DocumentCode :
3276961
Title :
Exploring semantic roles of Web interface components
Author :
Zhang, Kang ; Kong, Jun
Author_Institution :
Dept. of Comput. Sci., Univ. of Texas at Dallas, Dallas, TX, USA
fYear :
2010
fDate :
3-5 Oct. 2010
Firstpage :
8
Lastpage :
14
Abstract :
The adaptability of Web interfaces in response to changes in the interaction context, display environments (e.g., mobile screens) and user´s personal preferences is becoming increasingly desirable due to the pervasive use of Web information. One of the major challenges in Web interface adaptation is to discover the semantic structure underlying a Web interface. This paper presents a robust and formal approach to recovering interface semantics using a graph grammar approach. Due to its distinct characteristics of spatial specification in the abstract syntax, the Spatial Graph Grammar (SGG) is used to perform semantic grouping and interpretation of segmented screen objects. We use the well-established image processing technology to recognize atomic interface objects in an interface image. The output is a spatial graph, which records significant spatial relations among recognized objects. Based on the spatial graph, the SGG parser recovers the hierarchical relations among interface objects and thus provides semantic interpretation suitable for adaptation.
Keywords :
graph grammars; image segmentation; object recognition; semantic Web; ubiquitous computing; user interfaces; SGG parser; Web interface adaptation; abstract syntax; formal approach; image processing technology; interface image; pervasive interaction; screen object segmentation; semantic structure; spatial graph grammar; Grammar; Image recognition; Image segmentation; Production; Semantics; Web pages; Interface adaptation; Web semantics; graph grammar; layout;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine and Web Intelligence (ICMWI), 2010 International Conference on
Conference_Location :
Algiers
Print_ISBN :
978-1-4244-8608-3
Type :
conf
DOI :
10.1109/ICMWI.2010.5647848
Filename :
5647848
Link To Document :
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