02c3cd9e0 · outbound

This paper cites Latent dirichlet allocation.

Fine-Tuning Topics through Weighting Aspect Keywords Latent dirichlet allocation

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.282174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 682317e3-5438-4874-88b1-b434a40c4094 · outbound

This paper cites BERTopic: Neural topic modeling with a class-based TF-IDF procedure.

Fine-Tuning Topics through Weighting Aspect Keywords BERTopic: Neural topic modeling with a class-based TF-IDF procedure

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T04:56:12.703259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea913d2d-7848-4bbd-89fb-b48f119dc045 · outbound

This paper cites The application of text mining methods in innovation research: current state, evolution patterns, and development priorities.

Fine-Tuning Topics through Weighting Aspect Keywords The application of text mining methods in innovation research: current state, evolution patterns, and development priorities

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.266659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 52a5b08d-b630-4844-ad2e-bb8abaa62fbe · outbound

This paper cites Evolution of topics and trends in emerging research fields: multiple analyses with entity linking, Mann–Kendall test and burst methods in cloud computing.

Fine-Tuning Topics through Weighting Aspect Keywords Evolution of topics and trends in emerging research fields: multiple analyses with entity linking, Mann–Kendall test and burst methods in cloud computing

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.251612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9f1f1db2-0867-4791-a1ae-c2c166229e6a · outbound

This paper cites Short Text Clustering with a Deep Multi-embedded Self-supervised Model.

Fine-Tuning Topics through Weighting Aspect Keywords Short Text Clustering with a Deep Multi-embedded Self-supervised Model

Reference 5

Resolution: verified exact; doi, observed 2026-08-08T04:56:13.072617Z

Source-reported events for the cited work

correction dated 2022-01-17. Source: crossref record 10.1007/978-3-030-86383-8_55->10.1007/978-3-030-86383-8_12:correction, observed 2026-07-11T03:09:17.867122+00:00. This notice travels one citation hop only.

Observation 05c3b065-778c-41ee-a7e0-c17da25e50e8 · outbound

This paper cites Document clustering with dual supervision through feature reweighting.

Fine-Tuning Topics through Weighting Aspect Keywords Document clustering with dual supervision through feature reweighting

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.236349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3f8159c5-53a6-42cc-ac88-7dbcb685579f · outbound

This paper cites Hyperspherical Fuzzy clustering for online document categorization.

Fine-Tuning Topics through Weighting Aspect Keywords Hyperspherical Fuzzy clustering for online document categorization

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.221427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 29744467-437d-4bc5-8146-1a63c3513457 · outbound

This paper cites Clustering massive-categories and complex documents via graph convolutional network.

Fine-Tuning Topics through Weighting Aspect Keywords Clustering massive-categories and complex documents via graph convolutional network

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.206200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 58247401-6528-44c7-b37a-a3a65c43426d · outbound

This paper cites The integrative domain of foresight and competitive intelligence and its impact on R&D management: Integrative domain of foresight and competitive intelligence.

Fine-Tuning Topics through Weighting Aspect Keywords The integrative domain of foresight and competitive intelligence and its impact on R&D management: Integrative domain of foresight and competitive intelligence

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.190211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9f0f9e77-1712-4e10-ac70-9e32f2cc799a · outbound

This paper cites Linking technology intelligence to open innovation.

Fine-Tuning Topics through Weighting Aspect Keywords Linking technology intelligence to open innovation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.174767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 335756ff-8b93-4626-bb46-fe5b225914d8 · outbound

This paper cites Systematic Mapping Studies in Software Engineering.

Fine-Tuning Topics through Weighting Aspect Keywords Systematic Mapping Studies in Software Engineering

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.159284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5c928b4e-e850-4889-be14-4167c66eb56c · outbound

This paper cites Guidelines for conducting systematic mapping studies in software engineering: An update.

