Abstract : The content and structure of linked information such as sets of web pages or research paper archives are dynamic and keep on changing. Even though different methods are proposed to exploit both the link structure and the content information, no existing approach can effectively deal with this evolution. We propose a novel joint model, called Link-IPLSI, to combine texts and links in a topic modeling framework incrementally. The model takes advantage of a novel link updating technique that can cope with dynamic changes of online document streams in a faster and scalable way. Furthermore, an adaptive asymmetric learning method is adopted to freely control the assignment of weights to terms and citations. Experimental results on two different sources of online information demonstrate the time saving strength of our method and indicate that our model leads to systematic improvements in the quality of classification.
Zhongzhi Shi; Sunil Vadera; Agnar Aamodt; David Leake. 6th IFIP TC 12 International Conference on Intelligent Information Processing (IIP), Oct 2010, Manchester, United Kingdom. Springer, IFIP Advances in Information and Communication Technology, AICT-340, pp.259-270, 2010, Intelligent Information Processing V. 〈10.1007/978-3-642-16327-2_32〉
https://hal.inria.fr/hal-01055070
Contributeur : Hal Ifip
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Soumis le : lundi 11 août 2014 - 12:35:34
Dernière modification le : vendredi 3 novembre 2017 - 22:24:06
Document(s) archivé(s) le : mercredi 26 novembre 2014 - 22:01:24
Huifang Ma, Zhixin Li, Zhongzhi Shi. Combining the Missing Link: An Incremental Topic Model of Document Content and Hyperlink. Zhongzhi Shi; Sunil Vadera; Agnar Aamodt; David Leake. 6th IFIP TC 12 International Conference on Intelligent Information Processing (IIP), Oct 2010, Manchester, United Kingdom. Springer, IFIP Advances in Information and Communication Technology, AICT-340, pp.259-270, 2010, Intelligent Information Processing V. 〈10.1007/978-3-642-16327-2_32〉. 〈hal-01055070〉
