AMiner: Search and Mining of Academic Social Networks
AMiner is a novel online academic search and mining system, and it aims to provide a systematic modeling approach to help researchers and scientists gain a deeper understanding of the large and heterogeneous networks formed by authors, papers, conferences, journals and organizations. The system is s...
Gespeichert in:
| Veröffentlicht in: | Data intelligence 2019-03, Vol.1 (1), p.58-76 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 76 |
|---|---|
| container_issue | 1 |
| container_start_page | 58 |
| container_title | Data intelligence |
| container_volume | 1 |
| creator | Wan, Huaiyu Zhang, Yutao Zhang, Jing Tang, Jie |
| description | AMiner is a novel online academic search and mining system, and it aims to provide a systematic modeling approach to help researchers and scientists gain a deeper understanding of the large and heterogeneous networks formed by authors, papers, conferences, journals and organizations. The system is subsequently able to extract researchers’ profiles automatically from the Web and integrates them with published papers by a way of a process that first performs name disambiguation. Then a generative probabilistic model is devised to simultaneously model the different entities while providing a topic-level expertise search. In addition, AMiner offers a set of researcher-centered functions, including social influence analysis, relationship mining, collaboration recommendation, similarity analysis, and community evolution. The system has been in operation since 2006 and has been accessed from more than 8 million independent IP addresses residing in more than 200 countries and regions. |
| doi_str_mv | 10.1162/dint_a_00006 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1162_dint_a_00006</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2890967253</sourcerecordid><originalsourceid>FETCH-LOGICAL-c390t-c933902477975a5631070b50b425539ba56241aeaaf7d8b714bcb9bf142432813</originalsourceid><addsrcrecordid>eNp1kEtLAzEUhYMoWLQ7f0DAjQtHc_OYNG6kFF9QdVEFdyHJZDS1nanJVNFfb0pdVNC7OZfDd8-Fg9ABkBOAkp5Woem00SRPuYV6tORQcCaetjf2XdRPaZoJCiUoLnpIDG9D4-MZnngT3Qs2TYWzE5pn3NZ46Ezl58HhSeuCmeE733208TXto53azJLv_-geery8eBhdF-P7q5vRcFw4pkhXOMWyUi6lksKIkgGRxApiORWCKZstysF4Y2pZDawEbp1VtgZOOaMDYHvocJ27iO3b0qdOT9tlbPJLTQeKqFJSwTJ1vKZcbFOKvtaLGOYmfmogetWN3uwm40drfB428v5Bz_9AV8g7BNCM0JIpTXOd-VgTpb_C4nfCN8Rmdow</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2890967253</pqid></control><display><type>article</type><title>AMiner: Search and Mining of Academic Social Networks</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Alma/SFX Local Collection</source><source>ProQuest Central</source><creator>Wan, Huaiyu ; Zhang, Yutao ; Zhang, Jing ; Tang, Jie</creator><creatorcontrib>Wan, Huaiyu ; Zhang, Yutao ; Zhang, Jing ; Tang, Jie</creatorcontrib><description>AMiner is a novel online academic search and mining system, and it aims to provide a systematic modeling approach to help researchers and scientists gain a deeper understanding of the large and heterogeneous networks formed by authors, papers, conferences, journals and organizations. The system is subsequently able to extract researchers’ profiles automatically from the Web and integrates them with published papers by a way of a process that first performs name disambiguation. Then a generative probabilistic model is devised to simultaneously model the different entities while providing a topic-level expertise search. In addition, AMiner offers a set of researcher-centered functions, including social influence analysis, relationship mining, collaboration recommendation, similarity analysis, and community evolution. The system has been in operation since 2006 and has been accessed from more than 8 million independent IP addresses residing in more than 200 countries and regions.