Mining latent entity structures:
The 'big data' era is characterized by an explosion of information in the form of digital data collections, ranging from scientific knowledge, to social media, news, and everyone's daily life. Examples of such collections include scientific publications, enterprise logs, news articles...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
[San Rafael, California]
Morgan & Claypool Publishers
[2015]
|
| Series: | Synthesis lectures on data mining and knowledge discovery
#10 |
| Subjects: | |
| Online Access: | UER01 Volltext |
| Summary: | The 'big data' era is characterized by an explosion of information in the form of digital data collections, ranging from scientific knowledge, to social media, news, and everyone's daily life. Examples of such collections include scientific publications, enterprise logs, news articles, social media, and general web pages. Valuable knowledge about multi-typed entities is often hidden in the unstructured or loosely structured, interconnected data. Mining latent structures around entities uncovers hidden knowledge such as implicit topics, phrases, entity roles and relationships. In this monograph, we investigate the principles and methodologies of mining latent entity structures from massive unstructured and interconnected data. We propose a text-rich information network model for modeling data in many different domains. This leads to a series of new principles and powerful methodologies for mining latent structures, including (1) latent topical hierarchy, (2) quality topical phrases, (3) entity roles in hierarchical topical communities, and (4) entity relations. This book also introduces applications enabled by the mined structures and points out some promising research directions |
| Item Description: | Part of: Synthesis digital library of engineering and computer science. - Includes bibliographical references (pages 141-145) |
| Physical Description: | Online-Ressource (xi, 147 pages) illustrations |
| ISBN: | 9781627056618 |
| DOI: | 10.2200/S00625ED1V01Y201502DMK010 |
Staff View
MARC
| LEADER | 00000nmm a22000001cb4500 | ||
|---|---|---|---|
| 001 | BV044756667 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 180212s2015 |||| o||u| ||||||eng d | ||
| 020 | |a 9781627056618 |c ebook |9 978-1-62705-661-8 | ||
| 024 | 7 | |a 10.2200/S00625ED1V01Y201502DMK010 |2 doi | |
| 035 | |a (OCoLC)1024133734 | ||
| 035 | |a (DE-599)BSZ469714883 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-29 | ||
| 050 | 0 | |a QA76.9.D343 | |
| 082 | 0 | |a 006.312 | |
| 100 | 1 | |a Wang, Chi |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Mining latent entity structures |c Chi Wang (Microsoft Research), Jiawei Han (University of Illinois at Urbana-Champaign) |
| 264 | 1 | |a [San Rafael, California] |b Morgan & Claypool Publishers |c [2015] | |
| 264 | 4 | |c © 2015 | |
| 300 | |a Online-Ressource (xi, 147 pages) |b illustrations | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 1 | |a Synthesis lectures on data mining and knowledge discovery |v #10 | |
| 500 | |a Part of: Synthesis digital library of engineering and computer science. - Includes bibliographical references (pages 141-145) | ||
| 520 | 3 | |a The 'big data' era is characterized by an explosion of information in the form of digital data collections, ranging from scientific knowledge, to social media, news, and everyone's daily life. Examples of such collections include scientific publications, enterprise logs, news articles, social media, and general web pages. Valuable knowledge about multi-typed entities is often hidden in the unstructured or loosely structured, interconnected data. Mining latent structures around entities uncovers hidden knowledge such as implicit topics, phrases, entity roles and relationships. In this monograph, we investigate the principles and methodologies of mining latent entity structures from massive unstructured and interconnected data. We propose a text-rich information network model for modeling data in many different domains. This leads to a series of new principles and powerful methodologies for mining latent structures, including (1) latent topical hierarchy, (2) quality topical phrases, (3) entity roles in hierarchical topical communities, and (4) entity relations. This book also introduces applications enabled by the mined structures and points out some promising research directions | |
| 653 | 0 | |a Data mining | |
| 653 | 0 | |a Latent structure analysis | |
| 700 | 1 | |a Han, Jiawei |d 1949- |e Verfasser |0 (DE-588)137798342 |4 aut | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe, Paperback |z 978-1-62705-660-1 |
