From social data mining and analysis to prediction and community detection. (2017)

• Record Type: Book
• Further Information: Note: Mehmet Kaya, Özcan Erdoǧan, Jon Rokne, editors.
• Editors: Kaya, Mehmet; Erdoǧan, Özcan; Rokne, J (Jon), 1941-
• Contents: Preface; Introduction; From Social Data Mining and Analysis to Prediction and Community Detection; Contents; An Offline-Online Visual Framework for Clustering Memes in Social Media; 1 Introduction; 2 Related Work; 2.1 Similarity Measures and Text Clustering; 2.2 Online Clustering Algorithms in OSNs; 2.3 Detecting Memes in Online Social Networks; 3 Reddit Social Network; 4 Google Tri-gram Method; 5 Semantic Jaccard Coefficient; 6 Similarity Scores and Combination Strategies; 6.1 Similarity Scores; 6.2 Combination Strategies; 6.2.1 Pairwise Maximization Strategy; 6.2.2 Pairwise Average Strategy. 6.2.3 Linear Combination Strategy6.2.4 Internal Centrality-Based Weighting; 6.2.5 Similarity Score Reweighting with Relevance User Feedback; 7 The Offline-Online Meme Detection Framework; 7.1 The Offline-Online Meme Clustering Algorithm; 8 Experimental Results; 8.1 Ground-Truth Dataset; 8.2 Clustering Algorithms; 8.3 Baselines; 8.4 Results; 8.4.1 Clustering with Semantic Similarity Scores; 8.4.2 The ICW Strategy; 8.4.3 Similarity Score Reweighting with Relevance User Feedback; 8.4.4 Similarity Score with Wikipedia Concepts; 8.4.5 Semantic Jaccard Coefficient. 8.4.6 The Offline-Online Meme Clustering Algorithm9 Conclusions; References; A System for Email Recipient Prediction; 1 Introduction; 2 The Recipient Prediction Problem; 3 Features for Recipient Prediction; 3.1 Temporal Features; 3.2 Textual Features; 4 Finding Names in Greeting; 4.1 Extracting Names from a Greeting; 4.2 Handling Additional Languages; 4.3 Experimental Evaluation; 5 Implementation; 5.1 Definitions and Assumptions; 5.2 Implementation; 6 Experimental Evaluation; 6.1 Personalized Functions; 6.2 Within-Domain Setting; 6.3 Cross-Domain Setting; 6.4 Known Prefix. 6.5 Feature Evaluation6.6 Comparison with Related Work; 7 Conclusion and Future Work; References; A Credibility Assessment Model for Online Social Network Content; 1 Introduction; 2 Related Work; 3 Proposed Model; 3.1 Tweet Collector; 3.2 Tweet Feature Extractor; 3.3 Relative Importance Matrix; 3.4 Classification Process; 3.5 Sentiment Score Process; 3.6 Final Credibility Assessment; 4 Experiments; 4.1 Experimental Data; 4.2 Experimental Results; 5 Conclusion; References; Web Search Engine-Based Representation for Arabic Tweets Categorization; 1 Introduction; 2 Related Work. 2.1 Short Text Representation2.2 Tweets Categorization; 3 Arabic Text Preprocessing; 4 Rough Set Theory; 4.1 Generalized Approximation Spaces; 4.2 Tolerance Rough Set Model; 5 Machine Learning for Text Categorization; 5.1 *-1pc; 5.2 Support Vector Machine; 5.3 Decision Tree; 6 Proposed Method for Enriching Arabic Tweets Representation; 6.1 Tweet's Preprocessing; 6.2 Enrichment Component; 7 Experiments Results; 7.1 Datasets; 7.2 Results; 7.3 Discussion; 8 Conclusion and Future Work; References; Sentiment Trends and Classifying Stocks Using P-Trees; 1 Introduction; 2 The P-Tree Technology.
• Publisher Details: Cham, Switzerland : Springer
• Publication Date: 2017
• Extent: 1 online resource
• Subjects: 006.3/12; 004; Computer science; Data mining; COMPUTERS -- Databases -- Data Mining; Data mining; Computer Science; Data Mining and Knowledge Discovery; Artificial Intelligence (incl. Robotics); Applications of Graph Theory and Complex Networks; Computers -- Intelligence (AI) & Semantics; Science -- System Theory; Artificial intelligence; Mathematical physics; Artificial intelligence; Computers -- Database Management -- Data Mining; Data mining; Electronic books
• Languages: English
• ISBNs: 9783319513676; 3319513672
• Related ISBNs: 9783319513669; 3319513664
• Notes: Note: Includes bibliographical references and index.; Note: Online resource; title from PDF title page (SpringerLink, viewed April 4, 2017).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
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