On the public citation graph

Subject metadata enrichment using statistical topic models

0 signed · 48 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/(sici)1097-4571(199009)41:6<391::aid-asi1>3.0.co;2-9openalex-snapshot

Indexing by latent semantic analysis

inferredcites →https://doi.org/10.1002/asi.v57:6openalex-snapshot

inferredcites →https://doi.org/10.1007/11760146_9openalex-snapshot

Analyzing Entities and Topics in News Articles Using Statistical Topic Models

inferredcites →https://doi.org/10.1023/a:1007612920971openalex-snapshot

Concept Decompositions for Large Sparse Text Data Using Clustering

inferredcites →https://doi.org/10.1023/a:1007617005950openalex-snapshot

Unsupervised Learning by Probabilistic Latent Semantic Analysis

inferredcites →https://doi.org/10.1038/44565openalex-snapshot

Learning the parts of objects by non-negative matrix factorization

inferredcites →https://doi.org/10.1073/pnas.0307752101openalex-snapshot

Finding scientific topics

inferredcites →https://doi.org/10.1109/wi.2004.12openalex-snapshot

A Scalable Topic-Based Open Source Search Engine

inferredcites →https://doi.org/10.1145/1065385.1065442openalex-snapshot

An initial evaluation of automated organization for digital library browsing

inferredcites →https://doi.org/10.1145/1141753.1141765openalex-snapshot

Bibliometric impact measures leveraging topic analysis

inferredcites →https://doi.org/10.1145/1143844.1143917openalex-snapshot

Pachinko allocation

inferredcites →https://doi.org/10.5555/944919.944937openalex-snapshot

Latent dirichlet allocation

inferredcites →https://doi.org/10.7551/mitpress/7503.003.0035openalex-snapshot

Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.3171739openalex-extracted

Viscovery: Trend Tracking in Opinion Forums based on Dynamic Topic Models

inferred← citeshttps://doi.org/10.2139/ssrn.3199465openalex-extracted

inferred← citeshttps://doi.org/10.1007/978-3-319-13674-5_23openalex-snapshot

A Framework for the Evaluation of Automatic Metadata Enrichments

inferred← citeshttps://doi.org/10.1007/978-3-319-24129-6_9openalex-snapshot

Discovering the Topical Evolution of the Digital Library Evaluation Community

inferred← citeshttps://doi.org/10.1007/978-3-642-23160-5_7openalex-snapshot

Metadata Enrichment via Topic Models for Author Name Disambiguation

inferred← citeshttps://doi.org/10.1007/s00799-015-0146-2openalex-snapshot

A generalized topic modeling approach for automatic document annotation

inferred← citeshttps://doi.org/10.1007/s00799-017-0222-xopenalex-snapshot

Discovering the structure and impact of the digital library evaluation domain

inferred← citeshttps://doi.org/10.1007/s00799-021-00302-1openalex-snapshot

Automatically evaluating the quality of textual descriptions in cultural heritage records

inferred← citeshttps://doi.org/10.1007/s00799-025-00429-5openalex-snapshot

Toward purpose-oriented topic model evaluation enabled by large language models

inferred← citeshttps://doi.org/10.1007/s41060-024-00583-0openalex-snapshot

Temporal analysis of topic modeling output by machine learning techniques

inferred← citeshttps://doi.org/10.1016/j.ipm.2017.01.003openalex-snapshot

Vocabulary size and its effect on topic representation

inferred← citeshttps://doi.org/10.1016/j.jvcir.2008.11.007openalex-snapshot

Latent Style Model: Discovering writing styles for calligraphy works

inferred← citeshttps://doi.org/10.1016/j.poetic.2013.10.001openalex-snapshot

Introduction—Topic models: What they are and why they matter

inferred← citeshttps://doi.org/10.1016/j.websem.2009.12.001openalex-snapshot

Leveraging personal metadata for Desktop search: The Beagle++ system

inferred← citeshttps://doi.org/10.1045/july2007-hagedornopenalex-snapshot

Enhancing Search and Browse Using Automated Clustering of Subject Metadata

inferred← citeshttps://doi.org/10.1108/07378830911007646openalex-snapshot

Enhancing document modeling by means of open topic models

inferred← citeshttps://doi.org/10.1108/10650751011087639openalex-snapshot

“Sense of place” in digital collections

inferred← citeshttps://doi.org/10.1108/jd-07-2014-0103openalex-snapshot

Augmenting Dublin Core digital library metadata with Dewey Decimal Classification

inferred← citeshttps://doi.org/10.1109/bigdata.2018.8622487openalex-snapshot

Measuring completeness as metadata quality metric in Europeana

inferred← citeshttps://doi.org/10.1109/ubicomm.2007.42openalex-snapshot

Advanced Semantic Management of Digital Resources

inferred← citeshttps://doi.org/10.1109/ubicomm.2007.6openalex-snapshot

Visualization of Large Schemaless RDF Data

inferred← citeshttps://doi.org/10.1142/s0218001411008890openalex-snapshot

A WORD POSITION-RELATED LDA MODEL

inferred← citeshttps://doi.org/10.1145/1401890.1401960openalex-snapshot

Fast collapsed gibbs sampling for latent dirichlet allocation

inferred← citeshttps://doi.org/10.1145/1555400.1555405openalex-snapshot

Topic model methods for automatically identifying out-of-scope resources

inferred← citeshttps://doi.org/10.1145/1816123.1816156openalex-snapshot

Evaluating topic models for digital libraries

inferred← citeshttps://doi.org/10.1145/1998076.1998160openalex-snapshot

Are learned topics more useful than subject headings

inferred← citeshttps://doi.org/10.1145/2037715.2037816openalex-snapshot

Using statistical topic models to organize and visualize large-scale architectural image databases

inferred← citeshttps://doi.org/10.1145/2467696.2467706openalex-snapshot

Automatic tag recommendation for metadata annotation using probabilistic topic modeling

inferred← citeshttps://doi.org/10.1371/journal.pone.0236863openalex-snapshot

Microblog topic identification using Linked Open Data

inferred← citeshttps://doi.org/10.18438/eblip29514openalex-snapshot

First-Year Students and the Framework: Using Topic Modeling to Analyze Student Understanding of the Framework for Information Literacy for Higher Education

inferred← citeshttps://doi.org/10.2390/biecoll-or2010-79openalex-snapshot

Building a DDC Annotated Corpus from OAI Metadata

inferred← citeshttps://doi.org/10.3115/1621829.1621835openalex-snapshot

Latent Dirichlet Allocation with topic-in-set knowledge

inferred← citeshttps://doi.org/10.3390/ijgi11020087openalex-snapshot

Approaches for the Clustering of Geographic Metadata and the Automatic Detection of Quasi-Spatial Dataset Series

inferred← citeshttps://doi.org/10.5117/9789053564127openalex-snapshot

Investigative study of standards for Digital Repositories and related services

inferred← citeshttps://doi.org/10.6017/ital.v41i2.13799openalex-snapshot

Applying Topic Modeling for Automated Creation of Descriptive Metadata for Digital Collections

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.