Harvesting facts from textual web sources by constrained label propagation
|Harvesting facts from textual web sources by constrained label propagation|
|Author(s)||Wang Y., Yang B., Qu L., Spaniol M., Weikum G.|
|Published in||International Conference on Information and Knowledge Management, Proceedings|
|Keyword(s)||knowledge harvesting, label propagation, temporal facts (Extra: Knowledge harvesting, label propagation, Large knowledge basis, Loss functions, Online news, temporal facts, Text sources, Time-awareness, Web sources, Wikipedia, Knowledge management, Websites, Harvesting)|
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Harvesting facts from textual web sources by constrained label propagation is a 2011 conference paper written in English by Wang Y., Yang B., Qu L., Spaniol M., Weikum G. and published in International Conference on Information and Knowledge Management, Proceedings.
There have been major advances on automatically constructing large knowledge bases by extracting relational facts from Web and text sources. However, the world is dynamic: periodic events like sports competitions need to be interpreted with their respective timepoints, and facts such as coaching a sports team, holding political or business positions, and even marriages do not hold forever and should be augmented by their respective timespans. This paper addresses the problem of automatically harvesting temporal facts with such extended time-awareness. We employ pattern-based gathering techniques for fact candidates and construct a weighted pattern-candidate graph. Our key contribution is a system called PRAVDA based on a new kind of label propagation algorithm with a judiciously designed loss function, which iteratively processes the graph to label good temporal facts for a given set of target relations. Our experiments with online news and Wikipedia articles demonstrate the accuracy of this method.
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