Options
Savoy, Jacques
Nom
Savoy, Jacques
Affiliation principale
Fonction
Professeur.e ordinaire
Email
jacques.savoy@unine.ch
Identifiants
Résultat de la recherche
Voici les éléments 1 - 10 sur 14
- PublicationAccès libreInformation retrieval with Hindi, Bengali, and Marathi languages: evaluation and analysis(2013)
;
For the three studied languages, our experiments tend to show that IR models derived from Divergence from Randomness (DFR) paradigm tend to produce the best overall results. For these languages, our various experiments demonstrate also that either an aggressive stemming procedure or the trunc-n indexing approach produces better retrieval effectiveness when compared to other word-based or n-gram language-independent approaches. Applying the Z-score as data fusion operator after a blind-query expansion tends also to improve the MAP of the merged run over the best single IR system. - PublicationAccès libreRecherche d’information dans un corpus bruité (OCR)(2011)
; ; Dolamic, LjiljanaCet article désire mesurer la perte de performance lors de la recherche d'information dans une collection de documents scannés. Disposant d'un corpus sans erreur et de deux versions renfermant 5 % et 20 % d'erreurs en reconnaissance, nous avons évalué six modèles de recherche d'information basés sur trois représentations des documents (sac de mots, n-grammes, ou trunc-n) et trois enracineurs. Basé sur l'inverse du rang du premier document pertinent dépisté, nous démontrons que la perte de performance se situe aux environs de - 17 % avec un taux d'erreur en reconnaissance de 5 % et s'élève à – 46 % si ce taux grimpe à 20 %. La représentation par 4-grammes semble apporter une meilleure qualité de réponse avec un corpus bruité. Concernant l'emploi ou non d'un enracineur léger ou la pseudo-rétroaction positive, aucune conclusion définitive ne peut être tirée., This paper evaluates the retrieval effectiveness degradation when facing with noisy text corpus. With the use of a test-collection having the clean text, another version with around 5% error rate in recognition and a third with 20% error rate, we have evaluated six IR models based on three text representations (bag-of-words, n-grams, trunc-n) as well as three stemmers. Using the mean reciprocal rank as performance measure, we show that the average retrieval effectiveness degradation is around -17% when dealing with an error rate of 5%. This average decrease is around -46% when facing with an error rate of 20%. The representation by 4-grams tends to offer the best retrieval when searching with noisy text. Finally, we are not able to obtain clear conclusion about the impact of different stemming strategies or the use of blind-query expansion. - PublicationAccès libreInfluence of language morphological complexity on information retrieval(2010)
; In this dissertation two aspects of information retrieval are elaborated. The frst involves the creation and evaluation of various linguistic tools for languages less studied than English, and in our case we have chosen to work with the two Slavic languages Czech and Russian, and three languages widely spoken on the Indian subcontinent, Hindi, Marathi and Bengali. To do so we compare various indexing strategies and IR models most likely to obtain the best possible performance. The second part involves an evaluation of the effectiveness of queries written in different languages when searching collections written in either English or French. To cross the language barriers we apply publicly available machine translation services, analyze the results and then explain the poor performances obtained by the translated queries. - PublicationAccès libreComparative Study of Indexing and Search Strategies for the Hindi, Marathi, and Bengali Languages(2010)
In our evaluation of these stemming strategies we make use of the FIRE 2008 test collections, and then to broaden our comparisons we implement and evaluate two language independent indexing methods: the n-gram and trunc-n (truncation of the first n letters). We evaluate these solutions by applying our various IR models, including the Okapi, Divergence from Randomness (DFR) and statistical language models (LM) together with two classical vector-space approaches: tf idf and Lnu-ltc.
Experiments performed with all three languages demonstrate that the I(ne)C2 model derived from the Divergence from Randomness paradigm tends to provide the best mean average precision (MAP). Our own tests suggest that improved retrieval effectiveness would be obtained by applying more aggressive stemmers, especially those accounting for certain derivational suffixes, compared to those involving a light stemmer or ignoring this type of word normalization procedure. Comparisons between no stemming and stemming indexing schemes shows that performance differences are almost always statistically significant. When, for example, an aggressive stemmer is applied, the relative improvements obtained are ≈28% for the Hindi language, ≈42% for Marathi, and ≈18% for Bengali, as compared to a no-stemming approach. Based on a comparison of word-based and language-independent approaches we find that the trunc-4 indexing scheme tends to result in performance levels statistically similar to those of an aggressive stemmer, yet better than the 4-gram indexing scheme. A query-by-query analysis reveals the reasons for this, and also demonstrates the advantage of applying a stemming or a trunc-4 indexing scheme. - PublicationAccès libreRetrieval Effectiveness of Machine Translated Queries(2010)
- PublicationAccès libreAd Hoc Retrieval with the Persian Language(2010)
- PublicationAccès libreUniNE at CLEF 2008: TEL, and Persian IR(2009)
- PublicationAccès libreIndexing and searching strategies for the Russian language(2009)
- PublicationAccès libreHow effective is Google's translation service in search?(2009)
; Dolamic, LjiljanaIn multilingual countries (Canada, Hong Kong, India, among others) and large international organizations or companies (such as, WTO, European Parliament), and among Web users in general, accessing information written in other languages has become a real need (news, hotel or airline reservations, or government information, statistics). While some users are bilingual, others can read documents written in another language but cannot formulate a query to search it, or at least cannot provide reliable search terms in a form comparable to those found in the documents being searched. There are also many monolingual users who may want to retrieve documents in another language and then have them translated into their own language, either manually or automatically.
Translation services may however be too expensive, not readily accessible or not available within a short timeframe. On the other hand, many documents contain non-textual information such as images, videos and statistics that do not need translation and can be understood regardless of the language involved. In response to these needs and in order to make the Web universally available regardless of any language barriers, in May 2007 Google launched a translation service that now provides two-way online translation services mainly between English and 41 other languages, for example, Arabic, simplified and traditional Chinese, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish (http://translate.google.com/). Over the last few years other free Internet translation services have been made available as for example by BabelFish (http://babel.altavista.com/) or Yahoo! (http://babelfish.yahoo.com/). These two systems are similar to that used by Google, given they are based on technology developed by Systran, one of the earliest companies to develop machine translation. Also worth mentioning here is the Promt system (also known as Reverso, http://translation2.paralink.com/), which was developed in Russia to provide mainly translation between Russian and other languages.
The question we would like to address here is to what extent a translation service such as Google can produce adequate results in the language other than that being used to write the query. Although we will not evaluate translations per se we will test and analyze various systems in terms of their ability to retrieve items automatically based on a translated query. To be adequate, these tests must be done on a collection of documents written in one given language plus a series of topics (expressing user information needs) written in other languages, plus a series of relevance assessments (relevant documents for each topic). - PublicationAccès libreWhen stopword lists make the difference(2009)