Classification and Annotation in Social Corpora using Multiple Relations

Yann Jacob 1 Ludovic Denoyer 1 Patrick Gallinari 1
1 MALIRE - Machine Learning and Information Retrieval
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : We consider the problem of learning to annotate documents with concepts or keywords in content information networks, where the documents may share multiple relations. The concepts associated to a document will depend both on its content and on its neighbors in the network through the different relations. We formalize this problem as single and multi-label classification in a multi-graph, the nodes being the documents and the edges representing the different relations. The proposed algorithm learns to weight the different relations according to their importance for the annotation task. We perform experiments on different corpora corresponding to different annotation tasks on scientific articles, emails and Flickr images and show how the model may take advantage of the rich relational information.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01286078
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Submitted on : Thursday, March 10, 2016 - 11:32:43 AM
Last modification on : Thursday, March 21, 2019 - 2:16:32 PM

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Yann Jacob, Ludovic Denoyer, Patrick Gallinari. Classification and Annotation in Social Corpora using Multiple Relations. The 20th ACM international conference on Information and knowledge management CIKM'11, Oct 2011, Glasgow, United Kingdom. pp.1215-1220, ⟨10.1145/2063576.2063752⟩. ⟨hal-01286078⟩

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