Phrasal translation and query expansion techniques for cross-language information retrieval
Proceedings of the 20th 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
Probabilistic latent semantic indexing
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
Evaluating a probabilistic model for cross-lingual 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
Cross-lingual relevance models
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Disambiguation Strategies for Cross-Language Information Retrieval
ECDL '99 Proceedings of the Third European Conference on Research and Advanced Technology for Digital Libraries
A systematic comparison of various statistical alignment models
Computational Linguistics
The Journal of Machine Learning Research
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
LDA-based document models for ad-hoc retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Combining bidirectional translation and synonymy for cross-language information retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
A Comparative Study of Utilizing Topic Models for Information Retrieval
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Cross-language linking of news stories on the web using interlingual topic modelling
Proceedings of the 2nd ACM workshop on Social web search and mining
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Multilingual topic models for unaligned text
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Cross-lingual latent topic extraction
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Cross lingual text classification by mining multilingual topics from wikipedia
Proceedings of the fourth ACM international conference on Web search and data mining
Identifying word translations from comparable corpora using latent topic models
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Extracting multilingual topics from unaligned comparable corpora
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing
Multilingual probabilistic topic modeling and its applications in web mining and search
Proceedings of the 7th ACM international conference on Web search and data mining
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We explore the potential of probabilistic topic modeling within the relevance modeling framework for both monolingual and cross-lingual ad-hoc retrieval. Multilingual topic models provide a way to represent documents in a structured and coherent way, regardless of their actual language, by means of language-independent concepts, that is, cross-lingual topics. We show how to integrate the topical knowledge into a unified relevance modeling framework in order to build quality retrieval models in monolingual and cross-lingual contexts. The proposed modeling framework processes all documents uniformly and does not make any conceptual distinction between monolingual and cross-lingual modeling. Our results obtained from the experiments conducted on the standard CLEF test collections reveal that fusing the topical knowledge and relevance modeling leads to building monolingual and cross-lingual retrieval models that outperform several strong baselines. We show that that the topical knowledge coming from a general Web-generated corpus boosts retrieval scores. Additionally, we show that within this framework the estimation of cross-lingual relevance models may be performed by exploiting only a general non-parallel corpus.