Clef de l'histoire de la comédie grecque,

Mode of access: Internet.

Supplement au corps universel diplomatique du droit des gens : contenant un recueil des traitez d'alliance, de paix, de treve, de neutralite, de Commerce, d'Echange, de Protection & de Garantie ... et en general de tous le titres, sous quelque nom qu'on les désigne /

Mode of access: Internet.

Fleurs historiques : clef des allusions aux faits et aux mots célèbres que l'on rencontre fréquemment dans les ouvrages des écrivains français /

Après 1862, date de la 1re éd. d'après BN Cat. gén.

Clef, ou Explication des divers points et termes principaux, employés par Jacob Boehme.

Mode of access: Internet.

Clef du grand œuvre, ou lettres du Sancelrien Tourangeau, a Madame L.D.L.B***. T.D.F.A.T. [Madame le Febvre de la Borde, Trésorière de France à Tours] : Dans la premiere ... la matiere des sages. Dans la seconde, les vertus ... de l'elexir [sic] blanc et rouge ... Dans la troisieme ... sera prouvé la réalité du grand œuvre.

The attribution to Cailleau is by Barbier. A note in the de Guaita copy assigns the work to J.J. Coullon.

La clef des langues, ou Observations sur l'origine et la formation des principales langues qu'on parle et qu'on écrit en Europe.

Mode of access: Internet.

Précis théorique et pratique de langue malgache, pour faciliter l'usage rapide du hova, clef des autres dialectes;

Mode of access: Internet.

La clef du cabinet des princes de l'Europe, ou, Recuëil historique & politique sur les matieres du tems.

Description based on: jan. 1706 (t. 4e).

Ariane et la Clef d'Or

L’œuvre de Paul Dukas ne peut pas être réduite à son œuvre la plus célèbre, L’Apprenti sorcier. Ayant pratiqué aussi la critique, Dukas apparaît comme un auteur avec un style original et propre différencié de celui de Debussy. Dans Ariane et Barbe-Bleue, malveillamment considérée comme une simple réponse à Pelléas et Mélisande, sa préoccupation principale reste la transformation en musique du poème de Maeterlinck, d’en sortir la musique interne du langage écrit.

Age and Gender Identification using Stacking for Classification⋆ Notebook for PAN at CLEF 2016

This paper presents our approach of identifying the profile of an unknown user based on the activities of known users. The aim of author profiling task of PAN@CLEF 2016 is cross-genre identification of the gender and age of an unknown user. This means training the system using the behavior of different users from one social media platform and identifying the profile of other user on some different platform. Instead of using single classifier to build the system we used a combination of different classifiers, also known as stacking. This approach allowed us explore the strength of all the classifiers and minimize the bias or error enforced by a single classifier.

Author Profiling using SVMs and Word Embedding Averages — Notebook for PAN at CLEF 2016

In this paper, we describe one of the approaches of the participation of Universidade de Évora. Our approach is similar to usual methods where text is preprocessed, features are extracted, and then used in SVMs with cross validation. The main difference is that features used come from averages of word embeddings, specifically word2vec vectors. Using PAN 2016 dataset, we were able to achieve 44.8% and 68.2% for English age and gender classification respectively. We were also able to achieve 51.3% and 67.1% accuracy for Spanish age and gender classification. Finally, we report 71.9% accuracy for Dutch age classification.

A Virtual Evaluation Track for Cross Language Link Discovery

The Wikipedia has become the most popular online source of encyclopedic information. The English Wikipedia collection, as well as some other languages collections, is extensively linked. However, as a multilingual collection the Wikipedia is only very weakly linked. There are few cross-language links or cross-dialect links (see, for example, Chinese dialects). In order to link the multilingual-Wikipedia as a single collection, automated cross language link discovery systems are needed – systems that identify anchor-texts in one language and targets in another. The evaluation of Link Discovery approaches within the English version of the Wikipedia has been examined in the INEX Link the-Wiki track since 2007, whilst both CLEF and NTCIR emphasized the investigation and the evaluation of cross-language information retrieval. In this position paper we propose a new virtual evaluation track: Cross Language Link Discovery (CLLD). The track will initially examine cross language linking of Wikipedia articles. This virtual track will not be tied to any one forum; instead we hope it can be connected to each of (at least): CLEF, NTCIR, and INEX as it will cover ground currently studied by each. The aim is to establish a virtual evaluation environment supporting continuous assessment and evaluation, and a forum for the exchange of research ideas. It will be free from the difficulties of scheduling and synchronizing groups of collaborating researchers and alleviate the necessity to travel across the globe in order to share knowledge. We aim to electronically publish peer-reviewed publications arising from CLLD in a similar fashion: online, with open access, and without fixed submission deadlines.

Overview of INEX 2013

INEX investigates focused retrieval from structured documents by providing large test collections of structured documents, uniform evaluation measures, and a forum for organizations to compare their results. This paper reports on the INEX 2013 evaluation campaign, which consisted of four activities addressing three themes: searching professional and user generated data (Social Book Search track); searching structured or semantic data (Linked Data track); and focused retrieval (Snippet Retrieval and Tweet Contextualization tracks). INEX 2013 was an exciting year for INEX in which we consolidated the collaboration with (other activities in) CLEF and for the second time ran our workshop as part of the CLEF labs in order to facilitate knowledge transfer between the evaluation forums. This paper gives an overview of all the INEX 2013 tracks, their aims and task, the built test-collections, and gives an initial analysis of the results

Creation of a new evaluation benchmark for information retrieval targeting patient information needs

Searching for health advice on the web is becoming increasingly common. Because of the great importance of this activity for patients and clinicians and the effect that incorrect information may have on health outcomes, it is critical to present relevant and valuable information to a searcher. Previous evaluation campaigns on health information retrieval (IR) have provided benchmarks that have been widely used to improve health IR and record these improvements. However, in general these benchmarks have targeted the specialised information needs of physicians and other healthcare workers. In this paper, we describe the development of a new collection for evaluation of effectiveness in IR seeking to satisfy the health information needs of patients. Our methodology features a novel way to create statements of patients’ information needs using realistic short queries associated with patient discharge summaries, which provide details of patient disorders. We adopt a scenario where the patient then creates a query to seek information relating to these disorders. Thus, discharge summaries provide us with a means to create contextually driven search statements, since they may include details on the stage of the disease, family history etc. The collection will be used for the first time as part of the ShARe/-CLEF 2013 eHealth Evaluation Lab, which focuses on natural language processing and IR for clinical care.

Report on INEX 2013

INEX investigates focused retrieval from structured documents by providing large test collections of structured documents, uniform evaluation measures, and a forum for organizations to compare their results. This paper reports on the INEX 2013 evaluation campaign, which consisted of four activities addressing three themes: searching professional and user generated data (Social Book Search track); searching structured or semantic data (Linked Data track); and focused retrieval (Snippet Retrieval and Tweet Contextualization tracks). INEX 2013 was an exciting year for INEX in which we consolidated the collaboration with (other activities in) CLEF and for the second time ran our workshop as part of the CLEF labs in order to facilitate knowledge transfer between the evaluation forums. This paper gives an overview of all the INEX 2013 tracks, their aims and task, the built test-collections, and gives an initial analysis of the results.