</description><identifier>ISSN: 2641-435X</identifier><identifier>EISSN: 2641-435X</identifier><identifier>DOI: 10.1162/dint_a_00006</identifier><language>eng</language><publisher>One Rogers Street, Cambridge, MA 02142-1209, USA: MIT Press</publisher><subject>Academic publications ; Academic social networks ; Data mining ; Expertise Search ; Information sources ; Machine learning ; Name disambiguation ; Network mining ; Probabilistic models ; Profile extraction ; Researchers ; Search engines ; Searching ; Semantic analysis ; Semantics ; Social network analysis ; Social networks ; Topic modeling ; User profiles</subject><ispartof>Data intelligence, 2019-03, Vol.1 (1), p.58-76</ispartof><rights>2019. This work is published under https://creativecommons.org/licenses/by/4.0/legalcode (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c390t-c933902477975a5631070b50b425539ba56241aeaaf7d8b714bcb9bf142432813</citedby><cites>FETCH-LOGICAL-c390t-c933902477975a5631070b50b425539ba56241aeaaf7d8b714bcb9bf142432813</cites><orcidid>0000-0002-6882-4044</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2890967253?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,21367,27901,27902,33721,43781</link.rule.ids></links><search><creatorcontrib>Wan, Huaiyu</creatorcontrib><creatorcontrib>Zhang, Yutao</creatorcontrib><creatorcontrib>Zhang, Jing</creatorcontrib><creatorcontrib>Tang, Jie</creatorcontrib><title>AMiner: Search and Mining of Academic Social Networks</title><title>Data intelligence</title><description>AMiner is a novel online academic search and mining system, and it aims to provide a systematic modeling approach to help researchers and scientists gain a deeper understanding of the large and heterogeneous networks formed by authors, papers, conferences, journals and organizations. The system is subsequently able to extract researchers’ profiles automatically from the Web and integrates them with published papers by a way of a process that first performs name disambiguation. Then a generative probabilistic model is devised to simultaneously model the different entities while providing a topic-level expertise search. In addition, AMiner offers a set of researcher-centered functions, including social influence analysis, relationship mining, collaboration recommendation, similarity analysis, and community evolution. The system has been in operation since 2006 and has been accessed from more than 8 million independent IP addresses residing in more than 200 countries and regions.</description><subject>Academic publications</subject><subject>Academic social networks</subject><subject>Data mining</subject><subject>Expertise Search</subject><subject>Information sources</subject><subject>Machine learning</subject><subject>Name disambiguation</subject><subject>Network mining</subject><subject>Probabilistic models</subject><subject>Profile extraction</subject><subject>Researchers</subject><subject>Search engines</subject><subject>Searching</subject><subject>Semantic analysis</subject><subject>Semantics</subject><subject>Social network analysis</subject><subject>Social networks</subject><subject>Topic modeling</subject><subject>User profiles</subject><issn>2641-435X</issn><issn>2641-435X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kEtLAzEUhYMoWLQ7f0DAjQtHc_OYNG6kFF9QdVEFdyHJZDS1nanJVNFfb0pdVNC7OZfDd8-Fg9ABkBOAkp5Woem00SRPuYV6tORQcCaetjf2XdRPaZoJCiUoLnpIDG9D4-MZnngT3Qs2TYWzE5pn3NZ46Ezl58HhSeuCmeE733208TXto53azJLv_-geery8eBhdF-P7q5vRcFw4pkhXOMWyUi6lksKIkgGRxApiORWCKZstysF4Y2pZDawEbp1VtgZOOaMDYHvocJ27iO3b0qdOT9tlbPJLTQeKqFJSwTJ1vKZcbFOKvtaLGOYmfmogetWN3uwm40drfB428v5Bz_9AV8g7BNCM0JIpTXOd-VgTpb_C4nfCN8Rmdow</recordid><startdate>20190301</startdate><enddate>20190301</enddate><creator>Wan, Huaiyu</creator><creator>Zhang, Yutao</creator><creator>Zhang, Jing</creator><creator>Tang, Jie</creator><general>MIT Press</general><general>MIT Press Journals, The</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L6V</scope><scope>M7S</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><orcidid>https://orcid.org/0000-0002-6882-4044</orcidid></search><sort><creationdate>20190301</creationdate><title>AMiner: Search and Mining of Academic Social