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[null,"1.","Record Nr.",null,"UNISA996466404703316"]
[null,null,"Titolo",null,"Big data and social media analytics : trending applications / / Mehmet Çakırtaş, Mehmet Kemal Ozdemir, editors"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"3-030-67044-9"]
[null,null,"Descrizione fisica",null,"1 online resource (246 pages)"]
[null,null,"Collana",null,"Lecture notes in social networks"]
[null,null,"Disciplina",null,"005.7"]
[null,null,"Soggetti",null,"Dades massives"]
[{"$nulls":4},"Mineria de dades"]
[{"$nulls":4},"Comunitats virtuals"]
[{"$nulls":4},"Big data"]
[{"$nulls":4},"Llibres electrònics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"Intro -- Contents -- Twenty Years of Network Science: A Bibliographic and Co-authorship Network Analysis -- 1 Introduction -- 2 Scholarly Networks Analysis -- 3 Preliminaries and Data -- 3.1 Co-authorship Network of Network Scientists -- 3.2 Glossary -- 3.3 Data Collection and Preparation -- 4 Analysis of Network Science Papers -- 5 Analysis of the Co-authorship Network -- 6 Conclusion -- References -- Impact of Locational Factors on Business Ratings/Reviews: A Yelp and TripAdvisor Study -- 1 Introduction -- 2 Related Work -- 3 Methodology and Datasets -- 3.1 Methodology -- 3.2 Restaurant Success Metric -- 3.3 Restaurant Dataset -- 3.3.1 Yelp-2019 Dataset -- 3.3.2 TripAdvisor Dataset -- 3.4 Location Dataset -- 4 Effect of Location Parameters on Restaurant Success -- 4.1 Location Characteristic Parameters -- 4.1.1 Living Standard -- 4.1.2 Tourism Significance -- 4.1.3 Business Convenience -- 4.1.4 Combined Parameters -- 4.2 Correlation Metrics -- 4.2.1 Spearman's Correlation -- 4.2.2 Kendall's Correlation -- 4.3 Correlation Results -- 4.3.1 State-Wise Correlation Using All Restaurants -- 4.3.2 Cluster-Wise Correlation Using All Restaurants -- 5 Conclusion -- References -- Identifying Reliable Recommenders in Users' Collaborating Filtering and Social Neighbourhoods -- 1 Introduction -- 2 Related Work -- 3 SN CF Prediction Formulation Foundations -- 4 The Proposed Algorithm and "]
[{"$nulls":4},"the Partial Prediction Combination Alternatives -- 4.1 The Proposed Algorithm -- 4.2 Alternatives for Combining the CF and SN Partial Predictions -- 4.3 Complexity Analysis -- 5 Experimental Evaluation -- 5.1 Prediction Accuracy Experiments Using the PCC as the Similarity Metric -- 5.2 Prediction Accuracy Experiments Using the CS as the Similarity Metric -- 6 Conclusions and Future Work -- References."]
[{"$nulls":4},"Safe Travelling Period Recommendation to High Attack Risk European Destinations Based on Past Attack Information -- 1 Introduction -- 2 Related Work -- 3 Algorithm Prerequisites -- 4 Prediction Algorithm -- 5 Experimental Results -- 5.1 Number of Attacks as the Evaluation Parameter -- 5.2 Number of Fatalities as the Evaluation Parameter -- 6 Conclusion and Future Work -- References -- Analyzing Cyber Influence Campaigns on YouTube Using YouTubeTracker -- 1 Introduction -- 2 State of the Art in YouTube Analysis -- 3 YouTubeTracker -- 3.1 Tracker Feature -- 3.2 Posting Frequency -- 3.3 Content Analysis -- 3.4 Content Engagement -- 4 Case Study: 2018 Trident Juncture Exercise -- 5 Extended Work -- 5.1 Elasticsearch -- 5.2 2019 Canadian Elections Use-Case -- 5.3 Video Characterization Using T-SNE and Barcode Visualization -- 6 Conclusion and Future Works -- References -- Blog Data Analytics Using Blogtrackers -- 1 Introduction -- 2 State of the Art in Blog Monitoring and Analysis -- 3 Blogtrackers: Analytical Capabilities -- 4 Analysis of Asia-Pacific Blogs: A Case Study -- 5 Conclusion and Future Works -- References -- Using Social Media Surveillance in Order to Enhance the Effectiveness of Crew Members in Search and Rescue Missions -- 1 Introduction -- 2 Related Work -- 2.1 Search and Rescue Missions (SARs) -- 2.2 Social Media in Crisis Situations -- 2.3 Visual Search Principles &amp -- Patterns -- 3 Problem Statement -- 4 Methodology -- 4.1 Description -- 4.2 Simulation Platform -- 4.3 Scenario -- 5 Experimental Analysis -- 5.1 Experimental Description -- 5.2 Results -- 6 Conclusions -- References -- Visual Exploration and Debugging of Machine Learning Classification over Social Media Data -- 1 Introduction -- 2 Related Work -- 3 SAVIZ: Brief Overview -- 3.1 User Experience -- 4 Conclusion -- References."]
