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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 蔡益坤 | |
| dc.contributor.author | Chih-Hua Tu | en |
| dc.contributor.author | 凃志樺 | zh_TW |
| dc.date.accessioned | 2021-06-14T17:07:16Z | - |
| dc.date.available | 2009-07-30 | |
| dc.date.copyright | 2008-07-30 | |
| dc.date.issued | 2008 | |
| dc.date.submitted | 2008-07-29 | |
| dc.identifier.citation | [1] Harith Alani, Sanghee Kim, David E. Millard, Mark J. Weal, Wendy Hall, Paul H.
Lewis, and Nigel R. Shadbolt. Automatic Ontology-Based Knowledge Extraction from Web Documents. IEEE Intelligent Systems, 18. [2] H.Peter Alesso and Craig F.Smith. Developing Semantic Web Services. A K Peters, Ltd., 2005. [3] R.C. Angell, G.E. Freund, and P. Willett. Automatic spelling correction using a trigram similarity measure. INFO. PROC. MGMT., 19(4):255–262, 1983. [4] Arvind Arasu and Hector Garcia-Molina. Extracting structured data from Web pages. Proceedings of the 2003 ACM SIGMOD international conference on Manage- ment of data, 2003. [5] David Aumueller, Hong-Hai Do, Sabine Massmann, and Erhard Rahm. Schema and ontology matching with COMA++. Proceedings of the 2003 ACM SIGMOD international conference on Management of data, 2005. [6] F. Baader, D. Calvanese, D. McGuinness, D. Nardi, and P. Patel-Schneider. The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, 2003. [7] Ricardo Baeza-Yates and Berthier Ribeiro-Neto. Modern Information Retrieval. Addison-Wesley, 1999. [8] T. Belwood et al. UDDI Version 3.0. [9] T. Bemers-Lee, J. Hendler, and O. Lassila. The Semantic Web. Scientific American, 284(5):34–43, 2001. [10] S.M. Benslimane, D. Benslimane, M. Malki, Y. Amghar, and H. Saliah-Hassane. Acquiring OWL ontologies from data-intensive web sites. Proceedings of the 6th international conference on Web engineering, pages 361–368, 2006. [11] D. Box, D. Ehnebuske, G. Kakivaya, A. Layman, N. Mendelsohn, HF Nielsen, S. Thatte, and D. Winer. Simple object access protocl (soap) 1.1. [12] C.H. Chang and S.C. Lui. IEPAD: Information Extraction Based on Pattern Dis- covery. Proceedings of the 10th international conference on World Wide Web, 2001. [13] E. Christensen, F. Curbera, G. Meredith, and S. Weerawarana. Web Services De- scription Language (WSDL) 1.1, 2001. [14] T.R. Gruber. A Translation Approach to Portable Ontology Specifications. Knowl- edge Acquisition, 5(2):199–220, 1993. [15] Dan Gusfield. Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology. Cambridge Universtiy Press, 1997. [16] Chung-Hao Hsieh. Approximate Matching and Ranking of Web Services Using On- tologies and Rules. Master’s thesis, National Taiwan University, Master’s Thesis, 2007. [17] H. Knublauch, R.W. Fergerson, N.F. Noy, and M.A. Musen. The Prot’eg’e OWL Plugin: An open development environment for semantic web applications. Third International Semantic Web Conference, pages 229–243, 2004. [18] Lee W. Lacy. OWL: Representing Information Using the Web Ontology Language. Tra?ord Publishing, 2005. [19] D.L. McGuinness, F. van Harmelen, et al. OWL web ontology language overview. W3C Recommendation, 10:2004–03, 2004. [20] George A. Miller. WordNet: a lexical database for English. Communications of the ACM, 38, 1995. [21] The University of She?eld. GATE, A General Architecture for Text Engineering, 2005. [22] P.F. Patel-Schneider and D. Fensel. Layering the Semantic Web: Problems and Directions. 2002 International Semantic Web Conference, 2002. [23] OWL Prot’eg’e. Plugin: www.protege. [24] Satoshi Sekine and Ralph Grishman. Apple Pie Parser. [25] K. Sivashanmugam, K. Verma, A. Sheth, and J. Miller. Adding semantics to web services standards. Proceedings of the International Conference on Web Services, pages 395–401, 2003. [26] Hsin-Ying Tai. Automated Web Service Composition and Execution Based on Se- mantic Web Technology. Master’s thesis, National Taiwan University, Master’s The- sis, 2007. [27] Waqas ur Rehman Chaudhry and Farid Meziane. Information Extraction from Het- erogeneousSourcesUsingDomainOntologies. IEEE—2005 International Conference on Emerging Technologies, 2005. [28] Patrick van Bommel (ed). Information Modeling for Internet Applications. Idea Group, 2003. [29] David W.Embley. Toward Semantic Understanding-An Approach Based on Informa- tionExtractionOntologies. Proceedings of the 15th Australasian database conference, 27, 2004. [30] Te-Wei Yang. An Integrated System for Web Services Search and Composition Combing Web2.0 and Semantic Web Technology. Master’s thesis, National Taiwan University, Master’s Thesis, 2008. [31] Franois Yergeau, Tim Bray, Jean Paoli, C. M. Sperberg-McQueen, and Eve Maler. Extensible Markup Language (XML) 1.0 (Fourth Edition). W3C Recommendation, 2006. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/40929 | - |
| dc.description.abstract | Web Services provide a standard means of interoperation between different software applications running on a variety of platforms and frameworks. Because of the rapid development of Web services,the scale of Web Services becomes larger. As a result, finding thesuitable Web Services is not a trivial task. Currently, the discovery mechanism supported by UDDI is not powerful enough for
