Machine learning and knowledge discovery in databases : International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, proceedings.: International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, proceedings. Part II (©2020)
- Record Type:
- Book
- Title:
- Machine learning and knowledge discovery in databases : International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, proceedings.: International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, proceedings. Part II (©2020)
- Main Title:
- Machine learning and knowledge discovery in databases : International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, proceedings.
- Further Information:
- Note: Peggy Cellier, Kurt Driessens (eds.).
- Other Names:
- Cellier, Peggy
Driessens, Kurt
ECML PKDD (Conference) - Contents:
- Intro -- Preface -- Organization -- Contents -- Part II -- Contents -- Part I -- Second International Workshop on Knowledge Discovery and User Modeling for Smart Cities (UMCit) -- District Heating Substation Behaviour Modelling for Annotating the Performance -- 1 Introduction -- 2 Methods and Techniques -- 2.1 Sequential Pattern Mining -- 2.2 Clustering Analysis -- 2.3 Distance Measure -- 3 Proposed Method -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Modeling Evolving User Behavior via Sequential Clustering -- 1 Introduction 2 Modeling Evolving User Behavior via Sequential Clustering -- 2.1 Sequential Partitioning Algorithm -- 2.2 Partitioning Algorithms -- 2.3 Dynamic Time Warping Algorithm -- 3 Case Study: Modeling Household Electricity Consumption Behavior -- 3.1 Case Description -- 3.2 Data and Experiments -- 3.3 Results and Discussion -- 4 Conclusions and Future Work -- References -- Recognizing User's Activity and Transport Mode Detection: Maintaining Low-Power Consumption -- 1 Introduction -- 2 Related Work -- 3 Data Collection -- 4 Data Preprocessing -- 5 Feature Extraction -- 6 Classification Models 6.1 Accelerometer Features -- 7 Evaluation and Results -- 7.1 Effect of Filtering Raw Accelerometer Data on Classification Accuracy -- 7.2 Effect of Location Data on Classification Accuracy -- 8 Conclusion -- References -- Can Twitter Help to Predict Outcome of 2019 Indian General Election: A Deep Learning Based Study -- 1 Introduction --Intro -- Preface -- Organization -- Contents -- Part II -- Contents -- Part I -- Second International Workshop on Knowledge Discovery and User Modeling for Smart Cities (UMCit) -- District Heating Substation Behaviour Modelling for Annotating the Performance -- 1 Introduction -- 2 Methods and Techniques -- 2.1 Sequential Pattern Mining -- 2.2 Clustering Analysis -- 2.3 Distance Measure -- 3 Proposed Method -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Modeling Evolving User Behavior via Sequential Clustering -- 1 Introduction 2 Modeling Evolving User Behavior via Sequential Clustering -- 2.1 Sequential Partitioning Algorithm -- 2.2 Partitioning Algorithms -- 2.3 Dynamic Time Warping Algorithm -- 3 Case Study: Modeling Household Electricity Consumption Behavior -- 3.1 Case Description -- 3.2 Data and Experiments -- 3.3 Results and Discussion -- 4 Conclusions and Future Work -- References -- Recognizing User's Activity and Transport Mode Detection: Maintaining Low-Power Consumption -- 1 Introduction -- 2 Related Work -- 3 Data Collection -- 4 Data Preprocessing -- 5 Feature Extraction -- 6 Classification Models 6.1 Accelerometer Features -- 7 Evaluation and Results -- 7.1 Effect of Filtering Raw Accelerometer Data on Classification Accuracy -- 7.2 Effect of Location Data on Classification Accuracy -- 8 Conclusion -- References -- Can Twitter Help to Predict Outcome of 2019 Indian General Election: A Deep Learning Based Study -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Dataset Collection -- 3.2 Hashtags Based Tweets Segregation -- 3.3 Twitter Sentiment Classification -- 3.4 Opinion Analysis Corresponding to Different States -- 4 Conclusion -- References Towards Sensing and Sharing Auditory Context Information Using Wearable Device -- 1 Introduction -- 2 Wearable Ambient Sound Sensing System -- 2.1 Wearable Device -- 2.2 Auditory Sensing Data -- 3 Extracting Context Information -- 3.1 Segmentation of Multi-dimensional Time-Series Data -- 4 Discussion and Future Work -- 5 Conclusion -- References -- Workshop on Data Integration and Applications (DINA) -- Noise Reduction in Distant Supervision for Relation Extraction Using Probabilistic Soft Logic -- 1 Introduction -- 2 Related Work -- 3 Probabilistic Soft Logic 4 HL-MRF Model for Noise Reduction -- 4.1 Prior Model -- 4.2 Consistency Between Predictions of NER Systems -- 4.3 Sentence Structure Analysis -- 4.4 Context-Based Constraints -- 4.5 Semantic Similarity in Noise Reduction -- 5 Experimental Evaluation -- 5.1 Experimental Setup: Data and Models -- 5.2 Experimental Setup: Benchmark Methods -- 5.3 Experimental Results -- 6 Conclusions and Outlook -- References -- Privacy-Preserving Record Linkage to Identify Fragmented Electronic Medical Records in the All of Us Research Program -- 1 Introduction -- 1.1 The All of Us Research Program … (more)
- Publisher Details:
- Cham : Springer
- Publication Date:
- 2020
- Copyright Date:
- 2020
- Extent:
- 1 online resource (755 pages)
- Subjects:
- 006.3/1
Machine learning -- Congresses
Data mining -- Congresses
Data mining
Machine learning
Electronic books
Conference papers and proceedings - Languages:
- English
- ISBNs:
- 9783030438876
3030438872 - Notes:
- Note: Includes bibliographical references and index.
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- British Library HMNTS - ELD.DS.507783
- Ingest File:
- 03_084.xml