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Probabilistic Latent Semantic Analysis

arXiv 1301.6705 ↗First posted 23 Jan 2013cs.LG cs.IR stat.MLcited by 63

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Abstract (arXiv)

Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of two-mode and co-occurrence data, which has applications in information retrieval and filtering, natural language processing, machine learning from text, and in related areas. Compared to standard Latent Semantic Analysis which stems from linear algebra and performs a Singular Value Decomposition of co-occurrence tables, the proposed method is based on a mixture decomposition derived from a latent class model. This results in a more principled approach which has a solid foundation in statistics. In order to avoid overfitting, we propose a widely applicable generalization of maximum likelihood model fitting by tempered EM. Our approach yields substantial and consistent improvements over Latent Semantic Analysis in a number of experiments.

Key facts. Cited by 63 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Jan 2013.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 13; 2022: 13; 2023: 11; 2024: 7; 2025: 14; 2026: 5.

63 papers.

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  1. 2022A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directionscited by 73
  2. 2023Effective Neural Topic Modeling with Embedding Clustering Regularizationcited by 46
  3. 2022Mitigating Data Sparsity for Short Text Topic Modeling by Topic-Semantic Contrastive Learningcited by 38
  4. 2024FASTopic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic Modelcited by 34
  5. 2021Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networkscited by 32
  6. 2023Prompting Large Language Models for Topic Modelingcited by 24
  7. 2021PEEK: A Large Dataset of Learner Engagement with Educational Videoscited by 9
  8. 2022Flexible and Hierarchical Prior for Bayesian Nonnegative Matrix Factorizationcited by 7
  9. 2022Persona-Based Conversational AI: State of the Art and Challengescited by 6
  10. 2021Few-shot Learning for Topic Modelingcited by 5
  11. 2021Learning Mathematical Properties of Integerscited by 4
  12. 2024GINopic: Topic Modeling with Graph Isomorphism Networkcited by 4
38 more
  1. 2024Provable unlearning in topic modeling and downstream taskscited by 4
  2. 2025Comparative Analysis of Topic Modeling Techniques on ATSB Text Narratives Using Natural Language Processingcited by 4
  3. 2025A Distributional Perspective on Word Learning in Neural Language Modelscited by 4
  4. 2022Efficient Algorithms for Sparse Moment Problems without Separationcited by 3
  5. 2022Topic Modeling on Clinical Social Work Notes for Exploring Social Determinants of Health Factorscited by 3
  6. 2024Determination of the Number of Topics Intrinsically: Is It Possible?cited by 3
  7. 2025BERTopic for Topic Modeling of Hindi Short Texts: A Comparative Studycited by 3
  8. 2021Bayesian Transfer Learning: An Overview of Probabilistic Graphical Models for Transfer Learningcited by 2
  9. 2021Learning Topic Models: Identifiability and Finite-Sample Analysiscited by 2
  10. 2021Word embeddings for topic modeling: an application to the estimation of the economic policy uncertainty indexcited by 2
  11. 2021TopNet: Learning from Neural Topic Model to Generate Long Storiescited by 2
  12. 2023Embeddings for Tabular Data: A Surveycited by 2
  13. 2023Persona-Coded Poly-Encoder: Persona-Guided Multi-Stream Conversational Sentence Scoringcited by 2
  14. 2025Large Language Models Struggle to Describe the Haystack without Human Help: Human-in-the-loop Evaluation of Topic Modelscited by 2
  15. 2025Hybrid-Hierarchical Fashion Graph Attention Network for Compatibility-Oriented and Personalized Outfit Recommendationcited by 2
  16. 2021AI supported Topic Modeling using KNIME-Workflowscited by 1
  17. 2021Topic Model Robustness to Automatic Speech Recognition Errors in Podcast Transcriptscited by 1
  18. 2021Topic Analysis of Superconductivity Literature by Semantic Non-negative Matrix Factorizationcited by 1
  19. 2022Short Text Topic Modeling: Application to tweets about Bitcoincited by 1
  20. 2022A majorization-minimization algorithm for nonnegative binary matrix factorizationcited by 1
  21. 2022SimLDA: A tool for topic model evaluationcited by 1
  22. 2022Robust Bayesian Nonnegative Matrix Factorization with Implicit Regularizerscited by 1
  23. 2023Topics in Contextualised Attention Embeddingscited by 1
  24. 2023The Deep Latent Position Topic Model for Clustering and Representation of Networks with Textual Edgescited by 1
  25. 2023From Fake to Hyperpartisan News Detection Using Domain Adaptationcited by 1
  26. 2024Inferring Discussion Topics about Exploitation of Vulnerabilities from Underground Hacking Forumscited by 1
  27. 2025Investigating Thematic Patterns and User Preferences in LLM Interactions using BERTopiccited by 1
  28. 2021Clustering Introductory Computer Science Exercises Using Topic Modeling Methodscited by 0
  29. 2021Teaching a Massive Open Online Course on Natural Language Processingcited by 0
  30. 2022Generating Tips from Song Reviews: A New Dataset and Frameworkcited by 0
  31. 2022CSSAM:Code Search via Attention Matching of Code Semantics and Structurescited by 0
  32. 2022Multimodal Query-guided Object Localizationcited by 0
  33. 2023Utilizing Social Media Attributes for Enhanced Keyword Detection: An IDF-LDA Model Applied to Sina Weibocited by 0
  34. 2023Decoding the Alphabet Soup of Degrees in the United States Postsecondary Education System Through Hybrid Method: Database and Text Miningcited by 0
  35. 2023Multi-State Brain Network Discoverycited by 0
  36. 2023Temporal Sequencing of Documentscited by 0
  37. 2024Iterative Improvement of an Additively Regularized Topic Modelcited by 0
  38. 2024fLSA: Learning Semantic Structures in Document Collections Using Foundation Modelscited by 0

50 most cited of 63 All 63 (JSON)