Fine-Tuning Topics through Weighting Aspect Keywords Guidelines for conducting systematic mapping studies in software engineering: An update

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.129162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6e9fcfb6-c107-4647-88ef-1ac6073b574f · outbound

This paper cites A correlated topic model of science.

Fine-Tuning Topics through Weighting Aspect Keywords A correlated topic model of science

Reference 13

Resolution: verified exact; doi, observed 2026-08-08T04:56:13.057053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5dd24bb2-d8b1-4b25-b806-90dc17d3d357 · outbound

This paper cites An empirical study on innovation ecosystem, technological trajectory transition, and innovation performance.

Fine-Tuning Topics through Weighting Aspect Keywords An empirical study on innovation ecosystem, technological trajectory transition, and innovation performance

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.114029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation faf2884f-c2f1-4918-81d3-d7bfceb9d7f1 · outbound

This paper cites Linguistic regularities in continuous space word representations.

Fine-Tuning Topics through Weighting Aspect Keywords Linguistic regularities in continuous space word representations

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.097884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bfd23ad8-d151-4b79-9595-2aad7dcf89d9 · outbound

This paper cites Term-weighting approaches in automatic text retrieval.

Fine-Tuning Topics through Weighting Aspect Keywords Term-weighting approaches in automatic text retrieval

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.082110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation efd91aaf-83d5-4daa-a8a3-e28f0836173c · outbound

This paper cites Incremental fuzzy clustering for document categorization.

Fine-Tuning Topics through Weighting Aspect Keywords Incremental fuzzy clustering for document categorization

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.066008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation aef7c418-9890-4eec-a086-36678c09054f · outbound

This paper cites Probabilistic word selection via topic modeling.

Fine-Tuning Topics through Weighting Aspect Keywords Probabilistic word selection via topic modeling

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.050909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a4f0356f-9a53-489a-8e96-682692374ce0 · outbound

This paper cites Incorporating lexical priors into topic models.

Fine-Tuning Topics through Weighting Aspect Keywords Incorporating lexical priors into topic models

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.036320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2b857dfe-e818-44b9-a197-8d251f49b8ce · outbound

This paper cites Seed-guided topic model for document filtering and classification.

Fine-Tuning Topics through Weighting Aspect Keywords Seed-guided topic model for document filtering and classification

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:14.006087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 252702a0-3b33-4207-89d9-88b021fe8587 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Topics through Weighting Aspect Keywords Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-08T04:56:14.021143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4afb0361-3706-4e3a-bb5c-e10880014b5b · outbound

This paper cites Research proposal content extraction using natural language processing and semi-supervised clustering: A demonstration and comparative analysis.

Fine-Tuning Topics through Weighting Aspect Keywords Research proposal content extraction using natural language processing and semi-supervised clustering: A demonstration and comparative analysis

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.976144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c773b115-a9c1-422a-a973-24961acc51d3 · outbound

This paper cites Document Clustering With Dual Supervision Through Feature Reweighting.

Fine-Tuning Topics through Weighting Aspect Keywords Document Clustering With Dual Supervision Through Feature Reweighting

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.990794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2d7c9b20-b804-42c0-bedd-3bb31af827cc · outbound

This paper cites Learning to cluster documents into workspaces using large scale activity logs.

Fine-Tuning Topics through Weighting Aspect Keywords Learning to cluster documents into workspaces using large scale activity logs

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.944302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7be789a0-bf1e-4352-a3c6-2a2e7de9931b · outbound

This paper cites Automatic constraints generation for semisupervised clustering: experiences with documents classification.

Fine-Tuning Topics through Weighting Aspect Keywords Automatic constraints generation for semisupervised clustering: experiences with documents classification

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.960568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7f5c0f10-c73c-4674-ab3a-5d5ce2c29a96 · outbound

This paper cites Heterogeneity of optimal balance between exploration and exploitation:the moderating roles of firm technological capability and industry alliance network position.

