Titlebook: Information Retrieval Technology; Third Asia Informati Hwee Tou Ng,Mun-Kew Leong,Donghong Ji Conference proceedings 2006 Springer-Verlag Be

sulcus

Chinese Question-Answering: Comparing Monolingual with English-Chinese Cross-Lingual Resultso English-Chinese cross language QA with three different forms of English-Chinese question translation, it attains top-1 accuracy and MRR of .155, .2094 (supported) and .215, .2932 (unsupported), about ~52% to ~62% of monolingual effectiveness. CLQA improvements via successively different forms of question translation are also demonstrated.

COM

沙文主义

Musket

A Supervised Learning Approach to Entity Searcheful for ranking in entity search. We propose using a linear model to combine the uses of different features and employing a supervised learning approach in training of the model. Experimental results on several data sets indicate that our method significantly outperforms the baseline method based solely on co-occurrences.

武器

Toward Generic Title Generation for Clustered Documentss anticipated. Real-case applications of these generic terms show promising in assisting humans in interpreting the clustered topics. Our method is general enough such that it can be easily extended to use other hierarchical resources for adaptable label generation.

情爱

Statistical Behavior Analysis of Smoothing Methods for Language Models of Mandarin Data Setsbehaviors of three smoothing methods are proposed. Our proposed smoothing methods comply with all the properties. We implement three language models in Mandarin data sets and then discuss the entropy. In general, the entropies of proposed smoothing method for three models are lower than that of other two methods.

入伍仪式

Conference proceedings 2006na, and the 2nd AIRS was held in Cheju, Korea. The AIRS conference series traces its roots to the successful Information Retrieval with Asian Languages (IRAL) workshop series which started in 1996. The AIRS series aims to bring together international researchers and dev- opers to exchange new ideas

AGGER

Hierarchical Learning Strategy in Relation Extraction Using Support Vector Machinesroach using the hierarchical learning strategy. Evaluation on the ACE RDC 2003 and 2004 corpora shows that the hierarchical learning strategy much improves the performance on least- and medium- frequent relations.

adjacent

Using Relative Entropy for Authorship Attributionoach is as effective as the best existing attribution methods for two class attribution, and is superior for multi-class attribution. It has lower computational cost and is cheaper to train. Finally, our results suggest this approach is a promising alternative for other categorization problems.

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