Abstract：In the situation of crawling Deep Web database that limits the number of results, the problem of appropriately predicting the results size of queries can be modeled as a set covering problem with condition of limited set size. This problem is modeled as a concept covering problem. Firstly, the relation among all couples composed by a query and its result is proved as tolerance. Secondly, set of them is proved as a complete lattice which is homomorphism to the concept lattice from the same source. Therefore, the order relation between concepts can be utilized to describe correlation between queries. The intent of a concept can be considered as a query, thus the result size is forecasted by cardinality of the concept extent. A lattice-based algorithm is proposed for data extraction from limited Deep Web database, called Ladeldew. Semi-lattice pruned based on the cardinality of extent is exploited by Ladeldew as search space. The new search space is iteratively generated from new data until nothing can be extracted. Both controlled and real experiments are implemented to evaluate Ladeldew, and the results verify its theoretical correction and realistic application.
张卓，李石君，张乃洲，田建伟. 基于格空间的受限DeepWeb数据抽取算法[J]. 模式识别与人工智能, 2011, 24(1): 130-137.
ZHANG Zhuo, LI Shi-Jun, ZHANG Nai-Zhou, TIAN Jian-Wei. Data Extraction from Limited Deep Web Based on Latticial Space. , 2011, 24(1): 130-137.
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2011, Vol. 24 
