On the public citation graph

On collocations and topic models

https://doi.org/10.1145/2483969.2483972
0 signed · 90 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1007/3-540-36456-0_38openalex-snapshot
The Design, Implementation, and Use of the Ngram Statistics Package
inferredcites →https://doi.org/10.1007/bfb0026683openalex-snapshot
Text categorization with Support Vector Machines: Learning with many relevant features
inferredcites →https://doi.org/10.1007/s10579-009-9101-4openalex-snapshot
Lexical association measures and collocation extraction
inferredcites →https://doi.org/10.1017/s1351324901002728openalex-snapshot
Applied morphological processing of English
inferredcites →https://doi.org/10.1023/a:1007692713085openalex-snapshot
Text Classification from Labeled and Unlabeled Documents using EM
inferredcites →https://doi.org/10.1037/0033-295x.114.2.211openalex-snapshot
Topics in semantic representation.
inferredcites →https://doi.org/10.1109/icdm.2007.86openalex-snapshot
Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval
inferredcites →https://doi.org/10.1109/tac.1974.1100705openalex-snapshot
A new look at the statistical model identification
inferredcites →https://doi.org/10.1145/1143844.1143967openalex-snapshot
Topic modeling
inferredcites →https://doi.org/10.1145/1148170.1148204openalex-snapshot
LDA-based document models for ad-hoc retrieval
inferredcites →https://doi.org/10.1145/1367497.1367513openalex-snapshot
Modeling online reviews with multi-grain topic models
inferredcites →https://doi.org/10.1201/9781420059458.ch4openalex-snapshot
Topic Models
inferredcites →https://doi.org/10.3115/1119282.1119294openalex-snapshot
An empirical model of multiword expression decomposability
inferredcites →https://doi.org/10.3115/1219840.1219885openalex-snapshot
Incorporating non-local information into information extraction systems by Gibbs sampling
inferredcites →https://doi.org/10.3115/1599081openalex-snapshot
Proceedings of the 22nd International Conference on Computational Linguistics - COLING '08
inferredcites →https://doi.org/10.3115/1599081.1599125openalex-snapshot
Modeling Chinese documents with topical word-character models
inferredcites →https://doi.org/10.3115/1609067.1609078openalex-snapshot
Bayesian word sense induction
inferredcites →https://doi.org/10.3115/1620754openalex-snapshot
Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics on - NAACL '09
inferredcites →https://doi.org/10.5555/299094openalex-snapshot
Advances in kernel methods: support vector learning
inferredcites →https://doi.org/10.5555/944919.944937openalex-snapshot
Latent dirichlet allocation
inferredcites →https://doi.org/10.7551/mitpress/1130.003.0015openalex-snapshot
Making Large-Scale Support Vector Machine Learning Practical

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.3990436openalex-extracted
Thirty years of academic finance
inferred← citeshttps://doi.org/10.1002/cpe.7847openalex-snapshot
Microblog topic detection using evolutionary clustering and social network information
inferred← citeshttps://doi.org/10.1007/978-3-031-36190-6_5openalex-snapshot
Topic Modelling for Risk Identification in Data Protection Act Judgements
inferred← citeshttps://doi.org/10.1007/978-3-319-16354-3_71openalex-snapshot
Nonparametric Topic Modeling Using Chinese Restaurant Franchise with Buddy Customers
inferred← citeshttps://doi.org/10.1007/978-3-319-18123-3_10openalex-snapshot
MPTM: A Topic Model for Multi-Part Documents
inferred← citeshttps://doi.org/10.1007/978-3-319-64206-2_24openalex-snapshot
Adding Thesaurus Information into Probabilistic Topic Models
inferred← citeshttps://doi.org/10.1007/978-3-319-73013-4_6openalex-snapshot
Combining Thesaurus Knowledge and Probabilistic Topic Models
inferred← citeshttps://doi.org/10.1007/978-3-319-91947-8_38openalex-snapshot
Evaluating Thesaurus-Based Topic Models
inferred← citeshttps://doi.org/10.1007/978-3-642-45068-6_7openalex-snapshot
A Nonparametric N-Gram Topic Model with Interpretable Latent Topics
inferred← citeshttps://doi.org/10.1007/978-981-10-3689-7_6openalex-snapshot
