Event-Driven Surveillance [electronic resource] : Possibilities and Challenges /
Denecke, Kerstin.author.
The Web has become a rich source of personal information in the last few years. People twitter, blog, and chat online. Current feelings, experiences or latest news are posted. For instance, first hints to disease outbreaks, customer preferences, or political changes could be identified with this data. Surveillance or early warning systems enable such detection of changes and support humans in getting information on changing situations. However, the variety of data that could be considered for surveillance is immense, ranging from sensor-measured values to collected counts and information extracted from natural language documents. Denecke's objective is to introduce the multiple possibilities and facets of surveillance and its applications. She first introduces the task of surveillance and provides an overview on surveillance in various domains. Next, the various information sources that are available and could already be used by surveillance systems are summarized. In the main part of the book, her focus is on unstructured data as a source for surveillance. An overview on existing methods as well as methods to be developed in order to process this kind of data with respect to surveillance is presented. As an example application, she introduces disease surveillance using Web 2.0, including corresponding methods and challenges to be addressed. The book closes with remarks on new possibilities for surveillance gained by recent developments of the Internet and mobile communication, and with an outline of future challenges.
Description based upon print version of record.
Event-Driven Surveillance; Preface; Contents; 1 Introduction; 2 The Task of Surveillance; 2.1 A Motivating Example; 2.2 Definitions and Characteristics of Surveillance; 2.2.1 Surveillance Task and Objectives; 2.2.2 Surveillance Process; 2.2.3 Summary; 2.3 Application Areas; 2.3.1 Surveillance in Politics; 2.3.2 Surveillance in Business and Finances; 2.3.3 Disaster Surveillance; 2.3.4 Traffic Surveillance and Management; 3 Information Sources for Surveillance; 3.1 Structured Data; 3.1.1 Sources of Structured Data; 3.1.2 Characteristics and Implications for Surveillance Systems
3.2 Unstructured Data3.2.1 The Web as Data Source; 3.2.2 Characteristics and Implications for Surveillance Systems; 4 Surveillance Methods; 4.1 Event-Driven Architectures; 4.1.1 Characteristics of Event-Driven Architectures; 4.1.2 Processing Steps and Components; 4.1.3 Benefits; 4.2 Data Collection Methodologies; 4.2.1 Web Crawling and Collecting Social Media Data; 4.2.2 Data Stream Management; 4.3 Data Preprocessing Methods; 4.3.1 Filtering Methodologies; 4.3.2 Text Analysis and Natural Language Processing; 4.3.3 Sentiment Analysis; 4.3.4 Role of NLP for Surveillance Systems
4.4 Data Analysis and Interpretation4.4.1 Event Detection Methods; 4.4.2 Event Tracking; 4.4.3 Aggregation of Events; 4.4.4 Interpretation of Detected Events; 4.5 Ontologies for Surveillance Systems; 4.6 Presentation of Information and Alerts; 5 An Example: Disease Surveillance from Web 2.0; 5.1 The Task of Disease Surveillance; 5.2 Event-Driven Architecture for Disease Surveillance; 5.2.1 Content Collection Component; 5.2.2 Document Analysis Component; 5.2.3 Event Detection and Signal Generation Component; 5.2.4 Recommendation Component; 5.2.5 User Interface; 5.3 Experiences and Perspectives
6 Future ChallengesGlossary; References; Index
Includes bibliographical references and index.
The Web has become a rich source of personal information in the last few years. People twitter, blog, and chat online. Current feelings, experiences or latest news are posted. For instance, first hints to disease outbreaks, customer preferences, or political changes could be identified with this data. Surveillance or early warning systems enable such detection of changes and support humans in getting information on changing situations. However, the variety of data that could be considered for surveillance is immense, ranging from sensor-measured values to collected counts and information extracted from natural language documents. Denecke's objective is to introduce the multiple possibilities and facets of surveillance and its applications. She first introduces the task of surveillance and provides an overview on surveillance in various domains. Next, the various information sources that are available and could already be used by surveillance systems are summarized. In the main part of the book, her focus is on unstructured data as a source for surveillance. An overview on existing methods as well as methods to be developed in order to process this kind of data with respect to surveillance is presented. As an example application, she introduces disease surveillance using Web 2.0, including corresponding methods and challenges to be addressed. The book closes with remarks on new possibilities for surveillance gained by recent developments of the Internet and mobile communication, and with an outline of future challenges.
Data mining.
Information storage and retrieval.
Natural language processing (Computer science).
Pattern recognition.
Artificial intelligence.
Data Mining and Knowledge Discovery.
Information Storage and Retrieval.
Natural Language Processing (NLP).
Pattern Recognition.
Artificial Intelligence.
SpringerBriefs in Computer Science