Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
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Mathematical Programming: Series A and B
Elements of information theory
Elements of information theory
An example-based mapping method for text categorization and retrieval
ACM Transactions on Information Systems (TOIS)
A maximum entropy approach to natural language processing
Computational Linguistics
Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
Unsupervised Learning of Finite Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Text Categorization Based on Regularized Linear Classification Methods
Information Retrieval
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Video Retrieval by Feature Learning in Key Frames
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Experimental result analysis for a generative probabilistic image retrieval model
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
An extensive empirical study of feature selection metrics for text classification
The Journal of Machine Learning Research
Formulating Semantic Image Annotation as a Supervised Learning Problem
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A Maximum Entropy Framework for Part-Based Texture and Object Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
A comparison of algorithms for maximum entropy parameter estimation
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
The Semantic Pathfinder: Using an Authoring Metaphor for Generic Multimedia Indexing
IEEE Transactions on Pattern Analysis and Machine Intelligence
High-dimensional visual vocabularies for image retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Multiple Bernoulli relevance models for image and video annotation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Automated image annotation using global features and robust nonparametric density estimation
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Logistic regression of generic codebooks for semantic image retrieval
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
A probabilistic framework for semantic video indexing, filtering,and retrieval
IEEE Transactions on Multimedia
Image classification for content-based indexing
IEEE Transactions on Image Processing
Enhancing enterprise knowledge processes via cross-media extraction
Proceedings of the 4th international conference on Knowledge capture
Exploring multimedia in a keyword space
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Multimedia Evidence Fusion for Video Concept Detection via OWA Operator
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
Bayesian Mixture Hierarchies for Automatic Image Annotation
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Foundations and Trends in Information Retrieval
Unified video annotation via multigraph learning
IEEE Transactions on Circuits and Systems for Video Technology
Web news categorization using a cross-media document graph
Proceedings of the ACM International Conference on Image and Video Retrieval
Topic models for semantics-preserving video compression
Proceedings of the international conference on Multimedia information retrieval
Modeling, classifying and annotating weakly annotated images using Bayesian network
Journal of Visual Communication and Image Representation
Image retrieval using Markov Random Fields and global image features
Proceedings of the ACM International Conference on Image and Video Retrieval
An information-theoretic framework for semantic-multimedia retrieval
ACM Transactions on Information Systems (TOIS)
Using manual and automated annotations to search images by semantic similarity
Multimedia Tools and Applications
High order pLSA for indexing tagged images
Signal Processing
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To solve the problem of indexing collections with diverse text documents, image documents, or documents with both text and images, one needs to develop a model that supports heterogeneous types of documents. In this paper, we show how information theory supplies us with the tools necessary to develop a unique model for text, image, and text/image retrieval. In our approach, for each possible query keyword we estimate a maximum entropy model based on exclusively continuous features that were preprocessed. The unique continuous feature-space of text and visual data is constructed by using a minimum description length criterion to find the optimal feature-space representation (optimal from an information theory point of view). We evaluate our approach in three experiments: only text retrieval, only image retrieval, and text combined with image retrieval.