Fine-Tuning Topics through Weighting Aspect Keywords Heterogeneity of optimal balance between exploration and exploitation:the moderating roles of firm technological capability and industry alliance network position

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.914676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9e21fb75-67ac-419a-8db9-a32763d97c96 · outbound

This paper cites The Interplay Between Exploration and Exploitation.

Fine-Tuning Topics through Weighting Aspect Keywords The Interplay Between Exploration and Exploitation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.929383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 523911b4-e027-404f-8c96-c482f608cd92 · outbound

This paper cites Intention-guided deep semi-supervised document clustering via metric learning.

Fine-Tuning Topics through Weighting Aspect Keywords Intention-guided deep semi-supervised document clustering via metric learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.884998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 36349085-0eb3-4f41-8878-de78bedbf9bb · outbound

This paper cites Enhancing neural topic model with multi-level supervisions from seed words.

Fine-Tuning Topics through Weighting Aspect Keywords Enhancing neural topic model with multi-level supervisions from seed words

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.899601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d3cc2765-94c9-45d4-a7f4-793a7bc09034 · outbound

This paper cites Design Science in Information Systems Research.

Fine-Tuning Topics through Weighting Aspect Keywords Design Science in Information Systems Research

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.870875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e76c036c-c61e-45b2-87b3-fc03b4ef1031 · outbound

This paper cites Anticipating Future Innovation Pathways Through Large Data Analysis.

Fine-Tuning Topics through Weighting Aspect Keywords Anticipating Future Innovation Pathways Through Large Data Analysis

Reference 31

Resolution: verified exact; doi, observed 2026-08-08T04:56:13.041397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b4a7351c-d132-44c0-8a29-6caba68ab492 · outbound

This paper cites Secure Quantum Communication Technologies and Systems: From Labs to Markets.

Fine-Tuning Topics through Weighting Aspect Keywords Secure Quantum Communication Technologies and Systems: From Labs to Markets

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.841662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 001409a0-3192-4d45-9368-8470e185fcc6 · outbound

This paper cites A Design Science Research Methodology for Information Systems Research.

Fine-Tuning Topics through Weighting Aspect Keywords A Design Science Research Methodology for Information Systems Research

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.856137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ecc6c144-ba76-45e9-a8fe-f1a2a9489dce · outbound

This paper cites Present landscape of quantum computing.

Fine-Tuning Topics through Weighting Aspect Keywords Present landscape of quantum computing

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.811838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 42a0cba0-d999-4d2b-8548-0d7007787af8 · outbound

This paper cites Quantum Communications in Future Networks and Services.

Fine-Tuning Topics through Weighting Aspect Keywords Quantum Communications in Future Networks and Services

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.826847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e3a2b7e8-5f49-4628-a021-ed78b3cf080f · outbound

This paper cites Introduction to information retrieval.

Fine-Tuning Topics through Weighting Aspect Keywords Introduction to information retrieval

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-08T04:56:12.879307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0d5ae03-a3e6-45f3-bdf1-8cf396e9c7a0 · outbound

This paper cites Active Learning Literature Survey.

Fine-Tuning Topics through Weighting Aspect Keywords Active Learning Literature Survey

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.796754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2338527b-2739-47f2-9e72-0130bbfbd04b · outbound

This paper cites Supervised clustering-algorithms and benefits.

Fine-Tuning Topics through Weighting Aspect Keywords Supervised clustering-algorithms and benefits

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.766603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5e990d60-87b9-4f72-beec-aec532aa5603 · outbound

This paper cites An algorithm to cluster documents based on relevance.

Fine-Tuning Topics through Weighting Aspect Keywords An algorithm to cluster documents based on relevance

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.781383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 71d5ee0b-2a59-4d6a-9930-020b92e7dd52 · outbound

This paper cites Seeded Sequential LDA: A Semi-Supervised Algorithm for Topic-Specific Analysis of Sentences.

