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000914750 020__ $$a9783030261429$$q(electronic book)
000914750 020__ $$a3030261425$$q(electronic book)
000914750 020__ $$z9783030261412
000914750 0247_ $$a10.1007/978-3-030-26142-9$$2doi
000914750 035__ $$aSP(OCoLC)on1120721569
000914750 035__ $$aSP(OCoLC)1120721569
000914750 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dUKMGB$$dOCLCF$$dOCLCO$$dEBLCP
000914750 049__ $$aISEA
000914750 050_4 $$aQA76.9.D343
000914750 08204 $$a006.3/12$$223
000914750 1112_ $$aPAKDD (Conference)$$n(23rd :$$d2019 :$$cMacau, China)
000914750 24510 $$aTrends and Applications in Knowledge Discovery and Data Mining :$$bPAKDD 2019 Workshops, BDM, DLKT, LDRC, PAISI, WeL, Macau, China, April 14-17, 2019, revised selected papers /$$cLeong Hou U., Hady W. Lauw (eds.).
000914750 264_1 $$aCham, Switzerland :$$bSpringer,$$c2019.
000914750 300__ $$a1 online resource (xiii, 366 pages) :$$billustrations.
000914750 336__ $$atext$$btxt$$2rdacontent
000914750 337__ $$acomputer$$bc$$2rdamedia
000914750 338__ $$aonline resource$$bcr$$2rdacarrier
000914750 4901_ $$aLecture notes in artificial intelligence
000914750 4901_ $$aLecture notes in computer science ;$$v11607
000914750 4901_ $$aLNCS sublibrary. SL 7, Artificial intelligence
000914750 500__ $$aIncludes author index.
000914750 5050_ $$aIntro; Preface; Organization; Contents; The 14th Pacific Asia Workshop on Intelligence and Security Informatics (PAISI 2019); A Supporting Tool for IT System Security Specification Evaluation Based on ISO/IEC 15408 and ISO/IEC 18045; 1 Introduction; 2 Security Target and Its Evaluation Process; 2.1 Security Target with ISO/IEC 15408; 2.2 Evaluation Process Based on ISO/IEC 18045; 2.3 Issues of the Evaluation Process; 3 Supporting Methods for Evaluation on Security Targets; 3.1 Analysis of Evaluation Tasks on Security Targets; 3.2 Supporting Methods
000914750 5058_ $$a4 Security Target Evaluator: A Supporting Tool for Evaluation on Security Targets4.1 Requirements for Security Target Evaluator; 4.2 Components for Supporting Methods in Security Target Evaluator; 4.3 Management of Relevant Documents and Data; 5 Concluding Remarks; References; An Investigation on Multi View Based User Behavior Towards Spam Detection in Social Networks; Abstract; 1 Introduction; 2 Related Work; 3 Hypothesis; 4 Approach and Experimental Setup; 4.1 Dataset Description; 4.2 Representation of User's Content Interest for the Investigation
000914750 5058_ $$a4.3 Representation of User's Popularity for the Investigation4.4 Experimental Methods for User Behavior Analysis; 5 Discussion; 6 Conclusion; References; A Cluster Ensemble Strategy for Asian Handicap Betting; 1 Introduction; 2 Related Works; 3 Methodology; 3.1 Expected Goal Difference Trend; 3.2 Model Design; 3.3 Component Cluster; 3.4 Cluster Ensemble; 4 Case Studies; 4.1 Data; 4.2 Evaluation Metrics; 4.3 Model Parameters Selection; 4.4 Out of Sample Prediction; 5 Conclusions; References; Designing an Integrated Intelligence Center: New Taipei City Police Department as an Example; Abstract
000914750 5058_ $$a1 Introduction2 Literature Review; 3 Method; 3.1 Discovery; 3.2 Understanding; 3.3 Implementation; 3.3.1 Query Service; 3.3.2 Crime Information Analysis; 3.3.3 Applied System Q 3.3.4 Image Analysis Service; 3.3.5 Real-Time Video and Image Transmission; 3.3.6 Internet Information Collection; 4 Discussion and Future Work; 5 Conclusion; References; Early Churn User Classification in Social Networking Service Using Attention-Based Long Short-Term Memory; 1 Introduction; 2 Data; 2.1 RoomClip; 2.2 Definition of Early Churn Users in RoomClip; 2.3 Distribution of Event Interval of New Users
000914750 5058_ $$a3 Proposed Model3.1 Input; 3.2 Sequence Encoding Layer; 3.3 Attention Layer; 3.4 Early Churn Classification Layer; 3.5 Learning Algorithm; 4 Experiment; 4.1 Evaluation Criteria; 4.2 Preprocessing; 4.3 Baseline Models; 4.4 Result; 5 Feature Importance Analysis; 5.1 Importance of Each Temporal Part in Event Sequence; 5.2 Importance of Event Type; 6 Related Research; 7 Discussion and Conclusion; References; PAKDD 2019 Workshop on Weakly Supervised Learning: Progress and Future (WeL 2019); Weakly Supervised Learning by a Confusion Matrix of Contexts; Abstract; 1 Introduction
000914750 506__ $$aAccess limited to authorized users.
000914750 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed September 23, 2019).
000914750 650_0 $$aData mining$$vCongresses.
000914750 7001_ $$aU., Leong Hou,$$eeditor.
000914750 7001_ $$aLauw, Hady W.$$eeditor.
000914750 7112_ $$aBDM (Workshop)$$n(8th :$$d2019 :$$cMacau, China),$$jjointly held conference.
000914750 7112_ $$aDLKT (Workshop)$$n(1st :$$d2019 :$$cMacau, China),$$jjointly held conference.
000914750 7112_ $$aLDRC (Workshop)$$d(2019 :$$cMacau, China),$$jjointly held conference.
000914750 7112_ $$aPAISI (Workshop)$$n(14th :$$d2019 :$$cMacau, China),$$jjointly held conference.
000914750 7112_ $$aInternational Workshop on Wind Energy and Landscape$$d(1997 :$$cGenoa, Italy),$$jjointly held conference.
000914750 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
000914750 830_0 $$aLecture notes in computer science ;$$v11607.
000914750 830_0 $$aLNCS sublibrary.$$nSL 7,$$pArtificial intelligence.
000914750 852__ $$bebk
000914750 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-26142-9$$zOnline Access$$91397441.1
000914750 909CO $$ooai:library.usi.edu:914750$$pGLOBAL_SET
000914750 980__ $$aEBOOK
000914750 980__ $$aBIB
000914750 982__ $$aEbook
000914750 983__ $$aOnline
000914750 994__ $$a92$$bISE