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One, no one and one hundred thousand events: Defining and processing events in an inter-disciplinary perspective
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IR-Depth Face Detection and Lip Localization Using Kinect V2
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In: Master's Theses (2015)
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Statistical Shape Analysis on MRI
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In: Sadeghi, Roksana. (2015). Statistical Shape Analysis on MRI. UC San Francisco: Biomedical Imaging. Retrieved from: http://www.escholarship.org/uc/item/4cp8t6x4 (2015)
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Multilingual Event Extraction for Epidemic Detection
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In: ISSN: 0933-3657 ; Artificial Intelligence in Medicine ; https://hal.archives-ouvertes.fr/hal-01294127 ; Artificial Intelligence in Medicine, Elsevier, 2015, 65 (2), pp.131--143. ⟨10.1016/j.artmed.2015.06.005⟩ (2015)
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Abstract:
International audience ; Objective : This paper presents a multilingual news surveillance system applied to tele-epidemiology. It has been shown that multilingual approaches improve timeliness in detection of epidemic events across the globe, eliminating the wait for local news to be translated into major languages. We present here a system to extract epidemic events in potentially any language, provided a Wikipedia seed for common disease names exists.Methods : The Daniel system presented herein relies on properties that are common to news writing (the journalistic genre), the most useful being repetition and saliency. Wikipedia is used to screen common disease names to be matched with repeated characters strings. Language variations, such as declensions, are handled by processing text at the character-level, rather than at the word level. This additionally makes it possible to handle various writing systems in a similar fashion.Material :As no multilingual ground truth existed to evaluate the Daniel system, we built a multilingual corpus from the Web, and collected annotations from native speakers of Chinese, English, Greek, Polish and Russian, with no connection or interest in the Daniel system. This data set is available online freely, and can be used for the evaluation of other event extraction systems.Results :Experiments for 5 languages out of 17 tested are detailed in this paper: Chinese, English, Greek, Polish and Russian. The Daniel system achieves an average F-measure of 82% in these 5 languages. It reaches 87% on BEcorpus, the state-of-the-art corpus in English, slightly below top-performing systems, which are tailored with numerous language-specific resources. The consistent performance of Daniel on multiple languages is an important contribution to the reactivity and the coverage of epidemiological event detection systems.Conclusions : Most event extraction systems rely on extensive resources that are language-specific. While their sophistication induces excellent results (over 90% precision and recall), it restricts their coverage in terms of languages and geographic areas. In contrast, in order to detect epidemic events in any language, the Daniel system only requires a list of a few hundreds of disease names and locations, which can actually be acquired automatically. The system can perform consistently well on any language, with precision and recall around 82% on average, according to this paper's evaluation. Daniel's character-based approach is especially interesting for morphologically-rich and low-resourced languages. The lack of resources to be exploited and the state of the art string matching algorithms imply that Daniel can process thousands of documents per minute on a simple laptop. In the context of epidemic surveillance, reactivity and geographic coverage are of primary importance, since no one knows where the next event will strike, and therefore in what vernacular language it will first be reported. By being able to process any language, the Daniel system offers unique coverage for poorly endowed languages, and can complete state of the art techniques for major languages.
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Keyword:
[INFO]Computer Science [cs]; Early event detection; Epidemic surveillance; Multilingual information access; Poorly endowed languages; Tele-epidemiology
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URL: https://doi.org/10.1016/j.artmed.2015.06.005
https://hal.archives-ouvertes.fr/hal-01294127
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Coreference Resolution for Oral Corpus: a machine learning experiment with ANCOR corpus ; Les coréférences à l'oral : une expérience d'apprentissage automatique sur le corpus ANCOR
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In: ISSN: 1248-9433 ; EISSN: 1965-0906 ; Revue TAL ; https://halshs.archives-ouvertes.fr/halshs-01153297 ; Revue TAL, ATALA (Association pour le Traitement Automatique des Langues), 2015, Traitement automatique du langage parlé, 55 (2), pp.97-121 ; http://www.atala.org/-Volume-55- (2015)
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Detecting sociosemantic communities by applying social network analysis in tweets
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In: ISSN: 1869-5450 ; EISSN: 1869-5469 ; Social Network Analysis and Mining ; https://hal.archives-ouvertes.fr/hal-01283863 ; Social Network Analysis and Mining, Springer, 2015, vol. 5 (n° 1), pp. 1-17. ⟨10.1007/s13278-015-0280-2⟩ (2015)
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Model of detection PR-impact by means of Internet mass media ; Метод выявления PR-влияния через Интернет-СМИ ; Метод виявлення PR-впливу через Інтернет ЗМІ
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In: Безпека інформації; Том 21, № 3 (2015); 294-300 ; Безопасность информации; Том 21, № 3 (2015); 294-300 ; Ukrainian Scientific Journal of Information Security; Том 21, № 3 (2015); 294-300 (2015)
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Sociolinguistically Informed Natural Language Processing: Automating Irony Detection
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In: DTIC (2015)
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Identifying Universal Linguistic Features Associated with Veracity and Deception
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In: DTIC (2015)
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Robust Speech Processing & Recognition: Speaker ID, Language ID, Speech Recognition/Keyword Spotting, Diarization/Co-Channel/Environmental Characterization, Speaker State Assessment
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In: DTIC (2015)
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Mobile Active Authentication via Linguistic Modalities
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In: DTIC (2015)
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Towards News Verification: Deception Detection Methods for News Discourse
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In: Victoria Rubin (2015)
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Towards News Verification: Deception Detection Methods for News Discourse
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In: FIMS Presentations (2015)
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Multilingual Trend Detection in the Web
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Stutzki, Jan. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2014. : OASIcs - OpenAccess Series in Informatics. 4th Student Conference on Operational Research, 2014
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“Time for Some Traffic Problems”: Enhancing E-Discovery and Big Data Processing Tools with Linguistic Methods for Deception Detection
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In: Journal of Digital Forensics, Security and Law (2014)
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Pragmatic and Cultural Considerations for Deception Detection in Asian Languages
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In: FIMS Publications (2014)
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Early-Detection System for Cross-Language (Translated) Plagiarism
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In: Lecture Notes in Computer Science ; 1st International Conference on Information and Communication Technology (ICT-EurAsia) ; https://hal.inria.fr/hal-01480193 ; 1st International Conference on Information and Communication Technology (ICT-EurAsia), Mar 2013, Yogyakarta, Indonesia. pp.21-30, ⟨10.1007/978-3-642-36818-9_3⟩ (2013)
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Détection automatique des sessions de recherche par similarité des résultats provenant d'une collection de documents externe
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In: Actes de la 15e Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RECITAL 2013) ; 15e Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RECITAL 2013) ; https://hal-univ-tlse2.archives-ouvertes.fr/hal-00982483 ; 15e Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RECITAL 2013), Jun 2013, Les Sables d'Olonne, France. pp.217-230 (2013)
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