Understanding-Oriented Multimedia News Summarization
inferred← citeshttps://doi.org/10.1007/s00267-023-01798-wopenalex-snapshot
Slurry Tales: Newspaper Coverage of Livestock Slurry Reproduces Public Discourse on Agriculture in Germany
inferred← citeshttps://doi.org/10.1007/s11192-019-03258-xopenalex-snapshot
Personal research idea recommendation using research trends and a hierarchical topic model
inferred← citeshttps://doi.org/10.1007/s11192-023-04672-yopenalex-snapshot
Innovation signals: leveraging machine learning to separate noise from news
inferred← citeshttps://doi.org/10.1007/s11280-020-00814-xopenalex-snapshot
A Pseudo-document-based Topical N-grams model for short texts
inferred← citeshttps://doi.org/10.1007/s44217-026-01281-8openalex-snapshot
A comprehensive investigation utilizing topic modeling to analyze research interests and trends in digital literacy
inferred← citeshttps://doi.org/10.1016/j.artint.2017.06.004openalex-snapshot
Latent tree models for hierarchical topic detection
inferred← citeshttps://doi.org/10.1016/j.eswa.2015.02.055openalex-snapshot
An analysis of the coherence of descriptors in topic modeling
inferred← citeshttps://doi.org/10.1016/j.eswa.2018.06.021openalex-snapshot
Latent association rule cluster based model to extract topics for classification and recommendation applications
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.116518openalex-snapshot
A probabilistic topic model based on short distance Co-occurrences
inferred← citeshttps://doi.org/10.1016/j.giq.2019.06.004openalex-snapshot
Open data visualizations and analytics as tools for policy-making
inferred← citeshttps://doi.org/10.1057/ejis.2016.2openalex-snapshot
Utilizing big data analytics for information systems research: challenges, promises and guidelines
inferred← citeshttps://doi.org/10.1075/cilt.341openalex-snapshot
Multiword Units in Machine Translation and Translation Technology
inferred← citeshttps://doi.org/10.1075/cilt.341.01monopenalex-snapshot
Multiword units in machine translation and translation technology
inferred← citeshttps://doi.org/10.1080/07421222.2024.2340827openalex-snapshot
Knowledge-Aware Learning Framework Based on Schema Theory to Complement Large Learning Models
inferred← citeshttps://doi.org/10.1080/09644016.2026.2673666openalex-snapshot
Democratic legitimacy in practice: stakeholder participation in the rule-making of the Paris agreement article 6.4 removal standard
inferred← citeshttps://doi.org/10.1108/mip-02-2025-0098openalex-snapshot
Value creation and destruction in telehealth services: the role of technology affordances
inferred← citeshttps://doi.org/10.1109/hicss.2015.257openalex-snapshot
Understanding Citizens' Direct Policy Suggestions to the Federal Government: A Natural Language Processing and Topic Modeling Approach
inferred← citeshttps://doi.org/10.1109/icacci.2014.6968216openalex-snapshot
Learning to rank experts using combination of multiple features of expertise
inferred← citeshttps://doi.org/10.1109/icbk.2017.39openalex-snapshot
Modeling Topic Evolution in Social Media Short Texts
inferred← citeshttps://doi.org/10.1109/ickg55886.2022.00015openalex-snapshot
Distilling Business Value from COVID - 19 Public Media Dataset with Machine Learning and Natural Language Processing
inferred← citeshttps://doi.org/10.1109/tem.2020.2989214openalex-snapshot
Artificial Intelligence in Innovation: How to Spot Emerging Trends and Technologies
inferred← citeshttps://doi.org/10.1111/joes.12571openalex-snapshot
Thirty years of academic finance
inferred← citeshttps://doi.org/10.1123/ijsc.2026-0001openalex-snapshot
Tracing a Decade of Esports Research: Insights From Topic Modeling
inferred← citeshttps://doi.org/10.1145/2822907openalex-snapshot
Multimedia News Summarization in Search
inferred← citeshttps://doi.org/10.1145/2983323.2983898openalex-snapshot
A Non-Parametric Topic Model for Short Texts Incorporating Word Coherence Knowledge
inferred← citeshttps://doi.org/10.1145/3197026.3197038openalex-snapshot
My Approach = Your Apparatus?