[{"$nulls":4},"Efficient and Flexible Compression of Very Sparse Networksof Big Data -- 1 Introduction -- 2 Background and Related Work -- 3 Our Efficient and Flexible Compression Model -- 3.1 Graph Representation of a Social Network -- 3.2 Matrix Representation of a Social Network -- 3.3 Bit Vector Representation of a Follower in a Social Network -- 3.4 Word-Aligned Hybrid (WAH) Compressed Bitmap Representation of a Follower in a Social Network -- 3.4.1 An Example of WAH Compressed Bitmap -- 3.5 Improved Position List Word-Aligned Hybrid (IPLWAH) Compressed Bitmap Representation of a Follower in a Social Network -- 3.5.1 An Example of IPLWAH(1) Compressed Bitmap -- 3.5.2 An Example of IPLWAH(2) Compressed Bitmap -- 3.6 Multi-group Position List Word-Aligned Hybrid (MPLWAH) Compressed Bitmap Representation of a Follower in a Social Network -- 3.6.1 An Example of MPLWAH(2) Compressed Bitmap -- 3.6.2 An Example of MPLWAH(3) Compressed Bitmap -- 3.6.3 Other Examples of MPLWAH(3) Compressed Bitmaps -- 4 Our Data Science Solution for Social Network Mining on MPLWAH Compressed Bitmaps -- 4.1 An Example of Discovering Frequently Followed Groups of Followees from a Social Network Represented by a Collection of MPLWAH(3) Compressed Bitmaps -- 5 Evaluation -- 5.1 Evaluation on Memory Consumption -- 5.2 Evaluation on Runtime -- 5.3 Evaluation on Scalability -- 6 Conclusion -- References -- Weather Big Data Analytics: Seeking Motifs in Multivariate Weather Data -- 1 Introduction -- 2 Related Work -- 3 Temperatures Time Series Analysis and Clustering -- 3.1 Data "]
[{"$nulls":4},"Acquisition -- 3.2 Data Preparation and Curation -- 3.3 Discretization -- 3.4 LERP-RSA Construction -- 3.5 ARPaD Pattern Discovery -- 3.6 Similarity Meta-analysis -- 4 Experimental Analysis -- 5 Conclusions -- References -- Analysis of Link Prediction Algorithms in Hashtag Graphs -- 1 Introduction."]
[{"$nulls":4},"2 Background and Motivation -- 3 Foundation of the Hashtag Graph -- 3.1 Unweighted Heuristic Link Prediction Methods -- 3.2 Edge-Weighted Heuristic Link Prediction Methods -- 3.3 Graph Neural Network Link Prediction with SEAL -- 3.3.1 SEAL -- 3.3.2 Node Labelling -- 3.4 Other Heuristic Link Prediction Methods -- 3.4.1 Katz Index -- 3.4.2 SimRank -- 3.4.3 Rooted PageRank -- 4 Methodology: Vertex-and-Edge-Weighted Heuristic Link Prediction Methods -- 5 Experimental Setup -- 5.1 Data Collection -- 5.2 Data Pre-processing -- 6 Results -- 6.1 Heuristic Link Prediction Methods -- 6.2 SEAL -- 7 Conclusions and Future Research -- References."]
[null,"2.","Record Nr.",null,"UNISALENTO991001249849707536"]
[null,null,"Autore",null,"Tabucchi, Antonio"]
[null,null,"Titolo",null,"Racconti con figure / Antonio Tabucchi ; a cura di Thea Rimini"]
[null,null,"Pubbl/distr/stampa",null,"Palermo : Sellerio, c2011"]
[null,null,"ISBN",null,"9788838924941"]
[null,null,"Descrizione fisica",null,"356 p. : ill. ; 17 cm"]
[null,null,"Collana",null,"La memoria ; 848"]
[null,null,"Disciplina",null,"853.914"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]