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[null,null,"Titolo",null,"Knowledge Science, Engineering and Management [[electronic resource] ] : 10th International Conference, KSEM 2017, Melbourne, VIC, Australia, August 19-20, 2017, Proceedings / / edited by Gang Li, Yong Ge, Zili Zhang, Zhi Jin, Michael Blumenstein"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017"]
[null,null,"ISBN",null,"3-319-63558-1"]
[null,null,"Edizione",null,"[1st ed. 2017.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XVII, 563 p. 150 illus.)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence ; ; 10412"]
[null,null,"Disciplina",null,"006.33"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Information storage and retrieval"]
[{"$nulls":4},"Optical data processing"]
[{"$nulls":4},"Computer communication systems"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Computer Applications"]
[{"$nulls":4},"Information Storage and Retrieval"]
[{"$nulls":4},"Computer Imaging, Vision, Pattern Recognition and Graphics"]
[{"$nulls":4},"Computer Communication Networks"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Learning from Non-stationary Distributions (Invited Speech) -- Contents -- Text Mining and Document Analysis -- Learning Sparse Overcomplete Word Vectors Without Intermediate Dense Representations -- 1 Introduction -- 2 Related Work -- 3 Our Model -- 3.1 Parameter Estimation -- 3.2 Optimization Algorithm -- 4 Evaluation -- 4.1 Experimental Settings -- 4.2 Word Analogy -- 4.3 Word Similarity -- 4.4 Interpretability -- 5 Conclusion -- References -- A Study of Distributed Semantic Representations for Automated Essay Scoring -- 1 Introduction -- 2 Common Text Features -- 3 Semantic Representations for AES -- 3.1 Methods for Vector Representations -- 3.2 Semantic Features -- 4 "]
[{"$nulls":4},"Experimental Settings -- 4.1 Dataset -- 4.2 Evaluation Metrics and Learning Algorithms -- 5 Evaluation Design and Results -- 5.1 Evaluation Design -- 5.2 Evaluation Results -- 6 Conclusions and Future Work -- References -- Weakly Supervised Feature Compression Based Topic Model for Sentiment Classification -- 1 Introduction -- 2 Related Work -- 3 Hidden Topic Analysis Model -- 4 Weakly Supervised Feature Compression Based ELDA -- 5 Experiment Results -- 5.1 Data Preparation -- 5.2 Performance Evaluation -- 5.3 Results with Different Topics -- 5.4 Results with Different Gibbs Sampling Iterations -- 6 Conclusion -- References -- An Effective Gated and Attention-Based Neural Network Model for Fine-Grained Financial Target-Dependent Sentiment Analysis -- 1 Introduction -- 2 Related Work -- 3 The Proposed Neural Network Model GABi-LSTM -- 3.1 Motivation -- 3.2 The Overview of Model Architecture -- 3.3 Word Representation with Gated Char- and Word- Embedding -- 3.4 Sentence Representation with Attention-Based Bi-LSTM -- 3.5 Linear Regression -- 3.6 Parameter Learning -- 4 Experiments -- 4.1 Datasets -- 4.2 Evaluation Measure."]
