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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 4 of 4 1 Building bridges for multimodal research : international perspectives on theories and practices of multimodal analysis Weiland, Lydia; Kopf, Stephan; Wildfeuer, Janina (Herausgeber). - Frankfurt am Main : Peter Lang Edition, 2015 BLLDB UB Frankfurt Linguistik Show details 2 Automatic classification of iconic images based on a multimodal model : an interdisciplinary project Ponzetto, Simone; Wessler, Hartmut; Weiland, Lydia... In: Building bridges for multimodal research (Frankfurt am Main, 2015), p. 193-210 MPI für Psycholinguistik Show details 3 Image with a message : towards detecting non-literal image usages by visual linking Weiland, Lydia; Ponzetto, Simone Paolo; Dietz, Laura. - : Assoc. for Computational Linguistics, 2015 BASE Show details 4 Weakly supervised construction of a repository of iconic images Weiland, Lydia; Effelsberg, Wolfgang; Ponzetto, Simone Paolo. - : Asooc. for Computational Linguistics, 2014 Abstract: We present a first attempt at semi-automatically harvesting a dataset of iconic images, namely images that depict objects or scenes, which arouse associations to abstract topics. Our method starts with representative topic-evoking images from Wikipedia, which are labeled with relevant concepts and entities found in their associated captions. These are used to query an online image repository (i.e., Flickr), in order to further acquire additional examples of topic-specific iconic relations. To this end, we leverage a combination of visual similarity measures, image clustering and matching algorithms to acquire clusters of iconic images that are topically connected to the original seed images, while also allowing for various degrees of diversity. Our first results are promising in that they indicate the feasibility of the task and that we are able to build a first version of our resource with minimal supervision. Keyword: 004 Informatik URL: https://madoc.bib.uni-mannheim.de/37061/ http://www.aclweb.org/anthology/W14-5410 BASE Hide details

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