SESQ: A Model-Driven Method for Building Object Level Vertical Search Engines

Authors:
Ling Lin;Yukai He;Hang Guo;Ju Fan;Lizhu Zhou;Qi Guo;Gang Li
Affiliations:
Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Sohu Research and Development Division, Beijing, China;Sohu Research and Development Division, Beijing, China
Venue:
ER '08 Proceedings of the 27th International Conference on Conceptual Modeling
Year:
2008

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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.