inferred← citeshttps://doi.org/10.1145/3227609.3227659openalex-snapshot
Thesaurus-Based Topic Models and Their Evaluation
inferred← citeshttps://doi.org/10.1145/3779153.3779181openalex-snapshot
Leveraging BERT and LDA for Semi-Supervised Augmentation of Chinese Sexism Hate Speech Datasets
inferred← citeshttps://doi.org/10.11591/ijeecs.v31.i2.pp1008-1015openalex-snapshot
Summarizing twitter posts regarding COVID-19 based on n-grams
inferred← citeshttps://doi.org/10.11606/t.55.2015.tde-02122015-161054openalex-snapshot
Extração de tópicos baseado em agrupamento de regras de associação
inferred← citeshttps://doi.org/10.1162/tacl_a_00073openalex-snapshot
Unsupervised Acquisition of Comprehensive Multiword Lexicons using Competition in an n-gram Lattice
inferred← citeshttps://doi.org/10.1177/00222429221127927openalex-snapshot
Does Topic Consistency Matter? A Study of Critic and User Reviews in the Movie Industry
inferred← citeshttps://doi.org/10.15187/adr.2026.05.39.2.37openalex-snapshot
A Data-Driven Structured Prompt Framework for AI-Assisted Cultural Tourism Souvenir Design
inferred← citeshttps://doi.org/10.18653/v1/2022.findings-acl.212openalex-snapshot
More Than Words: Collocation Retokenization for Latent Dirichlet Allocation Models
inferred← citeshttps://doi.org/10.18653/v1/p17-1134openalex-snapshot
Unsupervised Text Segmentation Based on Native Language Characteristics
inferred← citeshttps://doi.org/10.18653/v1/p17-1165openalex-snapshot
Topical Coherence in LDA-based Models through Induced Segmentation
inferred← citeshttps://doi.org/10.18653/v1/p18-2040openalex-snapshot
Improving Topic Quality by Promoting Named Entities in Topic Modeling
inferred← citeshttps://doi.org/10.18653/v1/w16-18openalex-snapshot
Proceedings of the 12th Workshop on Multiword Expressions
inferred← citeshttps://doi.org/10.18653/v1/w16-1806openalex-snapshot
Accounting ngrams and multi-word terms can improve topic models
inferred← citeshttps://doi.org/10.2196/24236openalex-snapshot
Understanding Barriers to Novel Data Linkages: Topic Modeling of the Results of the LifeInfo Survey
inferred← citeshttps://doi.org/10.24251/hicss.2022.368openalex-snapshot
Social Media Mining in Drug Development Decision Making: Prioritizing Multiple Sclerosis Patients’ Unmet Medical Needs
inferred← citeshttps://doi.org/10.26089/nummet.v16r222openalex-snapshot
Topic models: adding bigrams and taking account of the similarity between unigrams and bigrams
inferred← citeshttps://doi.org/10.3115/v1/e14-1056openalex-snapshot
Machine Reading Tea Leaves: Automatically Evaluating Topic Coherence and Topic Model Quality
inferred← citeshttps://doi.org/10.3115/v1/p15-1141openalex-snapshot
A Computationally Efficient Algorithm for Learning Topical Collocation Models
inferred← citeshttps://doi.org/10.3115/v1/w15-09openalex-snapshot
Proceedings of the 11th Workshop on Multiword Expressions
inferred← citeshttps://doi.org/10.3115/v1/w15-0901openalex-snapshot
A Method of Accounting Bigrams in Topic Models
inferred← citeshttps://doi.org/10.31234/osf.io/dtakjopenalex-snapshot
Differential Diagnosis of Borderline Personality Disorder: Machine Learning Models of Subjective Experiences
inferred← citeshttps://doi.org/10.32920/24156462openalex-snapshot
A Triple Bottom Line Analysis of Sustainability Trends in the Luxury Fashion Industry: A Topic Modeling Approach
inferred← citeshttps://doi.org/10.32920/24156462.v1openalex-snapshot
A Triple Bottom Line Analysis of Sustainability Trends in the Luxury Fashion Industry: A Topic Modeling Approach
inferred← citeshttps://doi.org/10.3389/frai.2021.664737openalex-snapshot
Gender Bias in the News: A Scalable Topic Modelling and Visualization Framework
inferred← citeshttps://doi.org/10.3390/app12020814openalex-snapshot
Clustering Application for Condition-Based Maintenance in Time-Varying Processes: A Review Using Latent Dirichlet Allocation
inferred← citeshttps://doi.org/10.35566/jbds/v1n1/p1openalex-snapshot
What is Data Science? An Operational Definition based on Text Mining of Data Science Curricula
inferred← citeshttps://doi.org/10.4108/eai.13-7-2018.163131openalex-snapshot
Semantic N-Gram Topic Modeling
inferred← citeshttps://doi.org/10.48550/arxiv.1601.03313openalex-snapshot
Political Speech Generation
inferred← citeshttps://doi.org/10.48550/arxiv.1707.09816openalex-snapshot
Combining Thesaurus Knowledge and Probabilistic Topic Models
inferred← citeshttps://doi.org/10.48550/arxiv.1911.11240openalex-snapshot
My Approach = Your Apparatus? Entropy-Based Topic Modeling on Multiple Domain-Specific Text Collections
inferred← citeshttps://doi.org/10.48550/arxiv.2007.05163openalex-snapshot
Handling Collocations in Hierarchical Latent Tree Analysis for Topic Modeling
inferred← citeshttps://doi.org/10.48550/arxiv.2111.15278openalex-snapshot
Bilingual Topic Models for Comparable Corpora
inferred← citeshttps://doi.org/10.58837/chula.is.2021.103openalex-snapshot
Collocation-based retokenization methods for latent dirichlet allocation topic models
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.