| 830 | 0 | |a Synthesis lectures on data mining and knowledge discovery |v #10 |w (DE-604)BV044754814 |9 10 | |
| 856 | 4 | 0 | |u https://doi.org/10.2200/S00625ED1V01Y201502DMK010 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-105-MCB |a ZDB-105-MCS | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-030152178 | ||
| 966 | e | |u https://doi.org/10.2200/S00625ED1V01Y201502DMK010 |l UER01 |p ZDB-105-MCB |q UER_Einzelkauf |x Verlag |3 Volltext | |
Record in the Search Index
| _version_ | 1804178274087075840 |
|---|---|
| any_adam_object | |
| author | Wang, Chi Han, Jiawei 1949- |
| author_GND | (DE-588)137798342 |
| author_facet | Wang, Chi Han, Jiawei 1949- |
| author_role | aut aut |
| author_sort | Wang, Chi |
| author_variant | c w cw j h jh |
| building | Verbundindex |
| bvnumber | BV044756667 |
| callnumber-first | Q - Science |
| callnumber-label | QA76 |
| callnumber-raw | QA76.9.D343 |
| callnumber-search | QA76.9.D343 |
| callnumber-sort | QA 276.9 D343 |
| callnumber-subject | QA - Mathematics |
| collection | ZDB-105-MCB ZDB-105-MCS |
| ctrlnum | (OCoLC)1024133734 (DE-599)BSZ469714883 |
| dewey-full | 006.312 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.312 |
| dewey-search | 006.312 |
| dewey-sort | 16.312 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| doi_str_mv | 10.2200/S00625ED1V01Y201502DMK010 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03012nmm a22004331cb4500</leader><controlfield tag="001">BV044756667</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">180212s2015 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781627056618</subfield><subfield code="c">ebook</subfield><subfield code="9">978-1-62705-661-8</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.2200/S00625ED1V01Y201502DMK010</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1024133734</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BSZ469714883</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-29</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QA76.9.D343</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.312</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Wang, Chi</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Mining latent entity structures</subfield><subfield code="c">Chi Wang (Microsoft Research), Jiawei Han (University of Illinois at Urbana-Champaign)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">[San Rafael, California]</subfield><subfield code="b">Morgan & Claypool Publishers</subfield><subfield code="c">[2015]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2015</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">Online-Ressource (xi, 147 pages)</subfield><subfield code="b">illustrations</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="1" ind2=" "><subfield code="a">Synthesis lectures on data mining and knowledge discovery</subfield><subfield code="v">#10</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Part of: Synthesis digital library of engineering and computer science. - Includes bibliographical references (pages 141-145)</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">The 'big data' era is characterized by an explosion of information in the form of digital data collections, ranging from scientific knowledge, to social media, news, and everyone's daily life. Examples of such collections include scientific publications, enterprise logs, news articles, social media, and general web pages. Valuable knowledge about multi-typed entities is often hidden in the unstructured or loosely structured, interconnected data. Mining latent structures around entities uncovers hidden knowledge such as implicit topics, phrases, entity roles and relationships. In this monograph, we investigate the principles and methodologies of mining latent entity structures from massive unstructured and interconnected data. We propose a text-rich information network model for modeling data in many different domains. This leads to a series of new principles and powerful methodologies for mining latent structures, including (1) latent topical hierarchy, (2) quality topical phrases, (3) entity roles in hierarchical topical communities, and (4) entity relations. This book also introduces applications enabled by the mined structures and points out some promising research directions</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Data mining</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Latent structure analysis</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Han, Jiawei</subfield><subfield