| 摘要(英) |
WorldWideWeb (WWW) is the mainstream media of modern information dissemination. Many application services rely on Web Data Extraction technology to support information integration services.Although many unsupervised data capture methods have been proposed in the past, the multi-data capture method (such as MDR) that considers a single page can only process the RecordSet in this page, and it cannot consider the overall structure; While multi-page alignment methods (such as DCADE) can identify the difference between templates and data through multi-page data, the identification of record sets is often not robust enough, and it is often impossible to complete the retrieval task for complex websites.In this study, combining the advantages of the two methods, MDR is used to extract data sets from individual web pages, and then the data sets from multiple web pages are extracted for three sub-tasks: Recordset Matching, Column Alignment and NonRecordset Matching.In the record set part, we use the BERT sentence representation to calculate the representation of each data in the data set, and then use the Schema Matching to achieve the record set matching; at the same time, the KNN and SVM classifiers are used to complete the Column Alignment task; in The non-record part is accomplished by using the DCADE multi-page data capture method to perform multi-page attribute alignment capabilities for non-record sets; finally, we combine the two results to achieve multi-page data capture.In addition to ExAlg and WEIR data sets, we also provide a website latest news announcement data set (Announcement List Website, ALW), which is used to test the automatic data effect of the latest website news or announcement list. Experimental results show that our proposed method DEVOSM (Data Extraction via On-the-fly Schema Matching) improved by 55.6%、60% and 33.7% on ExAlg, WEIR and ALW datasets Recordset retrieval rate, showing the effectiveness of the proposed method. |
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