automatic discovery. Since the mechanism is keyword-based search,the users have to type in a precise term to find the services thatthey want. Besides, it is necessary for people to read the returned description. Too many manual processes lack efficiency. The Semantic Web provides a common framework that allows data to be shared and reused across applications. Ontology is the basis of semantic annotation on Semantic Web. As a result, we can benefit from associating information with ontologies. In this thesis, we propose a semi-automatic approach for mapping Web tables to ontologies. Although the collection of Web Services are getting larger, there are still many other applications working on the Web. Through our mapping approach, we can integrate abundant information on Web pages into our ontology. The purpose of our approach is to directly import and map data / information from a Web page to an domain ontology. In this way, we have to firstly generate information from Web pages and then annotate the generated results. Accordingly, we can divide our approach into two main tasks. The first is ``Information Extraction', which aims to extract information from Web pages. The second is ``Semantic Annotation', which aims to generate the mapping between Web pages and ontologies. In the real world, information on Web pages could be exploited in many forms. It is nearly impossible to find a way to solve all kinds of “Information Extraction” problems. Therefore, we narrow down the scope of ``Information Extraction' task to Web tables. Tables, no matter they are on Web pages, text files, or in database are used to present certain type of information to their viewers in a formatted way. We apply the observed heuristics to help us extract and analyze tables. In the ``Semantic Annotation' phase, Natural Language Processing tools are adopted to help us interpret and annotate the tables. Our framework therefore can directly store and consolidate the corresponding instances and relationships in the ontology. We implemented a prototype system ``Table Mapper' to demonstrate our approach. From the execution results, our system performs well in several different Web pages. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-14T17:07:16Z (GMT). No. of bitstreams: 1 ntu-97-R95725038-1.pdf: 4712083 bytes, checksum: be9bc4f8a7764326c918ac816477f0fc (MD5) Previous issue date: 2008 | en |
| dc.description.tableofcontents | 1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Motivation and Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2 Related Work 5 2.1 Semantic Web . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.1 Ontologies For The Semantic Web . . . . . . . . . . . . . . . . . . 6 2.2 Syntactic and Semantic Tools . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2.1 Apple Pie Parser . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2.2 GATE - General Architecture for Text Engineering . . . . . . . . 7 2.3 A Generic Model for Knowledge Extraction From Web Pages - KAARE . 8 2.4 Ontology Mapping and Semantic Annotation . . . . . . . . . . . . . . . . 9 2.4.1 Structured Data, Ontology-Based . . . . . . . . . . . . . . . . . . 10 2.4.2 Unstructured Data, Ontology-Based - Artequakt Project . . . . . 13 2.4.3 Structured and Unstructured Data, Non-prior Ontology . . . . . . 17 3 Preliminaries 18 3.1 Description Logics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.2 XML . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.3 RDF: Resource Description Framework . . . . . . . . . . . . . . . . . . . 21 3.4 RDFS: RDF Schema . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.5 OWL: Web Ontology Language . . . . . . . . . . . . . . . . . . . . . . . 24 3.5.1 OWL Lite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.5.2 OWL DL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.5.3 OWL Full . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.5.4 The Mapping Between OWL DL and Description Logic . . . . . . 29 4 Mapping Web Tables to a Domain Ontology 30 4.1 System Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 4.2 Preliminary Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 4.2.1 Web Table Definition . . . . . . . . . . . . . . . . . . . . . . . . . 33 4.3 The Mapping Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 4.3.1 Table Location . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 4.3.2 Table Pruning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 4.3.3 Table Classification . . . . . . . . . . . . . . . . . . . . . . . . . . 46 4.3.4 Attribute and Value Generation . . . . . . . . . . . . . . . . . . . 50 4.4 Matcher . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 4.4.1 WordNet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 4.4.2 Levenshtein String Matching Algorithm . . . . . . . . . . . . . . . 54 4.4.3 Jaro-Winker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 4.4.4 Jaccard Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 5 Prototype System: Table Mapper of the Traveller 57 5.1 The Table Mapper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 5.2 Web Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 5.3 Ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 5.4 System Demonstration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 6 Conclusion 64 6.1 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 6.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 | |
| dc.language.iso | en | |
| dc.subject | 資訊檢索 | zh_TW |
| dc.subject | 知識本體 | zh_TW |
| dc.subject | 語意網 | zh_TW |
| dc.subject | 網路服務 | zh_TW |
| dc.subject | 知識本體語言 | zh_TW |
| dc.subject | OWL | en |
| dc.subject | Ontology | en |
| dc.subject | Web Table | en |
| dc.subject | Information Extraction | en |
| dc.subject | Mapping | en |
| dc.title | 一套將網頁表格資料對映至知識本體的方法 | zh_TW |
| dc.title | A Semi-Automatic Approach for Mapping Web Tables to Ontologies | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 96-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 李瑞庭,陳建錦 | |
| dc.subject.keyword | 知識本體,語意網,網路服務,知識本體語言,資訊檢索, | zh_TW |
| dc.subject.keyword | Ontology,OWL,Mapping,Information Extraction,Web Table, | en |
| dc.relation.page | 70 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2008-07-29 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
| 顯示於系所單位： | 資訊管理學系 | |
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|---|---|---|---|
| ntu-97-1.pdf 未授權公開取用 | 4.6 MB | Adobe PDF |
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