A Cache-Based Natural Language Model for Speech Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computing iceberg concept lattices with TITANIC
Data & Knowledge Engineering
Discovering Frequent Closed Itemsets for Association Rules
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Selection criteria for word trigger pairs in language modelling
ICG! '96 Proceedings of the 3rd International Colloquium on Grammatical Inference: Learning Syntax from Sentences
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Term Similarity-Based Query Expansion for Cross-Language Information Retrieval
ECDL '99 Proceedings of the Third European Conference on Research and Advanced Technology for Digital Libraries
Mining Minimal Non-redundant Association Rules Using Frequent Closed Itemsets
CL '00 Proceedings of the First International Conference on Computational Logic
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Mining Non-Redundant Association Rules
Data Mining and Knowledge Discovery
Lexical triggers and latent semantic analysis for cross-lingual language model adaptation
ACM Transactions on Asian Language Information Processing (TALIP)
Generating a Condensed Representation for Association Rules
Journal of Intelligent Information Systems
Relative risk and odds ratio: a data mining perspective
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Improved statistical alignment models
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
Redundant association rules reduction techniques
International Journal of Business Intelligence and Data Mining
A new generic basis of "factual" and "implicative" association rules
Intelligent Data Analysis
Prince: an algorithm for generating rule bases without closure computations
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
Proxemic conceptual network based on ontology enrichment for representing documents in IR
EKAW'12 Proceedings of the 18th international conference on Knowledge Engineering and Knowledge Management
Key roles of closed sets and minimal generators in concise representations of frequent patterns
Intelligent Data Analysis
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In this paper, we describe two new methods of mining monolingual and bilingual text corpora that heavily rely on the use of association rules and triggers. The association rules based method is firstly applied in query expansion. The conducted experiments on French newspapers and on a set of scientific documents show that the proposed approach outperforms the baseline model. The second method focuses on the machine translation and is motivated by the results of triggers on statistical language modeling. In order to build up a translation table, association rules and triggers are then generalized to mine bilingual corpora. In this respect, we propose respectively the concepts of inter-lingual association rules and inter-lingual triggers. Both methods have been integrated in a real statistical machine translation. Carried out experiments highlight the practical feasibility of the introduced approaches in the context of machine translation and show that inter-lingual triggers achieve better results than those obtained using the third IBM model.