A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Classification of HTML Documents by Hidden Tree-Markov Models
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Simple Estimators for Relational Bayesian Classifiers
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Learning relational probability trees
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Bayesian network model for semi-structured document classification
Information Processing and Management: an International Journal - Special issue: Bayesian networks and information retrieval
Multi-labelled classification using maximum entropy method
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Kernel-Based Learning of Hierarchical Multilabel Classification Models
The Journal of Machine Learning Research
Learning probabilistic relational models
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Probabilistic classification and clustering in relational data
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Discriminative probabilistic models for relational data
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Predicting social-tags for cold start book recommendations
Proceedings of the third ACM conference on Recommender systems
| Hi-index | 0.00 |
We explore the problem of discovering multiple missing values in a semi-structured database. For this task, we formally develop Structured Relevance Model (SRM) built on one hypothetical generative model for semi-structured records. SRM is based on the idea that plausible values for a given field could be inferred from the context provided by the other fields in the record. Small-scale experiments on IMDb (Internet Movie Database) show that SRM matched three state-of-the-art relational learning approaches on the movie label prediction tasks. Large-scale experiments on a snapshot of the National Science Digital Library (NSDL) repository show that SRM is highly effective at discovering possible values for free-text fields even with quite modest amounts of training data, compared with state-of-the-art machine learning approaches.