A maximum entropy approach to natural language processing
Computational Linguistics
Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
The maximum entropy principle in information retrieval
Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Overview of the sixth text REtrieval conference (TREC-6)
Information Processing and Management: an International Journal - The sixth text REtrieval conference (TREC-6)
The maximum entropy approach and probabilistic IR models
ACM Transactions on Information Systems (TOIS)
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Polyphonic music modeling with random fields
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
Discriminative models for information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A Markov random field model for term dependencies
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Collective multi-label classification
Proceedings of the 14th ACM international conference on Information and knowledge management
Interpreting TF-IDF term weights as making relevance decisions
ACM Transactions on Information Systems (TOIS)
Improving biomedical document retrieval using domain knowledge
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Contextual proximity based term-weighting for improved web information retrieval
KSEM'07 Proceedings of the 2nd international conference on Knowledge science, engineering and management
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Sentence-level contextual opinion retrieval
Proceedings of the 20th international conference companion on World wide web
Computational Intelligence
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At their heart, most if not all information retrieval models utilize some form of term frequency.The notion is that the more often a query term occurs in a document, the more likely it is that document meets an information need. We examine an alternative. We propose a model which assesses the presence of a term in a document not by looking at the actual occurrence of that term, but by a set of non-independent supporting terms, i.e. context. This yields a weighting for terms in documents which is different from and complementary to tf-based methods, and is beneficial for retrieval.