Reasoning Techniques for the Web of Data:
Linked Data publishing has brought about a novel "Web of Data": a wealth of diverse, interlinked, structured data published on the Web. These Linked Datasets are described using the Semantic Web standards and are openly available to all, produced by governments, businesses, communities and...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Burke
IOS Press
2014
|
| Schriftenreihe: | Studies on the Semantic Web
v.19 |
| Schlagworte: | |
| Online-Zugang: | KUBA1 |
| Zusammenfassung: | Linked Data publishing has brought about a novel "Web of Data": a wealth of diverse, interlinked, structured data published on the Web. These Linked Datasets are described using the Semantic Web standards and are openly available to all, produced by governments, businesses, communities and academia alike. However, the heterogeneity of such data - in terms of how resources are described and identified - poses major challenges to potential consumers. Herein, we examine use cases for pragmatic, lightweight reasoning techniques that leverage Web vocabularies (described in RDFS and OWL) to better integrate large scale, diverse, Linked Data corpora. We take a test corpus of 1.1 billion RDF statements collected from 4 million RDF Web documents and analyse the use of RDFS and OWL therein. We then detail and evaluate scalable and distributed techniques for applying rule-based materialisation to translate data between different vocabularies, and to resolve coreferent resources that talk about the same thing. We show how such techniques can be made robust in the face of noisy and often impudent Web data. We also examine a use case for incorporating a PagerRank-style algorithm to rank the trustworthiness of facts produced by reasoning, subsequently using those ranks to fix formal contradictions in the data. All of our methods are validated against our real world, large scale, open domain, Linked Data evaluation corpus |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 online resource (344 pages) |
| ISBN: | 9781614993834 9781614993827 |
Internformat
MARC
| LEADER | 00000nmm a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV043610467 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 160616s2014 |||| o||u| ||||||eng d | ||
| 020 | |a 9781614993834 |9 978-1-61499-383-4 | ||
| 020 | |a 9781614993827 |c Print |9 978-1-61499-382-7 | ||
| 035 | |a (ZDB-30-PQE)EBC1720836 | ||
| 035 | |a (ZDB-89-EBL)EBL1720836 | ||
| 035 | |a (ZDB-38-EBR)ebr10898090 | ||
| 035 | |a (OCoLC)883628292 | ||
| 035 | |a (DE-599)BVBBV043610467 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-Y3 | ||
| 082 | 0 | |a 004.65 | |
| 100 | 1 | |a Hogan, A. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Reasoning Techniques for the Web of Data |
| 264 | 1 | |a Burke |b IOS Press |c 2014 | |
| 264 | 4 | |c © 2014 | |
| 300 | |a 1 online resource (344 pages) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Studies on the Semantic Web |v v.19 | |
| 500 | |a Description based on publisher supplied metadata and other sources | ||
| 520 | |a Linked Data publishing has brought about a novel "Web of Data": a wealth of diverse, interlinked, structured data published on the Web. These Linked Datasets are described using the Semantic Web standards and are openly available to all, produced by governments, businesses, communities and academia alike. However, the heterogeneity of such data - in terms of how resources are described and identified - poses major challenges to potential consumers. Herein, we examine use cases for pragmatic, lightweight reasoning techniques that leverage Web vocabularies (described in RDFS and OWL) to better integrate large scale, diverse, Linked Data corpora. We take a test corpus of 1.1 billion RDF statements collected from 4 million RDF Web documents and analyse the use of RDFS and OWL therein. We then detail and evaluate scalable and distributed techniques for applying rule-based materialisation to translate data between different vocabularies, and to resolve coreferent resources that talk about the same thing. We show how such techniques can be made robust in the face of noisy and often impudent Web data. We also examine a use case for incorporating a PagerRank-style algorithm to rank the trustworthiness of facts produced by reasoning, subsequently using those ranks to fix formal contradictions in the data. All of our methods are validated against our real world, large scale, open domain, Linked Data evaluation corpus | ||
| 650 | 4 | |a Künstliche Intelligenz | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Semantic computing | |
| 650 | 0 | 7 | |a Semantic Web |0 (DE-588)4688372-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Linked Data |0 (DE-588)7863462-3 |2 gnd |9 rswk-swf |
| 655 | 7 | |8 1\p |0 (DE-588)4113937-9 |a Hochschulschrift |2 gnd-content | |
| 689 | 0 | 0 | |a Semantic Web |0 (DE-588)4688372-1 |D s |