code="d">1949-</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)137798342</subfield><subfield code="4">aut</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe, Paperback</subfield><subfield code="z">978-1-62705-660-1</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Synthesis lectures on data mining and knowledge discovery</subfield><subfield code="v">#10</subfield><subfield code="w">(DE-604)BV044754814</subfield><subfield code="9">10</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.2200/S00625ED1V01Y201502DMK010</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-105-MCB</subfield><subfield code="a">ZDB-105-MCS</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-030152178</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.2200/S00625ED1V01Y201502DMK010</subfield><subfield code="l">UER01</subfield><subfield code="p">ZDB-105-MCB</subfield><subfield code="q">UER_Einzelkauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV044756667 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T08:01:21Z |
| institution | BVB |
| isbn | 9781627056618 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030152178 |
| oclc_num | 1024133734 |
| open_access_boolean | |
| owner | DE-29 |
| owner_facet | DE-29 |
| physical | Online-Ressource (xi, 147 pages) illustrations |
| psigel | ZDB-105-MCB ZDB-105-MCS ZDB-105-MCB UER_Einzelkauf |
| publishDate | 2015 |
| publishDateSearch | 2015 |
| publishDateSort | 2015 |
| publisher | Morgan & Claypool Publishers |
| record_format | marc |
| series | Synthesis lectures on data mining and knowledge discovery |
| series2 | Synthesis lectures on data mining and knowledge discovery |
| spelling | Wang, Chi Verfasser aut Mining latent entity structures Chi Wang (Microsoft Research), Jiawei Han (University of Illinois at Urbana-Champaign) [San Rafael, California] Morgan & Claypool Publishers [2015] © 2015 Online-Ressource (xi, 147 pages) illustrations txt rdacontent c rdamedia cr rdacarrier Synthesis lectures on data mining and knowledge discovery #10 Part of: Synthesis digital library of engineering and computer science. - Includes bibliographical references (pages 141-145) The 'big data' era is characterized by an explosion of information in the form of digital data collections, ranging from scientific knowledge, to social media, news, and everyone's daily life. Examples of such collections include scientific publications, enterprise logs, news articles, social media, and general web pages. Valuable knowledge about multi-typed entities is often hidden in the unstructured or loosely structured, interconnected data. Mining latent structures around entities uncovers hidden knowledge such as implicit topics, phrases, entity roles and relationships. In this monograph, we investigate the principles and methodologies of mining latent entity structures from massive unstructured and interconnected data. We propose a text-rich information network model for modeling data in many different domains. This leads to a series of new principles and powerful methodologies for mining latent structures, including (1) latent topical hierarchy, (2) quality topical phrases, (3) entity roles in hierarchical topical communities, and (4) entity relations. This book also introduces applications enabled by the mined structures and points out some promising research directions Data mining Latent structure analysis Han, Jiawei 1949- Verfasser (DE-588)137798342 aut Erscheint auch als Druck-Ausgabe, Paperback 978-1-62705-660-1 Synthesis lectures on data mining and knowledge discovery #10 (DE-604)BV044754814 10 https://doi.org/10.2200/S00625ED1V01Y201502DMK010 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Wang, Chi Han, Jiawei 1949- Mining latent entity structures Synthesis lectures on data mining and knowledge discovery |
| title | Mining latent entity structures |
| title_auth | Mining latent entity structures |
| title_exact_search | Mining latent entity structures |
| title_full | Mining latent entity structures Chi Wang (Microsoft Research), Jiawei Han (University of Illinois at Urbana-Champaign) |
| title_fullStr | Mining latent entity structures Chi Wang (Microsoft Research), Jiawei Han (University of Illinois at Urbana-Champaign) |
| title_full_unstemmed | Mining latent entity structures Chi Wang (Microsoft Research), Jiawei Han (University of Illinois at Urbana-Champaign) |
| title_short | Mining latent entity structures |
| title_sort | mining latent entity structures |
| url | https://doi.org/10.2200/S00625ED1V01Y201502DMK010 |
| volume_link | (DE-604)BV044754814 |
| work_keys_str_mv | AT wangchi mininglatententitystructures AT hanjiawei mininglatententitystructures |