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[null,"1.","Record Nr.",null,"UNINA990007140840403321"]
[null,null,"Autore",null,"Strinati, Valerio"]
[null,null,"Titolo",null,"Politica e cultura nel Partito socialista italiano : 1945-1978 / Valerio Strinati"]
[null,null,"Pubbl/distr/stampa",null,"Napoli : Liguori, 1980"]
[null,null,"Descrizione fisica",null,"345 p. ; 21 cm"]
[null,null,"Collana",null,"Le istituzioni culturali ; 6 / collana diretta da Giuliano Manacorda"]
[null,null,"Disciplina",null,"324.245 074"]
[null,null,"Locazione",null,"DDCIC"]
[{"$nulls":4},"FLFBC"]
[{"$nulls":4},"FSPBC"]
[null,null,"Collocazione",null,"III 265"]
[{"$nulls":4},"324.24 STR 1 BIS"]
[{"$nulls":4},"324.24 STR 1"]
[{"$nulls":4},"COLLEZ. 762 (6)"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNISA996464526903316"]
[null,null,"Titolo",null,"Data science . Part II : 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021, Taiyuan, China, September 17-20, 2021, proceedings / / Jianchao Zeng [and four others]"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"981-16-5943-5"]
[null,null,"Descrizione fisica",null,"1 online resource (532 pages)"]
[null,null,"Collana",null,"Communications in Computer and Information Science ; ; v.1452"]
[null,null,"Disciplina",null,"006.312"]
[null,null,"Soggetti",null,"Data mining"]
[{"$nulls":4},"Big data"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Social Media and Recommendation Systems -- Natural Language Inference Using Evidence from Knowledge Graphs -- 1 Introduction -- 2 Related Work -- 3 Model Architecture -- 3.1 Clue Extraction -- 3.2 Evidence and Sentence Encoding -- 3.3 Evidence Integration -- 3.4 Final Classifier -- 4 Experiments -- 4.1 Datasets and Knowledge Resources -- 4.2 Effectiveness of Different KGs and Clue Encoders -- 4.3 Experiments on MedNLI -- 4.4 Experiments on SciTail -- 4.5 Implementation Details -- 5 Conclusion and Future Works -- References -- Construction of Multimodal Chinese Tourism Knowledge Graph -- 1 Introduction -- 2 Related Work -- 3 MCTKG Construction -- 3.1 Semi-structured Knowledge Extraction -- 3.2 Entity Expansion -- 3.3 Ontology Construction -- 3.4 Attribute Normalization -- 3.5 Automatic Generation Algorithm of Tourist Routes -- 3.6 MCTKG Sharing Platform -- 4 Experiments -- 4.1 Attribute Normalization Evaluation -- 4.2 Route Evaluation -- 5 Conclusion -- References -- Study on Binary Code Evolution with Concrete Semantic Analysis -- 1 Introduction -- 2 Approach Overview -- 2.1 Motivation Example -- 2.2 Problem Statement -- 2.3 Frame of Overview -- 3 Methodology -- 3.1 Comparing Similarity -- 3.2 Locating Difference -- 3.3 Analyzing Semantic Patterns -- 3.4 Identifying Evolution -- 4 Evaluation -- 4.1 Locating Difference -- 4.2 What Semantics Are Evolved -- 5 Related "]
[{"$nulls":4},"Work -- 6 Conclusion -- References -- Research on COVID-19 Internet Derived Public Opinions Prediction Based on the Event Evolution Graph -- 1 Introduction -- 2 The Method and Steps of Building the Event Evolution Graph -- 2.1 Data Acquisition and Preprocessing -- 2.2 Causal Judgment and Event Extraction -- 2.3 Text Vectorization and Event Clustering."]