| 689 | 0 | |8 2\p |5 DE-604 | |
| 689 | 1 | 0 | |a Linked Data |0 (DE-588)7863462-3 |D s |
| 689 | 1 | |8 3\p |5 DE-604 | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |a Hogan, A |t . Reasoning Techniques for the Web of Data |
| 912 | |a ZDB-30-PQE |a ZDB-38-ESG | ||
| 940 | 1 | |q KUBA1-ZDB-30-PAD-2023 | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-029024526 | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 883 | 1 | |8 2\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 883 | 1 | |8 3\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 966 | e | |u https://ebookcentral.proquest.com/lib/khifiit/detail.action?docID=1720836 |l KUBA1 |p ZDB-30-PAD |q KHI |x Aggregator |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804176355924901888 |
|---|---|
| any_adam_object | |
| author | Hogan, A. |
| author_facet | Hogan, A. |
| author_role | aut |
| author_sort | Hogan, A. |
| author_variant | a h ah |
| building | Verbundindex |
| bvnumber | BV043610467 |
| collection | ZDB-30-PQE ZDB-38-ESG |
| ctrlnum | (ZDB-30-PQE)EBC1720836 (ZDB-89-EBL)EBL1720836 (ZDB-38-EBR)ebr10898090 (OCoLC)883628292 (DE-599)BVBBV043610467 |
| dewey-full | 004.65 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 004 - Computer science |
| dewey-raw | 004.65 |
| dewey-search | 004.65 |
| dewey-sort | 14.65 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03544nmm a2200565zcb4500</leader><controlfield tag="001">BV043610467</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">160616s2014 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781614993834</subfield><subfield code="9">978-1-61499-383-4</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781614993827</subfield><subfield code="c">Print</subfield><subfield code="9">978-1-61499-382-7</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-30-PQE)EBC1720836</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-89-EBL)EBL1720836</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-38-EBR)ebr10898090</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)883628292</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV043610467</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-Y3</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">004.65</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hogan, A.</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Reasoning Techniques for the Web of Data</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Burke</subfield><subfield code="b">IOS Press</subfield><subfield code="c">2014</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2014</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (344 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Studies on the Semantic Web</subfield><subfield code="v">v.19</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Linked Data publishing has brought about a novel "Web of Data": a wealth of diverse, interlinked, structured data published on the Web. These Linked Datasets are described using the Semantic Web standards and are openly available to all, produced by governments, businesses, communities and academia alike. However, the heterogeneity of such data - in terms of how resources are described and identified - poses major challenges to potential consumers. Herein, we examine use cases for pragmatic, lightweight reasoning techniques that leverage Web vocabularies (described in RDFS and OWL) to better integrate large scale, diverse, Linked Data corpora. We take a test corpus of 1.1 billion RDF statements collected from 4 million RDF Web documents and analyse the use of RDFS and OWL therein. We then detail and evaluate scalable and distributed techniques for applying rule-based materialisation to translate data between different vocabularies, and to resolve coreferent resources that talk about the same thing. We show how such techniques can be made robust in the face of noisy and often impudent Web data. We also examine a use case for incorporating a PagerRank-style algorithm to rank the trustworthiness of facts produced by reasoning, subsequently using those ranks to fix formal contradictions in the data. All of our methods are validated against our real world, large scale, open domain, Linked Data evaluation corpus</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Künstliche Intelligenz</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Semantic computing</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Semantic Web</subfield><subfield code="0">(DE-588)4688372-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Linked Data</subfield><subfield code="0">(DE-588)7863462-3</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="8">1\p</subfield><subfield code="0">(DE-588)4113937-9</subfield><subfield code="a">Hochschulschrift</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Semantic Web</subfield><subfield