Networks</title><author>Wan, Huaiyu ; Zhang, Yutao ; Zhang, Jing ; Tang, Jie</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c390t-c933902477975a5631070b50b425539ba56241aeaaf7d8b714bcb9bf142432813</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Academic publications</topic><topic>Academic social networks</topic><topic>Data mining</topic><topic>Expertise Search</topic><topic>Information sources</topic><topic>Machine learning</topic><topic>Name disambiguation</topic><topic>Network mining</topic><topic>Probabilistic models</topic><topic>Profile extraction</topic><topic>Researchers</topic><topic>Search engines</topic><topic>Searching</topic><topic>Semantic analysis</topic><topic>Semantics</topic><topic>Social network analysis</topic><topic>Social networks</topic><topic>Topic modeling</topic><topic>User profiles</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wan, Huaiyu</creatorcontrib><creatorcontrib>Zhang, Yutao</creatorcontrib><creatorcontrib>Zhang, Jing</creatorcontrib><creatorcontrib>Tang, Jie</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><jtitle>Data intelligence</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wan, Huaiyu</au><au>Zhang, Yutao</au><au>Zhang, Jing</au><au>Tang, Jie</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>AMiner: Search and Mining of Academic Social Networks</atitle><jtitle>Data intelligence</jtitle><date>2019-03-01</date><risdate>2019</risdate><volume>1</volume><issue>1</issue><spage>58</spage><epage>76</epage><pages>58-76</pages><issn>2641-435X</issn><eissn>2641-435X</eissn><abstract>AMiner is a novel online academic search and mining system, and it aims to provide a systematic modeling approach to help researchers and scientists gain a deeper understanding of the large and heterogeneous networks formed by authors, papers, conferences, journals and organizations. The system is subsequently able to extract researchers’ profiles automatically from the Web and integrates them with published papers by a way of a process that first performs name disambiguation. Then a generative probabilistic model is devised to simultaneously model the different entities while providing a topic-level expertise search. In addition, AMiner offers a set of researcher-centered functions, including social influence analysis, relationship mining, collaboration recommendation, similarity analysis, and community evolution. The system has been in operation since 2006 and has been accessed from more than 8 million independent IP addresses residing in more than 200 countries and regions.</abstract><cop>One Rogers Street, Cambridge, MA 02142-1209, USA</cop><pub>MIT Press</pub><doi>10.1162/dint_a_00006</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0002-6882-4044</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2641-435X |
| ispartof | Data intelligence, 2019-03, Vol.1 (1), p.58-76 |
| issn | 2641-435X 2641-435X |
| language | eng |
| recordid | cdi_crossref_primary_10_1162_dint_a_00006 |
| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Alma/SFX Local Collection; ProQuest Central |
| subjects | Academic publications Academic social networks Data mining Expertise Search Information sources Machine learning Name disambiguation Network mining Probabilistic models Profile extraction Researchers Search engines Searching Semantic analysis Semantics Social network analysis Social networks Topic modeling User profiles |
| title | AMiner: Search and Mining of Academic Social Networks |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-03T21%3A10%3A00IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=AMiner:%20Search%20and%20Mining%20of%20Academic%20Social%20Networks&rft.jtitle=Data%20intelligence&rft.au=Wan,%20Huaiyu&rft.date=2019-03-01&rft.volume=1&rft.issue=1&rft.spage=58&rft.epage=76&rft.pages=58-76&rft.issn=2641-435X&rft.eissn=2641-435X&rft_id=info:doi/10.1162/dint_a_00006&rft_dat=%3Cproquest_cross%3E2890967253%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2890967253&rft_id=info:pmid/&rfr_iscdi=true |