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Publisher
Springer, Berlin, Heidelberg
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Authors: Giuliano Armano Alessandro Giuliani Alberto Messina Maurizio Montagnuolo Eloisa Vargiu
Publish Date: 2013
Volume: , Issue: , Pages: 33-52
Abstract
Nowadays Web is characterized by a growing availability of multimedia data together with a strong need for integrating different media and modalities of interaction Hence one of the main challenges is to bring into the Web data thought and produced for different media such as TV or press content In this scenario we focus on multimodal news aggregation retrieval and fusion Multimodality here is intended as the capability of processing gathering manipulating and organizing data from multiple media In particular we tackle two main issues to extract relevant keywords to news and news aggregations and to automatically associate suitable advertisements to aggregated data To achieve the first goal we propose a solution based on the adoption of extractionbased text summarization techniques whereas to achieve the second goal we developed a contextual advertising system that works on multimodal aggregated data To assess the proposed solutions we performed experiments on Italian news aggregations Results show that in both cases the proposed solution performs better than the adopted baseline solutions
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