Abstract
Recently, the Web has been rapidly “deepened” by many searchable databases online, where data are hidden behind query interfaces. Automatic processing of a query interface is a must to access the invisible contents of deep Web. This entails automatic segmentation, i.e., the task of grouping related components of an interface together. The segmentation is divided into two steps: interface component labeling and interface component grouping. In this paper we present a new approach to perform query interface segmentation using two-phase Conditional Random Fields (CRFs). At the first phase, one CRFs model is used to tag each component with a semantic label (attribute-name, operator, operand or other); at the second phase, another CRFs model is used to create groups of related components. Experiments show that our approach yields high accuracy.
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Dong, Y., Zhao, X., Zhang, G. (2011). A Study on Using Two-Phase Conditional Random Fields for Query Interface Segmentation. In: Gong, Z., Luo, X., Chen, J., Lei, J., Wang, F.L. (eds) Web Information Systems and Mining. WISM 2011. Lecture Notes in Computer Science, vol 6988. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23982-3_45
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DOI: https://doi.org/10.1007/978-3-642-23982-3_45
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