English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the zaia usage as premium feature

ZAIA

Presents the pdf analysis as premium feature

PDF Analysis

Insights

Presents the summarisation as premium feature

Summarisation

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the access of premium content as premium feature

Premium Content

Zendy Tools

Zendy Open

For our second participation in the CLEF retrieval tasks, our first objective was to propose better and more general stopword lists for various European languages (namely, French, Italian, German, Spanish and Finnish) along with improved, simpler and efficient stemming procedures. Our second goal was to propose a combined query-translation approach that could cross language barriers and also an effective merging strategy based on logistic regression for accessing the multilingual collection. Finally, within the Amaryllis experiment, we wanted to analyze how a specialized thesaurus might improve retrieval effectiveness. Based on our experiments of last year (Savoy 2002b), we participate in French, Italian, Spanish, German, Dutch and Finnish monolingual tasks in which our information retrieval approaches could work without having to rely on a dictionary. In Section 1, we improve our stopword lists and simple stemmers for the French, Italian, Spanish and German languages. For German, we also propose a new decompounding algorithm. For Dutch, we use the available stoplist and stemmer, and for the Finnish language we design a new stemmer and stopword list. In order to obtain a better overview, we evaluate our propositions using ten different retrieval schemes. In Section 2, for the various bilingual tracks we choose to express the submitted requests in the English language, which are in turn automatically translated using five different machine translation (MT) systems and one bilingual dictionary. We study these various translations, and based on the relative merit of each translation device we investigate various combinations of them. In Section 3, we carry out a multilingual information retrieval, investigating various merging strategies based on the results obtained during our bilingual tasks. Finally, in the last section, we present various experiments done using the Amaryllis corpus, within which a specialized thesaurus is made available in order to improve the retrieval effectiveness of the information retrieval system.

Report on CLEF 2002 Experiments: Combining Multiple Sources of Evidence