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» Learning to summarise XML documents using content and struct...
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WWW
2009
ACM
14 years 8 months ago
Enhancing diversity, coverage and balance for summarization through structure learning
Document summarization plays an increasingly important role with the exponential growth of documents on the Web. Many supervised and unsupervised approaches have been proposed to ...
Liangda Li, Ke Zhou, Gui-Rong Xue, Hongyuan Zha, Y...
CN
1999
143views more  CN 1999»
13 years 7 months ago
Embedding Knowledge in Web Documents
The paper argues for the use of general and intuitive knowledge representation languages (and simpler notational variants, e.g. subsets of natural languages) for indexing the cont...
Philippe Martin, Peter W. Eklund
SIGIR
2004
ACM
14 years 1 months ago
Multiple sources of evidence for XML retrieval
Document-centric XML collections contain text-rich documents, marked up with XML tags. The tags add lightweight semantics to the text. Querying such collections calls for a hybrid...
Börkur Sigurbjörnsson, Jaap Kamps, Maart...
ICPR
2010
IEEE
13 years 6 months ago
Unsupervised Learning from Linked Documents
Documents in many corpora, such as digital libraries and webpages, contain both content and link information. In a traditional topic model which plays an important role in the uns...
Zhen Guo, Shenghuo Zhu, Yun Chi, Zhongfei Zhang, Y...
ICML
2002
IEEE
14 years 8 months ago
Kernels for Semi-Structured Data
Semi-structured data such as XML and HTML is attracting considerable attention. It is important to develop various kinds of data mining techniques that can handle semistructured d...
Hisashi Kashima, Teruo Koyanagi