[{"$nulls":4},"4.3 Experimental Results -- 4.4 Comparison with the State-of-the-Art Systems -- 4.5 Qualitative Visualization Analysis -- 5 Concluding Remarks -- References -- A Hidden Astroturfing Detection Approach Base on Emotion Analysis -- 1 Introduction -- 2 Related Work -- 3 Hidden Astroturfing Detection Method -- 3.1 Data Preparation -- 3.2 Pre-processing Operations -- 3.3 Bag-of-Word Module Construction -- 3.4 Emotion Mining and Analysis -- 3.5 Matching -- 3.6 Summary -- 4 Experiment and Evaluation -- 4.1 Experiment Setup -- 4.2 Evaluation Result -- 5 Conclusion -- References -- Leveraging Term Co-occurrence Distance and Strong Classification Features for Short Text Feature Selection -- Abstract -- 1 Introduction -- 2 Problem Preliminaries -- 2.1 Correlation of Two Terms in a Text -- 2.2 Expected Cross Entropy -- 3 The Proposed Approach -- 3.1 Terming Weighting Method Based on Co-occurrence Distance -- 3.2 Feature Dictionary Construction -- 4 Experiments and Results Analysis -- 4.1 Data Sets and Evaluation Metrics -- 4.2 Experimental Results and Analysis -- 4.2.1 Comparison of Feature Dictionaries -- 4.2.2 Effect of Variation of Dictionary Size for Short Text Classification -- 4.2.3 Classification Performance of Different Feature Selection Methods -- 5 Conclusions and Future Work -- Acknowledgement -- References -- Formal Semantics and Fuzzy Logic -- A Fuzzy Logic Based Policy Negotiation Model -- 1 Introduction -- 2 Preliminaries -- 3 Model Definition -- 4 Fuzzy Rules -- 5 Experiment -- 6 Related Work -- 7 Conclusions -- References -- f-ALC(D)-LTL: A Fuzzy Spatio-Temporal Description Logic -- 1 Introduction -- 2 Spatial Fuzzy Description Logic -- 3 Fuzzy Spatio-Temporal Description Logic f-ALC(D)-LTL -- 3.1 Syntax -- 3.2 Models -- 4 Hintikka Structures for f-ALC(D)-LTL -- 5 Reasoning in f-ALC(D)-LTL -- 5.1 Tableau Rules -- 5.2 Tableau Construction."]
[{"$nulls":4},"5.3 Tableau Elimination -- 5.4 Correctness -- 6 Conclusion and Future Work -- References -- R-Calculus for the Primitive Statements in Description Logic ALC -- 1 Introduction -- 2 Description Logic ALC -- 3 R-Calculus for Subset-Minimal Change -- 3.1 SDL: R-Calculus for a Statement -- 3.2 SDL: R-Calculus for a Set of Statements -- 4 Conclusions and Further Works -- References -- A Multi-objective Attribute Reduction Method in Decision-Theoretic Rough Set Model -- 1 Introduction -- 2 Preliminaries -- 2.1 Decision-Theoretic Rough Set Model -- 2.2 Three Kinds of Criteria in Decision-Theoretic Rough Set Model -- 3 Multi-objective Attribute Reduction in Decision-Theoretic Rough Set Model -- 3.1 Multi-objective Attribute Reduct -- 3.2 Multi-"]
[{"$nulls":4},"objective Attribute Reduction Algorithm -- 4 Experiments -- 4.1 Dataset -- 4.2 Experimental Setting -- 4.3 Experimental Results -- 5 Conclusion -- References -- A Behavior-Based Method for Distinction of Flooding DDoS and Flash Crowds -- 1 Introduction -- 2 Proposed Method -- 3 Experiments -- 4 Conclusion -- References -- Knowledge Management -- Analyzing Customer's Product Preference Using Wireless Signals -- 1 Introduction -- 2 Channel State Information -- 3 Analyzing Customer's Product Preference Using CSI -- 3.1 CSI Preprocessing -- 3.2 Feature Extraction -- 3.3 Classification -- 4 Performance Evaluation -- 4.1 Experimental Methodology -- 4.2 Feasibility of Customer's Product Preference Analysis -- 5 Related Work -- 5.1 Device-Based Activity Sensing -- 5.2 Device-Free Activity Sensing Using WiFi -- 6 Conclusion -- References -- Improved Knowledge Base Completion by the Path-Augmented TransR Model -- 1 Introduction -- 2 Our Approach -- 2.1 Base Model: TransR -- 2.2 Path-Augmented TransR: PTransR -- 2.3 Training Details -- 3 Evaluation -- 3.1 Dataset -- 3.2 Experimental Settings -- 3.3 Overall Performance."]
