Gathering meta-data and instances from object referral lists on the web
Purpose - The purpose of this research is to automatically separate and extract meta-data and instance information from various link pages in the web, by utilizing presentation and linkage regularities on the web.Design methodology approach - Research objectives have been achieved through an informa...
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| Veröffentlicht in: | Online information review 2006-01, Vol.30 (3), p.278-296 |
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| creator | Vadrevu, Srinivas Gelgi, Fatih Nagarajan, Saravanakumar Davulcu, Hasan |
| description | Purpose - The purpose of this research is to automatically separate and extract meta-data and instance information from various link pages in the web, by utilizing presentation and linkage regularities on the web.Design methodology approach - Research objectives have been achieved through an information extraction system called semantic partitioner that automatically organizes the content in each web page into a hierarchical structure, and an algorithm that interprets and translates these hierarchical structures into logical statements by distinguishing and representing the meta-data and their individual data instances.Findings - Experimental results for the university domain with 12 computer science department web sites, comprising 361 individual faculty and course home pages indicate that the performance of the meta-data and instance extraction averages 85, 88 percent F-measure, respectively. Our METEOR system achieves this performance without any domain specific engineering requirement.Originality value - Important contributions of the METEOR system presented in this paper are: it performs extraction without the assumption that the object instance pages are template-driven; it is domain independent and does not require any previously engineered domain ontology; and by interpreting the link pages, it can extract both meta-data, such as concept and attribute names and their relationships, as well as their instances with high accuracy. |
| doi_str_mv | 10.1108/14684520610675807 |
| format | Article |
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Our METEOR system achieves this performance without any domain specific engineering requirement.Originality value - Important contributions of the METEOR system presented in this paper are: it performs extraction without the assumption that the object instance pages are template-driven; it is domain independent and does not require any previously engineered domain ontology; and by interpreting the link pages, it can extract both meta-data, such as concept and attribute names and their relationships, as well as their instances with high accuracy.</description><identifier>ISSN: 1468-4527</identifier><identifier>EISSN: 1468-4535</identifier><identifier>DOI: 10.1108/14684520610675807</identifier><language>eng</language><publisher>Bradford: Emerald Group Publishing Limited</publisher><subject>Algorithms ; Arizona ; Arizona University ; Computer science ; Directories ; Information Retrieval ; Information Services ; Information Sources ; Mathematics ; Metadata ; METEOR ; Online information retrieval ; Referral ; Searching ; Semantics ; Semiotics ; Universities ; USA ; Web sites ; World Wide Web</subject><ispartof>Online information review, 2006-01, Vol.30 (3), p.278-296</ispartof><rights>Emerald Group Publishing Limited</rights><rights>Copyright Emerald Group Publishing Limited 2006</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c443t-cb9fe70aed4ac3dce8b691fd21f279807a200f546691a547da459989241b559e3</citedby><cites>FETCH-LOGICAL-c443t-cb9fe70aed4ac3dce8b691fd21f279807a200f546691a547da459989241b559e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.emerald.com/insight/content/doi/10.1108/14684520610675807/full/pdf$$EPDF$$P50$$Gemerald$$H</linktopdf><linktohtml>$$Uhttps://www.emerald.com/insight/content/doi/10.1108/14684520610675807/full/html$$EHTML$$P50$$Gemerald$$H</linktohtml><link.rule.ids>314,780,784,967,11635,21695,27924,27925,52686,52689,53244,53372</link.rule.ids></links><search><contributor>Sicilia, Miguel‐Angel</contributor><creatorcontrib>Vadrevu, Srinivas</creatorcontrib><creatorcontrib>Gelgi, Fatih</creatorcontrib><creatorcontrib>Nagarajan, Saravanakumar</creatorcontrib><creatorcontrib>Davulcu, Hasan</creatorcontrib><title>Gathering meta-data and instances from object referral lists on the web</title><title>Online information review</title><description>Purpose - The purpose of this research is to automatically separate and extract meta-data and instance information from various link pages in the web, by utilizing presentation and linkage regularities on the web.Design methodology approach - Research objectives have been achieved through an information extraction system called semantic partitioner that automatically organizes the content in each web page into a hierarchical structure, and an algorithm that interprets and translates these hierarchical structures into logical statements by distinguishing and representing the meta-data and their individual data instances.Findings - Experimental results for the university domain with 12 computer science department web sites, comprising 361 individual faculty and course home pages indicate that the performance of the meta-data and instance extraction averages 85, 88 percent F-measure, respectively. 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| ispartof | Online information review, 2006-01, Vol.30 (3), p.278-296 |
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| language | eng |
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| source | Emerald A-Z Current Journals; Standard: Emerald eJournal Premier Collection |
| subjects | Algorithms Arizona Arizona University Computer science Directories Information Retrieval Information Services Information Sources Mathematics Metadata METEOR Online information retrieval Referral Searching Semantics Semiotics Universities USA Web sites World Wide Web |
| title | Gathering meta-data and instances from object referral lists on the web |
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