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31 results on '"Candan, K.S."'

1. Object and combination shedding schemes for adaptive media workflow execution

Author

Lina Peng, Renwei Yu, Candan, K.S., and Xinxin Wang

Subjects
Query processing -- Analysis, Real-time control -- Analysis, Real-time systems -- Analysis, Multimedia asset management software, Real-time system, Business, Computers, Electronics, Electronics and electrical industries
Published
2010

2. Overview of SimpleText 2021 - CLEF Workshop on Text Simplification for Scientific Information Access

Author

Ermakova, L., Bellot, P., Braslavski, P., Kamps, J., Mothe, J., Nurbakova, D., Ovchinnikova, I., SanJuan, E., Candan, K.S., Ionescu, B., Goeuriot, L., Larsen, B., Müller, H., Joly, A., Maistro, M., Piroi, F., Faggioli, G., Ferro, N., ILLC (FGw), Language and Computation (ILLC, FNWI/FGw), Université de Brest (UBO), Héritages et Constructions dans le Texte et l'Image (HCTI), Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Institut Brestois des Sciences de l'Homme et de la Société (IBSHS), Laboratoire d'Informatique et Systèmes (LIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Ural Federal University [Ekaterinburg] (UrFU), University of Amsterdam [Amsterdam] (UvA), Systèmes d’Informations Généralisées (IRIT-SIG), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Sechenov First Moscow State Medical University, Laboratoire Informatique d'Avignon (LIA), Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI, Distribution, Recherche d'Information et Mobilité (DRIM), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Contextualization, Correctness, Computer science, Text simplification, MULTI DOCUMENTS SUMMARIZATION, Information access, Scientific literature, (Multi-document) summarization, Background knowledge Everything, DOCUMENT RETRIEVAL, Multi-document summarization, SCIENTIFIC TEXTS, Document retrieval, SCIENTIFIC INFORMATION, (MULTI-DOCUMENT) SUMMARIZATION, Data science, CONTEXTUALIZATION, INFORMATION RETRIEVAL, Clef, SCIENTIFIC TEXT SIMPLIFICATION, NATURAL LANGUAGE PROCESSING SYSTEMS, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], BACKGROUND KNOWLEDGE, INFORMATION ACCESS, Scientific text simplification, FULLY INTEGRATED
Abstract

Information retrieval has moved from traditional document retrieval in which search is an isolated activity, to modern information access where search and the use of the information are fully integrated. But non-experts tend to avoid authoritative primary sources such as scientific literature due to their complex language, internal vernacular, or lacking prior background knowledge. Text simplification approaches can remove some of these barriers, thereby avoiding that users rely on shallow information in sources prioritizing commercial or political incentives rather than the correctness and informational value. The CLEF 2021 SimpleText track addresses the opportunities and challenges of text simplification approaches to improve scientific information access head-on. We aim to provide appropriate data and benchmarks, starting with pilot tasks in 2021, and create a community of NLP and IR researchers working together to resolve one of the greatest challenges of today. © 2021, Springer Nature Switzerland AG.

Published
2021
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3. Collaborative Multimedia Systems: Synthesis of Media Objects

Author

Candan, K.S., Candan, K.S., Rangan, V., Subrahmanian, V.S., Candan, K.S., Candan, K.S., Rangan, V., and Subrahmanian, V.S.

Abstract

When a group I_1,... ,I_n of individuals wishes to collaboratively construct a complex multimedia document, the first requirement is that they be able to manipulate media-objects created by one another. For instance, if individual I_j wishes to access some media objects present at participant I_k's site, he must be able to; (1) retrieve this object from across the network, (2) ensure that the object is in a form that is compatible with the viewing/editing resources he has available at his node, and (3) ensure that the object has the desired quality (such as image size and resolution). Furthermore, he must be able to achieve these goals at the lowest possible cost. In this paper, we develop a theory of media objects, and present optimal algorithms for collaborative object sharing/synthesis of the sort envisaged above. We then extend the algorithms to incorporate quality constraints (such as image size) as well as distribution across multiple nodes. The theoretical model is validated by an experimental implementation that supports the theoretical results. (Also cross-referenced as UMIACS-TR-96-8)

Published
1998

4. Collaborative Multimedia Documents: Authoring and Presentation

Author

Candan, K.S., Candan, K.S., Prabhakaran, B., Subrahmanian, V.S., Candan, K.S., Candan, K.S., Prabhakaran, B., and Subrahmanian, V.S.

Abstract

Multimedia documents are composed of different data types such as video, audio, text and images. Authoring a multimedia document is a creative exercise. Unlike traditional computer supported collaborative work where documents are composed of static objects, multimedia documents have temporal, spatial and quality of service (QoS) requirements that must be supported by any collaborative multimedia platform. In this paper, we show that most requirements (including temporal, spatial, and QoS requirements) for collaborative multimedia systems can be expressed in terms of a highly-structured class of linear constraints called difference constraints that have been well-studied in the operations research literature. As a consequence, well known algorithms for solving difference constraints may be used as a starting point for creating multimedia documents. Based on our difference-constraint based characterization, we develop efficient, incremental algorithms for creating and modifying multimedia documents so as to satisfy the required temporal, spatial and QoS constraints. We further develop methods to identify inconsistent requirements, and show how such inconsistencies may be removed through constraint relaxation techniques. (Also cross-referenced as UMIACS-TR-96-9)

Published
1998

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