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CIKM
2011
Springer

Joint inference for cross-document information extraction

12 years 3 months ago
Joint inference for cross-document information extraction
Previous information extraction (IE) systems are typically organized as a pipeline architecture of separated stages which make independent local decisions. When the data grows beyond some certain size, the extracted facts become inter-dependent and thus we can take advantage of information redundancy to conduct reasoning across documents and improve the performance of IE. We describe a joint inference approach based on information network structure to conduct cross-fact reasoning with an integer linear programming framework. Without using any additional labeled data this new method obtained 13.7%-24.4% user browsing cost reduction over a state-of-the-art IE system which extracts various types of facts independently. Categories and Subject Descriptors I.2.7 [Natural Language Processing]: Text analysis; H.3.4 [Systems and Software]: Information networks, Question-answering (fact retrieval) systems General Terms Algorithms Keywords Information extraction, global reasoning, Integer Linear...
Qi Li, Sam Anzaroot, Wen-Pin Lin, Xiang Li, Heng J
Added 13 Dec 2011
Updated 13 Dec 2011
Type Journal
Year 2011
Where CIKM
Authors Qi Li, Sam Anzaroot, Wen-Pin Lin, Xiang Li, Heng Ji
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