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- Publisher Website: 10.1007/s10115-017-1062-0
- Scopus: eid_2-s2.0-85019121195
- WOS: WOS:000427971400002
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Article: STEM: a suffix tree-based method for web data records extraction
Title | STEM: a suffix tree-based method for web data records extraction |
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Authors | |
Keywords | Web data extraction Suffix tree HTML tag path Data Record pattern |
Issue Date | 2018 |
Publisher | Springer-Verlag London Ltd. The Journal's web site is located at http://link.springer.de/link/service/journals/10115/ |
Citation | Knowledge and Information Systems, 2018, v. 55 n. 2, p. 305-331 How to Cite? |
Abstract | To automatically extract data records from Web pages, the data record extraction algorithm is required to be robust and efficient. However, most of existing algorithms are not robust enough to cope with rich information or noisy data. In this paper, we propose a novel suffix tree-based extraction method (STEM) for this challenging task. First, we extract a sequence of identifiers from the tag paths of Web pages. Then, a suffix tree is built on top of this sequence and four refining filters are proposed to screen out data regions that might not contain data records. To evaluate model performance, we define an evaluation metric called pattern similarity and perform rigorous experiments on five real data sets. The promising experimental results have demonstrated that the proposed STEM is superior to the state-of-the-art algorithms like MDR, TPC and CTVS with respect to precision, recall and pattern similarity. Moreover, the time complexity of STEM is linear to the total number of HTML tags contained in Web pages, which indicates the potential applicability of STEM in a wide range of Web-scale data record extraction applications. |
Persistent Identifier | http://hdl.handle.net/10722/243522 |
ISSN | 2023 Impact Factor: 2.5 2023 SCImago Journal Rankings: 0.860 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Fang, Y | - |
dc.contributor.author | Xie, X | - |
dc.contributor.author | Zhang, X | - |
dc.contributor.author | Cheng, CK | - |
dc.contributor.author | Zhang, Z | - |
dc.date.accessioned | 2017-08-25T02:55:57Z | - |
dc.date.available | 2017-08-25T02:55:57Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Knowledge and Information Systems, 2018, v. 55 n. 2, p. 305-331 | - |
dc.identifier.issn | 0219-1377 | - |
dc.identifier.uri | http://hdl.handle.net/10722/243522 | - |
dc.description.abstract | To automatically extract data records from Web pages, the data record extraction algorithm is required to be robust and efficient. However, most of existing algorithms are not robust enough to cope with rich information or noisy data. In this paper, we propose a novel suffix tree-based extraction method (STEM) for this challenging task. First, we extract a sequence of identifiers from the tag paths of Web pages. Then, a suffix tree is built on top of this sequence and four refining filters are proposed to screen out data regions that might not contain data records. To evaluate model performance, we define an evaluation metric called pattern similarity and perform rigorous experiments on five real data sets. The promising experimental results have demonstrated that the proposed STEM is superior to the state-of-the-art algorithms like MDR, TPC and CTVS with respect to precision, recall and pattern similarity. Moreover, the time complexity of STEM is linear to the total number of HTML tags contained in Web pages, which indicates the potential applicability of STEM in a wide range of Web-scale data record extraction applications. | - |
dc.language | eng | - |
dc.publisher | Springer-Verlag London Ltd. The Journal's web site is located at http://link.springer.de/link/service/journals/10115/ | - |
dc.relation.ispartof | Knowledge and Information Systems | - |
dc.rights | The final publication is available at Springer via http://dx.doi.org/[insert DOI] | - |
dc.subject | Web data extraction | - |
dc.subject | Suffix tree | - |
dc.subject | HTML tag path | - |
dc.subject | Data Record pattern | - |
dc.title | STEM: a suffix tree-based method for web data records extraction | - |
dc.type | Article | - |
dc.identifier.email | Cheng, CK: ckcheng@cs.hku.hk | - |
dc.identifier.authority | Cheng, CK=rp00074 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/s10115-017-1062-0 | - |
dc.identifier.scopus | eid_2-s2.0-85019121195 | - |
dc.identifier.hkuros | 275445 | - |
dc.identifier.volume | 55 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 305 | - |
dc.identifier.epage | 331 | - |
dc.identifier.isi | WOS:000427971400002 | - |
dc.publisher.place | United Kingdom | - |
dc.identifier.issnl | 0219-3116 | - |