Abstract
In vertical search engine research, many works have been reported. But most of them focus on its key issues such as crawling, extraction, and query and few of them give a total solution for building a complete vertical search engine from scratch in a systematic method. To address this issue, we propose a model-driven method and its supporting tool SESQ. Based on a user defined ER schema for a target domain, the tool can help to build a complete search engine by integrating tasks of crawling, extraction, data management and query within one unified framework. © 2008 Springer Berlin Heidelberg.
Author supplied keywords
Cite
CITATION STYLE
Lin, L., He, Y., Guo, H., Fan, J., Zhou, L., Guo, Q., & Li, G. (2008). SESQ: A model-driven method for building object level vertical search engines. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5231 LNCS, pp. 516–517). Springer Verlag. https://doi.org/10.1007/978-3-540-87877-3_39
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