[{"$nulls":4},"3 An Empirical Study of COVID-19 Network Public Opinion Event Evolution Graph -- 3.1 COVID-19 Event Data Acquisition and Preprocessing -- 3.2 COVID-19 Event Data Acquisition and Preprocessing -- 3.3 The Construction of Event Evolution Graph -- 4 Analysis and Discussion -- 5 Conclusion -- References -- A Text Correlation Algorithm for Stock Market News Event Extraction -- 1 Introduction -- 2 Related Work -- 2.1 Extraction of Stock Market News Information -- 2.2 Text Correlation Algorithm -- 3 Our Proposed Method -- 3.1 Word Vector Model -- 3.2 Structured Event and Event Vector -- 3.3 Text Correlation Algorithm Based on Matching and Clustering -- 4 Experiments -- 4.1 Data Collection and Preprocessing -- 4.2 Relevance Between Words -- 4.3 Correlation Between Event Triples -- 4.4 Relevance Between Texts -- 4.5 Correlation Between Text Sets -- 4.6 Interpretable Information of Correlation Calculation -- 5 Conclusion -- References -- Citation Recommendation Based on Community Merging and Time Effect -- 1 Introduction -- 2 Problem Statement -- 3 Community Merging -- 4 CMTE-PathSim Model -- 4.1 Meta Path-Based Feature Space -- 4.2 Citation Probability -- 4.3 Time Effect -- 4.4 Citation Recommendation -- 5 Experiments -- 5.1 Dataset and Methods Setup -- 5.2 Verifying Time Effect Factor -- 5.3 Comparison with Benchmark Algorithm -- 6 Conclusions and Future Work -- References -- Sentiment Analysis for MOOC Course Reviews -- 1 Introduction -- 2 Related Work -- 3 MOOC Text Comment Sentiment Analysis Model -- 3.1 ALBERT Pre-trained Language Model -- 3.2 BiGRU Neural Network Model -- 3.3 Capsule Network -- 3.4 Attention Mechanism -- 3.5 Fully Connected Layer -- 4 Experimental Analysis -- 4.1 Introduction to the Data Set -- 4.2 Evaluation Standard -- 4.3 Experimental Comparison Model -- 4.4 Analysis of Experimental Results -- 5 Conclusion -- References."]
[{"$nulls":4},"Analyzing Interpretability Semantically via CNN Visualization -- 1 Introduction -- 2 Related Work -- 3 Interpretation by Filters Screening and Semantic Labeling -- 3.1 Data Preparation -- 3.2 Screening Convolution Features -- 3.3 Deconvolutional Visualization -- 3.4 Semantic Annotation of Filters -- 4 Experiments -- 4.1 Visualization of Screened Filters -- 4.2 The Coincidence Degree of Interpretable Regions and Expert Regions -- 4.3 Semantic Consistency of Filters -- 5 Conclusion -- References -- Probing Filters to Interpret CNN Semantic Configurations by Occlusion -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Dataset and Semantic Configurations -- 3.2 Probe Filters to Recognize Specified Visual Semantic Concepts by Occluding -- 3.3 Visualization for Evaluation -- 4 Experiment -- 4.1 Dataset and Experimental Setup -- 4.2 Annotation Task -- 4.3 Experiment Result -- 5 Conclusion -- References -- Targeted BERT Pre-training and Fine-Tuning Approach for Entity Relation Extraction -- 1 Introduction -- 2 Related Work -- 2.1 Methods with Distant Supervision -- 2.2 Methods with Pre-trained Language Model -- 3 Methodology -- 3.1 Separated Pipeline Model Architecture -- 3.2 Verb-mLM Task for Relation Classification Model -- 3.3 Entity-MLM Task for Entity-Pair Annotation Model -- 3.4 Inter-layer Sharing Attention Mechanism -- 4 Experiments -- 4.1 Datasets -- 4.2 Experiment on Entity Relation Classification -- 4.3 Experiment on Entity-Pair Annotation -- 4.4 Results Analysis -- 5 Conclusion -- References -- "]
[{"$nulls":4},"Data Security and Privacy -- Security-as-a-Service with Cyberspace Mimic Defense Technologies in Cloud -- 1 Introduction -- 2 Background -- 3 SECaaS -- 3.1 User's Perception Module -- 3.2 Decision Module -- 3.3 Multi-compiler -- 3.4 Cyberspace Mimic Environments -- 4 Experiments -- 4.1 Security Experiments -- 4.2 Performance Evaluation."]