Fine-Tuning Topics through Weighting Aspect Keywords Seeded Sequential LDA: A Semi-Supervised Algorithm for Topic-Specific Analysis of Sentences

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.737347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d3a3df9e-0f70-4e6b-997c-126727560274 · outbound

This paper cites Improving topic models with latent feature word representations.

Fine-Tuning Topics through Weighting Aspect Keywords Improving topic models with latent feature word representations

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.752106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 43eb0f1a-9630-4ff1-ae11-6bd26d5369ff · outbound

This paper cites Using structural topic modeling to identify latent topics and trends in aviation incident reports.

Fine-Tuning Topics through Weighting Aspect Keywords Using structural topic modeling to identify latent topics and trends in aviation incident reports

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.707490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5d824493-588c-4d21-8c9a-5541992c2d58 · outbound

This paper cites Semisupervised fuzzy clustering with partition information of subsets.

Fine-Tuning Topics through Weighting Aspect Keywords Semisupervised fuzzy clustering with partition information of subsets

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.722782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9701171a-29af-4199-aef3-176db0df042c · outbound

This paper cites Self-organizing weighted incremental probabilistic latent semantic analysis.

Fine-Tuning Topics through Weighting Aspect Keywords Self-organizing weighted incremental probabilistic latent semantic analysis

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.677339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 44aba68c-f234-4179-a60c-34abd98f9e72 · outbound

This paper cites Dataless text classification: A topic modeling approach with document manifold.

Fine-Tuning Topics through Weighting Aspect Keywords Dataless text classification: A topic modeling approach with document manifold

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.692348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f3462056-fdcb-400e-b35c-6e9fce3acc5a · outbound

This paper cites tBERT: Topic models and BERT joining forces for semantic similarity detection.

Fine-Tuning Topics through Weighting Aspect Keywords tBERT: Topic models and BERT joining forces for semantic similarity detection

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.647417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 499836b9-8d70-4e1b-93b9-510f0f601d65 · outbound

This paper cites Research on Multi-label Text Classification Method Based on tALBERT-CNN.

Fine-Tuning Topics through Weighting Aspect Keywords Research on Multi-label Text Classification Method Based on tALBERT-CNN

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.662564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6258cdb7-df56-4827-a21f-bd27195cbf45 · outbound

This paper cites Supervised topic models for multi-label classification.

Fine-Tuning Topics through Weighting Aspect Keywords Supervised topic models for multi-label classification

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.617699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation df4b4cc0-466e-4dd5-9da2-52aa41d9c4ec · outbound

This paper cites An overview of topic modeling and its current applications in bioinformatics.

Fine-Tuning Topics through Weighting Aspect Keywords An overview of topic modeling and its current applications in bioinformatics

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.632588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 33caf350-22c9-431d-afa2-e512f4c7c31c · outbound

This paper cites DOLDA: a regularized supervised topic model for high-dimensional multi-class regression.

Fine-Tuning Topics through Weighting Aspect Keywords DOLDA: a regularized supervised topic model for high-dimensional multi-class regression

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.587742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 07f6be98-c620-4505-a74c-a408b181d702 · outbound

This paper cites Twin labeled LDA: a supervised topic model for document classification.

Fine-Tuning Topics through Weighting Aspect Keywords Twin labeled LDA: a supervised topic model for document classification

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.603325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 79f9ef62-7d2c-44cb-bd81-e9be32964a04 · outbound

This paper cites Effective document labeling with very few seed words: A topic model approach.

Fine-Tuning Topics through Weighting Aspect Keywords Effective document labeling with very few seed words: A topic model approach

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.557648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 720d609f-8c2e-47ab-8d74-1cb8b99cabf1 · outbound

This paper cites Labelset topic model for multi-label document classification.

Fine-Tuning Topics through Weighting Aspect Keywords Labelset topic model for multi-label document classification

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.572749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2bec6659-101b-4f3c-9d21-36c292c127f1 · outbound

This paper cites Dataless Text Classification: A Topic Modeling Approach with Document Manifold.