[{"$nulls":4},"3.4 In-Depth Analysis and Discussion -- 4 Related Work -- 5 Conclusion -- References -- Balancing Between Cognitive and Semantic Acceptability of Arguments -- 1 Introduction -- 2 Preliminaries -- 3 Equilibrium-Based Resolutions -- 3.1 Semantic and Cognitive Acceptabilities -- 3.2 Satisfiability Resolution -- 3.3 Entailment Resolution -- 3.4 Semantic Equivalence Resolution -- 4 Generality and Applicability -- 4.1 Characterising Existence of Resolutions -- 4.2 Application Illustration in Online Forum -- 5 Conclusions and Discussion -- A Proofs -- References -- Discovery of Jump Breaks in Joint Volatility for Volume and Price of High-Frequency Trading Data in China -- Abstract -- 1 Introduction -- 2 Bivariate Normal Distribution -- 3 Realized Trading Volatility of Price and Volume -- 3.1 Price Volatility -- 3.2 Volume Volatility -- 3.3 Volatility Rate of Price and Volume of Realized Trading -- 4 The Jump Point Model for High-Frequency Trading Volatility Break -- 5 The Algorithm of Point-by-Point Test for Jump Critical Points -- 6 The Empirical Analysis of Jump Critical Points -- 7 Conclusion -- Acknowledgments -- References -- Device-Free Intruder Sensing Leveraging Fine-Grained Physical Layer Signatures -- 1 Introduction -- 2 Related Work -- 2.1 Gait Based Human Identification -- 2.2 WiFi Based Activity Recognition -- 3 System Design -- 3.1 Channel State Information Extration -- 3.2 Data Prepocessing -- 3.3 Step Analysis -- 3.4 Device-Free Intruder Sensing -- 4 Experimentation Evaluation -- 4.1 Equipment -- 4.2 Experimental Results -- 5 Conclusion -- References -- Understanding Knowledge Management in Agile Software Development Practice -- Abstract -- 1 Introduction -- 2 Background and Related Work -- 2.1 Knowledge Classifications -- 2.2 Prior Reviews on Knowledge Management in ASD -- 3 Review Method."]
[{"$nulls":4},"3.1 Planning the Review and Identifying Relevant Literature -- 3.2 Publication Selection -- 3.3 Data Extraction and Synthesis -- 4 Results -- 4.1 Agile Practices Supporting Knowledge Management -- 4.2 Knowledge Involved in Agile Practices -- 5 Discussion -- 5.1 Implications -- 5.2 Limitations -- 6 Conclusion -- Acknowledgement -- References -- Knowledge Integration -- Multi-view Unit Intact Space Learning -- 1 Introduction -- 2 The Proposed Model -- 2.1 Background -- 2.2 Multi-view Unit Intact Space Learning -- 3 Optimization -- 3.1 Update Latent Feature Vectors in Unit Intact Space -- 3.2 Update View Generation Matrices -- 3.3 Convergence Analysis -- 3.4 Complexity Analysis -- 4 Experiments -- 4.1 Datasets and Evaluation Measures -- 4.2 Parameter Analysis -- 4.3 Comparison Results -- 5 Conclusion -- "]
[{"$nulls":4},"References -- A Novel Blemish Detection Algorithm for Camera Quality Testing -- Abstract -- 1 Introduction -- 2 Related Works -- 2.1 Traditional Methods Based on Image Filtering -- 2.2 Image Size Reduction by Scaling -- 2.3 Median Filtering -- 2.4 Image Subtraction -- 2.5 Thresholding -- 3 Novel Filtering Method -- 3.1 Influences of Image Noises -- 3.2 Proposed Multi-directional Median Filter -- 3.3 Adaptive Threshold with Bias -- 4 Results and Discussion -- 4.1 Low Noise Samples -- 4.2 High Noise Samples -- 5 Conclusion -- Acknowledgments -- References -- Learning to Infer API Mappings from API Documents -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Overview -- 3.2 Understanding API Documents -- 3.3 Computing Similarity Between APIs -- 4 Evaluation -- 4.1 Dataset -- 4.2 Experimental Settings -- 4.3 Results -- 5 Conclusion -- References -- Super-Resolution for Images with Barrel Lens Distortions -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Pretreatment Process -- 3.2 Training Stage -- 3.3 Testing Stage."]
[{"$nulls":4},"4 Experiments."]
[null,null,null,"Sommario/riassunto","This book constitutes the refereed proceedings of the 10th International Conference on Knowledge Science, Engineering and Management, KSEM 2017, held in Melbourne, Australia, in August 2017. The 35 revised full papers and 12 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: text mining and document analysis; formal semantics and fuzzy logic; knowledge management; knowledge integration; knowledge retrieval; recommendation algorithms and systems; knowledge engineering; and knowledge representation and reasoning."]