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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 21 – 31 of 31 21 Opinion and Polarity Detection within Far-East Languages in NTCIR-7 Olena Zubaryeva; Jacques Savoy In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings7/pdf/NTCIR7/C2/MOAT/21-NTCIR7-MOAT-ZubaryevaO.pdf BASE Show details 22 Report on CLEF-2002 experiments: Combining multiple sources of evidence Jacques Savoy In: https://doc.rero.ch/record/17185/files/Savoy_Jacques_-_Report_on_CLEF_2002_Experiments_Combining_20100210.pdf BASE Show details 23 Searching Strategies for the Bulgarian Language Jacques Savoy In: http://members.unine.ch/jacques.savoy/Papers/BUIR.pdf BASE Show details 24 Selecting Automatically the Best Query Translations Pierre-yves Berger; Jacques Savoy In: http://riao.free.fr/papers/11.pdf BASE Show details 25 Monolingual, Bilingual, and GIRT Information Retrieval at CLEF-2005 Jacques Savoy; Pierre-yves Berger In: http://members.unine.ch/jacques.savoy/Papers/CLEF2005WP.pdf BASE Show details 26 UniNE at CLEF 2012 Mitra Akasereh; Nada Naji; Jacques Savoy In: http://www.clef-initiative.eu/documents/71612/901619ab-eeeb-46ad-9188-933ed11a1641/ BASE Show details 27 Abstract Cross-Language Information Retrieval: Experiments Based on CLEF 2000 Corpora Jacques Savoy In: http://members.unine.ch/jacques.savoy/Papers/CLIRIPM.pdf BASE Show details 28 Abstract Combining Multiple Strategies for Effective Monolingual and Cross-Language Retrieval Jacques Savoy In: http://members.unine.ch/jacques.savoy/papers/clirir.pdf BASE Show details 29 Simple and efficient classification scheme based on specific vocabulary Jacques Savoy; Olena Zubaryeva Abstract: Assuming a binomial distribution for word occurrence, we propose computing a standardized Z score to define the specific vocabulary of a subset compared to that of the entire corpus. This approach is applied to weight terms (character n-gram, word, stem, lemma or sequence of them) which characterize a document. We then show how these Z score values can be used to derive a simple and efficient categorization scheme. To evaluate this proposition and demonstrate its effectiveness, we develop two experiments. First, the system must categorize speeches given by B. Obama as being either electoral or presidential speech. In a second experiment, sentences are extracted from these speeches and then categorized under the headings electoral or presidential. Based on these evaluations, the proposed classification scheme tends to perform better than a support vector machine model for both experiments, on the one hand, and on the other, shows a better performance level than a Naïve Bayes classifier on the first test and a slightly lower performance on the second (10-fold cross validation). Copyright Springer-Verlag 2012 ; Statistics in lexical analysis, Corpus linguistics, Text categorization, Machine learning, Natural language processing (NLP) URL: http://hdl.handle.net/10.1007/s10287-012-0149-z BASE Hide details 30 Stemming of French words based on grammatical categories Jacques Savoy BASE Show details 31 Retrieval effectiveness of machine translated queries Ljiljana Dolamic; Jacques Savoy BASE Show details Page: 1 2

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