Fine-Tuning Topics through Weighting Aspect Keywords Dataless Text Classification: A Topic Modeling Approach with Document Manifold

Reference 54

Resolution: metadata mismatch; raw_fallback, observed 2026-08-08T04:56:13.322569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 95d38478-6f23-48bb-b142-6675e253b7d6 · outbound

This paper cites Multi-label dataless text classification with topic modeling.

Fine-Tuning Topics through Weighting Aspect Keywords Multi-label dataless text classification with topic modeling

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.542596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e1bc1ded-802f-42a2-b4c6-25c09cc0a53c · outbound

This paper cites Seed-guided deep document clustering.

Fine-Tuning Topics through Weighting Aspect Keywords Seed-guided deep document clustering

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.511880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation eee80d1a-ddab-467e-b1df-23142e7849de · outbound

This paper cites Community detection in social networks considering topic correlations.

Fine-Tuning Topics through Weighting Aspect Keywords Community detection in social networks considering topic correlations

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.527206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b0faa5da-a17c-46e4-855f-a1e7031f9048 · outbound

This paper cites Transferable adversarial examples can efficiently fool topic models.

Fine-Tuning Topics through Weighting Aspect Keywords Transferable adversarial examples can efficiently fool topic models

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.479866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 175f8b43-f5a0-450a-8297-11824abd1758 · outbound

This paper cites Topic extraction from extremely short texts with variational manifold regularization.

Fine-Tuning Topics through Weighting Aspect Keywords Topic extraction from extremely short texts with variational manifold regularization

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.494977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f6208636-ae06-4971-b22f-b1a717dd84e3 · outbound

This paper cites HiGitClass: Keyword-driven hierarchical classification of GitHub repositories.

Fine-Tuning Topics through Weighting Aspect Keywords HiGitClass: Keyword-driven hierarchical classification of GitHub repositories

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.464765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b5d7473c-4bd4-4c50-82ef-342332c13651 · outbound

This paper cites TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts.

Fine-Tuning Topics through Weighting Aspect Keywords TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-08-08T04:56:13.243397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e22d454a-3b96-4a0a-a69f-2a0b80b331a2 · outbound

This paper cites Topic sentiment mixture: modeling facets and opinions in weblogs.

Fine-Tuning Topics through Weighting Aspect Keywords Topic sentiment mixture: modeling facets and opinions in weblogs

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-08T04:56:12.998207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4663ad28-f305-4190-b568-eb3335aba111 · outbound

This paper cites A study of classification of texts into categories of cybersecurity incident and attack with topic models.

Fine-Tuning Topics through Weighting Aspect Keywords A study of classification of texts into categories of cybersecurity incident and attack with topic models

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.449658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 14c0725b-0eff-4852-bfa0-5ca8b9fcb215 · outbound

This paper cites A two-dimensional topic-Aspect Model for discovering multi-faceted topics.

Fine-Tuning Topics through Weighting Aspect Keywords A two-dimensional topic-Aspect Model for discovering multi-faceted topics

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T04:56:13.434816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 36d86046-40de-41fa-bbf5-5c70712dfaec · outbound

This paper cites an unresolved cited work.

Fine-Tuning Topics through Weighting Aspect Keywords Unresolved cited work

Reference 2008

Resolution: unresolved; raw_fallback, observed 2026-08-08T04:56:14.143710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation 30dee4c8-2f74-4b29-aa95-910fde2b852b · inbound

Exploring the Technology Landscape through Topic Modeling, Expert Involvement, and Reinforcement Learning cites this paper.

Exploring the Technology Landscape through Topic Modeling, Expert Involvement, and Reinforcement Learning Fine-Tuning Topics through Weighting Aspect Keywords

Reference 232

Resolution: verified exact; local_arxiv, observed 2026-08-10T16:23:55.246225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.