New Frontiers in Mining Complex Patterns  8th International Workshop, NFMCP 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers /  [electronic resource] : 
edited by Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew Ras. 
 - 1st ed. 2020. 
 - XII, 155 p. 111 illus., 33 illus. in color.  online resource. 
 - Lecture Notes in Artificial Intelligence,  11948  2945-9141 ; .
 - Lecture Notes in Artificial Intelligence,  11948 .
<br/><br/>A Framework for Pattern Mining and Anomaly Detection in Multi-Dimensional Time Series and Event Logs -- A Heuristic Approach for Sensitive Pattern Hiding with Improved Data Quality -- Interpretable Survival Gradient Boosting Models with Bagged Trees Base Learners -- Neural Hybrid Recommender: Recommendation Needs Collaboration -- Discovering Discriminative Nodes for Classification with Deep Graph Convolutional Methods -- Soft Voting Windowing Ensembles for Learning from Partially Labelled Streams -- Disentangling Aspect and Opinion Words in Sentiment Analysis Using Lifelong PU Learning -- Customer Purchase Behavior Prediction in E-commerce: A Conceptual Framework and Research Agenda -- Hough Transform as a Tool for the Classification of Vehicle Speed Changes in on-road Audio Recordings. 
<br/><br/> This book constitutes the refereed post-conference proceedings of the 8th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2019, held in conjunction with ECML-PKDD 2019 in Würzburg, Germany, in September 2019. The workshop focused on the latest developments in the analysis of complex and massive data sources, such as blogs, event or log data, medical data, spatio-temporal data, social networks, mobility data, sensor data and streams. 
<br/><br/><label>ISBN: </label>9783030488611 
<br/><br/><label>Standard No.: </label>10.1007/978-3-030-48861-1  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Artificial intelligence.<br/>Data mining.<br/>Computer networks .<br/>Computer systems.<br/>Application software.<br/>Education--Data processing.<br/>Artificial Intelligence.<br/>Data Mining and Knowledge Discovery.<br/>Computer Communication Networks.<br/>Computer System Implementation.<br/>Computer and Information Systems Applications.<br/>Computers and Education.
<br/><br/><label>LC Class. No.: </label>Q334-342 TA347.A78 
<br/><br/><label>Dewey Class. No.: </label>006.3