[{"$nulls":4},"5 Related Works -- 5.1 Multi-compiler -- 5.2 MVEE -- 6 Conclusion and Future Works -- References -- Searchable Encryption System for Big Data Storage -- 1 Introduction -- 2 Functional Interaction Model and System Architecture -- 2.1 Functional Interaction Model -- 2.2 System Architecture -- 3 Main Cryptographic Algorithm -- 3.1 Key Management Algorithm -- 3.2 File Classification Encryption/Decryption Algorithm -- 3.3 Symmetric Searchable Encryption Algorithm -- 3.4 Dynamic Update of Cipher Index -- 4 Deployment and System Test -- 4.1 Deployment -- 4.2 System Test -- 4.3 Advantage Analysis -- 5 Conclusion -- References -- Research on Plaintext Resilient Encrypted Communication Based on Generative Adversarial Network -- 1 Introduction -- 2 Adversarial Neural Cryptography -- 2.1 GANs Principle -- 2.2 Adversarial Neural Cryptography Model -- 2.3 Function Design -- 3 Plaintext Leakage in the Original Model -- 3.1 Neural Network Design in the Original Model -- 3.2 Leakage Experiments Under the Original Model -- 4 Model Optimization -- 4.1 Increase Decryption Speed -- 4.2 Decrease the Correct Rate of Attacker's Cracking -- 5 Conclusions -- References -- An Improved LeNet-5 Model Based on Encrypted Data -- 1 Introduction -- 2 Preliminaries -- 2.1 Homomorphic Encryption -- 2.2 Convolutional Neural Network -- 2.3 LeNet-5 Model -- 3 Improved LeNet-5 Model in Ciphertext Domain -- 3.1 Mapping from the Plaintext Domain to the Ciphertext Domain -- 3.2 Improved LeNet-5 Model -- 4 Model Analysis -- 4.1 Feasibility Analysis -- 4.2 Efficiency Analysis -- 5 Conclusions -- References -- Design and Implementation of Intrusion Detection System Based on Neural Network -- 1 Introduction -- 2 Related Technologies -- 2.1 Intrusion Detection System -- 2.2 BP Neural Network -- 3 Design of Intrusion Detection System Based on Neural Network -- 3.1 System Framework."]
[{"$nulls":4},"3.2 Event Collector -- 3.3 Event Analyzer -- 4 Intrusion Detection Experiment Based on Neural Network -- 4.1 Experimental Environment -- 4.2 Experimental Results and Analysis -- 5 Conclusions -- References -- IoT Security Situational Awareness Based on Q-Learning and Bayesian Game -- 1 Introduction -- 2 Related Works -- 3 Q-Learning Algorithm -- 3.1 Markov Decision Process -- 3.2 Q-Learning Method -- 4 IoT Security Situational Awareness Model Based on Q-Learning and Bayesian Game -- 4.1 Characteristics of IoT Security -- 4.2 Model Selection and Definition -- 4.3 Selection of the Optimal Defense Strategy -- 4.4 IoT Security Situational Assessment -- 4.5 Model Algorithm -- 5 Experimental Simulation -- 5.1 Experimental Setup -- 5.2 Analysis of Results -- 6 Conclusion -- References -- Protecting Web Application Code and Sensitive Data with Symmetric and Identity-Based Cryptosystems -- 1 Introduction -- 2 Symmetric and Public Key Cryptographic Algorithms -- 2.1 Symmetric Cryptographic Algorithms -- 2.2 Public-Key Cryptographic Algorithms -- 3 Web Security Scheme for Protecting Sensitive Data and Program Code -- 3.1 The Idea and General Architecture -- 3.2 The Security Scheme -- 3.3 Experimental Results and Performance -- 3.4 Security Analysis -- 4 Conclusion -- References -- IoT Honeypot Scanning and Detection System Based on Authorization Mechanism -- 1 Introduction -- 2 Related Work -- 2.1 Network Scanning and Detection -- 2.2 IoT Honeypot -- 3 IoT Honeypot Scanning and Detection System "]
[{"$nulls":4},"Based on Authorization Mechanism -- 3.1 Authorization System -- 3.2 Honeypot System -- 4 Experiments -- 5 Conclusion -- References -- Privacy Protection Model for Blockchain Data Sharing Based on zk-SNARK -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 3.1 zk-SNARK -- 3.2 CP-ABE -- 3.3 Blockchain Data Sharing Model."]
[{"$nulls":4},"4 Privacy Protection Model for Blockchain Data Sharing."]
[null,null,null,"Sommario/riassunto","\"The 81 papers presented in these two volumes were carefully reviewed and selected from 256 submissions. The papers are organized in topical sections on big data management and applications; social media and recommendation systems; infrastructure for data science; basic theory and techniques for data science; machine learning for data science; multimedia data management and analysis; ​social media and recommendation systems; data security and privacy; applications of data science; education research, methods and materials for data science and engineering; research demo.\" -- Publisher's description."]