An outline of a general model for information retrieval systems
SIGIR '88 Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using lexical-semantic relations
SIGIR '94 Proceedings of the 17th 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
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
A hidden Markov model information retrieval system
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Information retrieval as statistical translation
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Document language models, query models, and risk minimization for information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
A study of smoothing methods for language models applied to Ad Hoc information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Model-based feedback in the language modeling approach to information retrieval
Proceedings of the tenth international conference on Information and knowledge management
Towards context sensitive information inference
Journal of the American Society for Information Science and Technology - Mathematical, logical, and formal methods in information retrieval
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Chinese word segmentation and its effect on information retrieval
Information Processing and Management: an International Journal
Dependence language model for information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Learning random walk models for inducing word dependency distributions
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Linear discriminant model for information retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Integrating word relationships into language models
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using term relationships in language models for information retrieval
Proceedings of the 14th ACM international conference on Information and knowledge management
Query expansion using random walk models
Proceedings of the 14th ACM international conference on Information and knowledge management
Contextual search and name disambiguation in email using graphs
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Context-dependent term relations for information retrieval
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
An Effective Approach to Verbose Queries Using a Limited Dependencies Language Model
ICTIR '09 Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory
Search with synonyms: problems and solutions
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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Document expansion and query expansion aim to add related terms into document and query representations in order to make them more complete. However, most previous studies are limited in two respects: They use either query expansion or document expansion, but not both; expansion has been limited to directly related words. In this paper, we propose a more general approach: both document and query representations are expanded, and the expansion process also exploits indirect term relationships. The whole process is implemented through Markov chains. Our experiments show that each of these extensions brings additional improvements.