LEADER 03543nam  22006615  450 
001 9910254821103321
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010   $a3-319-56212-6
024 7 $a10.1007/978-3-319-56212-4
035   $a(CKB)3710000001388720
035   $a(DE-He213)978-3-319-56212-4
035   $a(MiAaPQ)EBC4866066
035   $z(PPN)258871784
035   $a(PPN)201474026
035   $a(EXLCZ)993710000001388720
100   $a20170525d2017      u|         0
101 0 $aeng
135   $aurnn#008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aHeterogeneous Information Network Analysis and Applications /$fby Chuan Shi, Philip S. Yu
205   $a1st ed. 2017.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017.
215   $a1 online resource (IX, 227 p. 62 illus., 53 illus. in color.)
225 1 $aData Analytics,$x2520-1867
311 08$a3-319-56211-8 
320   $aIncludes bibliographical references.
327   $a1. Introduction -- 2. Summarization of the developments -- 3.Uniform relevance measure of heterogeneous objects -- 4. Path based Ranking -- 5. Ranking based Clustering -- 6. Recommendation with heterogeneous information -- 7. Information fusion with heterogeneous network -- 8. Prototype system -- 9. Future research directions -- 10. Conclusion.
330   $aThis book offers researchers an understanding of the fundamental issues and a good starting point to work on this rapidly expanding field. It provides a comprehensive survey of current developments of heterogeneous information network. It also presents the newest research in applications of heterogeneous information networks to similarity search, ranking, clustering, recommendation. This information will help researchers to understand how to analyze networked data with heterogeneous information networks. Common data mining tasks are explored, including similarity search, ranking, and recommendation. The book illustrates some prototypes which analyze networked data. Professionals and academics working in data analytics, networks, machine learning, and data mining will find this content valuable. It is also suitable for advanced-level students in computer science who are interested in networking orpattern recognition. .
410  0$aData Analytics,$x2520-1867
606   $aData mining
606   $aArtificial intelligence
606   $aPattern recognition systems
606   $aTelecommunication
606   $aComputer networks
606   $aData Mining and Knowledge Discovery
606   $aArtificial Intelligence
606   $aAutomated Pattern Recognition
606   $aCommunications Engineering, Networks
606   $aComputer Communication Networks
615  0$aData mining.
615  0$aArtificial intelligence.
615  0$aPattern recognition systems.
615  0$aTelecommunication.
615  0$aComputer networks.
615 14$aData Mining and Knowledge Discovery.
615 24$aArtificial Intelligence.
615 24$aAutomated Pattern Recognition.
615 24$aCommunications Engineering, Networks.
615 24$aComputer Communication Networks.
676   $a006.312
700   $aShi$b Chuan$4aut$4http://id.loc.gov/vocabulary/relators/aut$0964112
702   $aYu$b Philip S$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910254821103321
996   $aHeterogeneous Information Network Analysis and Applications$92535213
997   $aUNINA