Building efficient and effective metasearch engines
ACM Computing Surveys (CSUR)
Proceedings of the 27th International Conference on Very Large Data Bases
AnswerBus question answering system
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Attempto Controlled English for Knowledge Representation
Reasoning Web
Proceedings of the VLDB Endowment
Kosmix: high-performance topic exploration using the deep web
Proceedings of the VLDB Endowment
Schema Normalization for Improving Schema Matching
ER '09 Proceedings of the 28th International Conference on Conceptual Modeling
Guideline based evaluation and verbalization of OWL class and property labels
Data & Knowledge Engineering
Interoperability by design using the StdTrip tool: an a priori approach
Proceedings of the 6th International Conference on Semantic Systems
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This paper introduces an approach to address the problem of accessing conventional and geographic data from the Deep Web. The approach relies on describing the relevant data through well-structured sentences, and on publishing the sentences as Web pages, following the W3C and the Google recommendations. For conventional data, the sentences are generated with the help of database views. For vector data, the topological relationships between the objects represented are first generated, and then sentences are synthesized to describe the objects and their topological relationships. Lastly, for raster data, the geographic objects overlapping the bounding box of the data are first identified with the help of a gazetteer, and then sentences describing such objects are synthesized. The Web pages thus generated are easily indexed by traditional search engines, but they also facilitated the task of more sophisticated engines that support semantic search based on natural language features.