Probabilistic latent semantic analysis

Authors:
Thomas Hofmann
Affiliations:
EECS Department, Computer Science Division, University of California, Berkeley & International Computer Science Institute, Berkeley, CA
Venue:
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Year:
1999

Citing 7
Cited 313

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ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
A topic similarity model for hierarchical phrase-based translation

ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
SSHLDA: a semi-supervised hierarchical topic model

EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Intelligent multi-camera video surveillance: A review

Pattern Recognition Letters
Hierarchical topic integration through semi-supervised hierarchical topic modeling

Proceedings of the 21st ACM international conference on Information and knowledge management
User activity profiling with multi-layer analysis

Proceedings of the 21st ACM international conference on Information and knowledge management
Author-conference topic-connection model for academic network search

Proceedings of the 21st ACM international conference on Information and knowledge management
Reorder user's tweets

ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
PENETRATE: Personalized news recommendation using ensemble hierarchical clustering

Expert Systems with Applications: An International Journal
Representations for multi-document event clustering

Data Mining and Knowledge Discovery
Topic model for analyzing purchase data with price information

Data Mining and Knowledge Discovery
Geo topic model: joint modeling of user's activity area and interests for location recommendation

Proceedings of the sixth ACM international conference on Web search and data mining
Unsupervised graph-based topic labelling using dbpedia

Proceedings of the sixth ACM international conference on Web search and data mining
Connecting comments and tags: improved modeling of social tagging systems

Proceedings of the sixth ACM international conference on Web search and data mining
Continuous improvement of knowledge management systems using Six Sigma methodology

Robotics and Computer-Integrated Manufacturing
Knowledge kanban system for virtual research and development

Robotics and Computer-Integrated Manufacturing
Towards a Possibilistic Information Retrieval System Using Semantic Query Expansion

International Journal of Intelligent Information Technologies
Transforming graph data for statistical relational learning

Journal of Artificial Intelligence Research
Clustering tagged documents with labeled and unlabeled documents

Information Processing and Management: an International Journal
Dynamic scene understanding by improved sparse topical coding

Pattern Recognition
User Features and Social Networks for Topic Modeling in Online Social Media

ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
An efficient approach to suggesting topically related web queries using hidden topic model

World Wide Web
Rhetorics-based multi-document summarization

Expert Systems with Applications: An International Journal
Clustering documents with labeled and unlabeled documents using fuzzy semi-Kmeans

Fuzzy Sets and Systems
High order pLSA for indexing tagged images

Signal Processing
Co-regularized PLSA for multi-view clustering

ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Exploiting relevance, coverage, and novelty for query-focused multi-document summarization

Knowledge-Based Systems
Enhancing short text clustering with small external repositories

AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
Boosting novelty for biomedical information retrieval through probabilistic latent semantic analysis

Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Sparse online topic models

Proceedings of the 22nd international conference on World Wide Web
A Diagnostic Study of Search Result Diversification Methods

Proceedings of the 2013 Conference on the Theory of Information Retrieval
Rapid speaker adaptation in latent speaker space with non-negative matrix factorization

Speech Communication
Beyond bag of words: image representation in sub-semantic space

Proceedings of the 21st ACM international conference on Multimedia
Riding the tide of sentiment change: sentiment analysis with evolving online reviews

World Wide Web
Discovering coherent topics using general knowledge

Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
On handling textual errors in latent document modeling

Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Indoor scene recognition by a mobile robot through adaptive object detection

Robotics and Autonomous Systems
Spatial topic modeling in online social media for location recommendation

Proceedings of the 7th ACM conference on Recommender systems
Query-driven context aware recommendation

Proceedings of the 7th ACM conference on Recommender systems
Topic modelling of clickthrough data in image search

Multimedia Tools and Applications
Robust probabilistic tensor analysis for time-variant collaborative filtering

Neurocomputing
TopicDSDR: combining topic decomposition and data reconstruction for summarization

WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
Modeling semantic aspects of gaze behavior while catalog browsing

Proceedings of the 15th ACM on International conference on multimodal interaction
Concept learning for cross-domain text classification: a general probabilistic framework

IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
A survey of music similarity and recommendation from music context data

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Learning mixtures of arbitrary distributions over large discrete domains

Proceedings of the 5th conference on Innovations in theoretical computer science
Detecting non-gaussian geographical topics in tagged photo collections

Proceedings of the 7th ACM international conference on Web search and data mining
Application of non-negative spectrogram decomposition with sparsity constraints to single-channel speech enhancement

Speech Communication
The dual-sparse topic model: mining focused topics and focused terms in short text

Proceedings of the 23rd international conference on World wide web
A probabilistic approach to mining mobile phone data sequences

Personal and Ubiquitous Computing
Improved Semantic Retrieval of Spoken Content by Document/Query Expansion with Random Walk Over Acoustic Similarity Graphs

IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
CooL-AgentSpeak: Endowing AgentSpeak-DL agents with plan exchange and ontology services

Web Intelligence and Agent Systems
Robust estimation of a global Gaussian mixture by decentralized aggregations of local models

Web Intelligence and Agent Systems
Rectifying the representation learned by Non-negative Matrix Factorization

International Journal of Knowledge-based and Intelligent Engineering Systems
Activity-based topic discovery

Web Intelligence and Agent Systems
Novel document detection for massive data streams using distributed dictionary learning

IBM Journal of Research and Development

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Abstract

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.