Generalized vector spaces model in information retrieval
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
Translingual information retrieval: learning from bilingual corpora
Artificial Intelligence - Special issue: artificial intelligence 40 years later
The ESA retrieval model revisited
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A Wikipedia-based multilingual retrieval model
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
CLEF 2009 ad hoc track overview: TEL and Persian tasks
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
Dual-space re-ranking model for document retrieval
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Translation techniques in cross-language information retrieval
ACM Computing Surveys (CSUR)
On the connections between explicit semantic analysis and latent semantic analysis
Proceedings of the 21st ACM international conference on Information and knowledge management
Hi-index | 0.00 |
This paper describes our participation in the TEL@CLEF task of the CLEF 2009 ad-hoc track. The task is to retrieve items from various multilingual collections of library catalog records, which are relevant to a user's query. Two different strategies are employed: (i) the Cross-Language Explicit Semantic Analysis, CL-ESA, where the library catalog records and the queries are represented in a multilingual concept space that is spanned by aligned Wikipedia articles, and, (ii) a Cross Querying approach, where a query is translated into all target languages using Google Translate and where the obtained rankings are combined. The evaluation shows that both strategies outperform the monolingual baseline and achieve comparable results. Furthermore, inspired by the Generalized Vector Space Model we present a formal definition and an alternative interpretation of the CL-ESA model. This interpretation is interesting for real-world retrieval applications since it reveals how the computational effort for CL-ESA can be shifted from the query phase to a preprocessing phase.