code="0">(DE-588)4688372-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="8">2\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="1" ind2="0"><subfield code="a">Linked Data</subfield><subfield code="0">(DE-588)7863462-3</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2=" "><subfield code="8">3\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="a">Hogan, A</subfield><subfield code="t">. Reasoning Techniques for the Web of Data</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-PQE</subfield><subfield code="a">ZDB-38-ESG</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">KUBA1-ZDB-30-PAD-2023</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-029024526</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">2\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">3\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://ebookcentral.proquest.com/lib/khifiit/detail.action?docID=1720836</subfield><subfield code="l">KUBA1</subfield><subfield code="p">ZDB-30-PAD</subfield><subfield code="q">KHI</subfield><subfield code="x">Aggregator</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| genre | 1\p (DE-588)4113937-9 Hochschulschrift gnd-content |
| genre_facet | Hochschulschrift |
| id | DE-604.BV043610467 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:30:52Z |
| institution | BVB |
| isbn | 9781614993834 9781614993827 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029024526 |
| oclc_num | 883628292 |
| open_access_boolean | |
| owner | DE-Y3 |
| owner_facet | DE-Y3 |
| physical | 1 online resource (344 pages) |
| psigel | ZDB-30-PQE ZDB-38-ESG KUBA1-ZDB-30-PAD-2023 ZDB-30-PAD KHI |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| publisher | IOS Press |
| record_format | marc |
| series2 | Studies on the Semantic Web |
| spelling | Hogan, A. Verfasser aut Reasoning Techniques for the Web of Data Burke IOS Press 2014 © 2014 1 online resource (344 pages) txt rdacontent c rdamedia cr rdacarrier Studies on the Semantic Web v.19 Description based on publisher supplied metadata and other sources Linked Data publishing has brought about a novel "Web of Data": a wealth of diverse, interlinked, structured data published on the Web. These Linked Datasets are described using the Semantic Web standards and are openly available to all, produced by governments, businesses, communities and academia alike. However, the heterogeneity of such data - in terms of how resources are described and identified - poses major challenges to potential consumers. Herein, we examine use cases for pragmatic, lightweight reasoning techniques that leverage Web vocabularies (described in RDFS and OWL) to better integrate large scale, diverse, Linked Data corpora. We take a test corpus of 1.1 billion RDF statements collected from 4 million RDF Web documents and analyse the use of RDFS and OWL therein. We then detail and evaluate scalable and distributed techniques for applying rule-based materialisation to translate data between different vocabularies, and to resolve coreferent resources that talk about the same thing. We show how such techniques can be made robust in the face of noisy and often impudent Web data. We also examine a use case for incorporating a PagerRank-style algorithm to rank the trustworthiness of facts produced by reasoning, subsequently using those ranks to fix formal contradictions in the data. All of our methods are validated against our real world, large scale, open domain, Linked Data evaluation corpus Künstliche Intelligenz Artificial intelligence Semantic computing Semantic Web (DE-588)4688372-1 gnd rswk-swf Linked Data (DE-588)7863462-3 gnd rswk-swf 1\p (DE-588)4113937-9 Hochschulschrift gnd-content Semantic Web (DE-588)4688372-1 s 2\p DE-604 Linked Data (DE-588)7863462-3 s 3\p DE-604 Erscheint auch als Druck-Ausgabe Hogan, A . Reasoning Techniques for the Web of Data 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Hogan, A. Reasoning Techniques for the Web of Data Künstliche Intelligenz Artificial intelligence Semantic computing Semantic Web (DE-588)4688372-1 gnd Linked Data (DE-588)7863462-3 gnd |
| subject_GND | (DE-588)4688372-1 (DE-588)7863462-3 (DE-588)4113937-9 |
| title | Reasoning Techniques for the Web of Data |
| title_auth | Reasoning Techniques for the Web of Data |
| title_exact_search | Reasoning Techniques for the Web of Data |
| title_full | Reasoning Techniques for the Web of Data |
| title_fullStr | Reasoning Techniques for the Web of Data |
| title_full_unstemmed | Reasoning Techniques for the Web of Data |
| title_short | Reasoning Techniques for the Web of Data |
| title_sort | reasoning techniques for the web of data |
| topic | Künstliche Intelligenz Artificial intelligence Semantic computing Semantic Web (DE-588)4688372-1 gnd Linked Data (DE-588)7863462-3 gnd |
| topic_facet | Künstliche Intelligenz Artificial intelligence Semantic computing Semantic Web Linked Data Hochschulschrift |
| work_keys_str_mv | AT hogana reasoningtechniquesforthewebofdata |