Modeling score distributions for combining the outputs of search engines
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Two-stage language models for information retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Summarizing scientific articles: experiments with relevance and rhetorical status
Computational Linguistics - Summarization
Language Modeling for Information Retrieval
Language Modeling for Information Retrieval
Experiments in discourse analysis impact on information classification and retrieval algorithms
Information Processing and Management: an International Journal
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Retrieval evaluation with incomplete information
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Sentence level discourse parsing using syntactic and lexical information
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Automatic labeling of semantic roles
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Discourse processing for context question answering based on linguistic knowledge
Knowledge-Based Systems
Psychiatric document retrieval using a discourse-aware model
Artificial Intelligence
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
A novel discourse parser based on support vector machine classification
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
On statistical analysis and optimization of information retrieval effectiveness metrics
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Quality-biased ranking of web documents
Proceedings of the fourth ACM international conference on Web search and data mining
Discourse indicators for content selection in summarization
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Discourse constraints for document compression
Computational Linguistics
Polarity analysis of texts using discourse structure
Proceedings of the 20th ACM international conference on Information and knowledge management
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
Predicting thread discourse structure over technical web forums
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Unsupervised discovery of discourse relations for eliminating intra-sentence polarity ambiguities
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
An information retrieval approach based on discourse type
NLDB'06 Proceedings of the 11th international conference on Applications of Natural Language to Information Systems
Semantic concept-enriched dependence model for medical information retrieval
Journal of Biomedical Informatics
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Typically, every part in most coherent text has some plausible reason for its presence, some function that it performs to the overall semantics of the text. Rhetorical relations, e.g. contrast, cause, explanation, describe how the parts of a text are linked to each other. Knowledge about this so-called discourse structure has been applied successfully to several natural language processing tasks. This work studies the use of rhetorical relations for Information Retrieval (IR): Is there a correlation between certain rhetorical relations and retrieval performance? Can knowledge about a document's rhetorical relations be useful to IR? We present a language model modification that considers rhetorical relations when estimating the relevance of a document to a query. Empirical evaluation of different versions of our model on TREC settings shows that certain rhetorical relations can benefit retrieval effectiveness notably (10% in mean average precision over a state-of-the-art baseline).