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Scalable Subgraph Counting: The Methods Behind The Madness
2019
Companion Proceedings of The 2019 World Wide Web Conference on - WWW '19
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The tutorial will also cover methods for subgraph analysis on "big data" computational models such as the streaming model and models of parallel and distributed computation. ...
Subgraph counting is a fundamental problem in graph analysis that finds use in a wide array of applications. ...
Depending on the application, there may be a need for algorithms in Subgraph counting has a wide variety of uses, including: • Social network analysis: Classifying social behavior, social behavior in gaming ...
doi:10.1145/3308560.3320092
dblp:conf/www/SeshadhriT19
fatcat:fsjcujs6krdlhmeuihzdj5h3wq
Tutorial: Identifying Malicious Actors on Social Media
2016
International Conference on Advances in Social Networks Analysis and Mining
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The tutorial will identify commonly used features for classifying actors into malicious vs. benign and will give a brief explanation of different algorithms both specific to social platforms and general ...
Online social media platforms are severely compromised by the existence of malicious actors such as bots on Twitter, vandals on Wikipedia, fake accounts on Facebook, trolls on Twitter and Slashdot, and ...
This tutorial focuses on detecting these malicious actors using state-of-the-art social network analysis, data mining and machine learning techniques. ...
dblp:conf/asunam/KumarSS16
fatcat:guljvmlvanfsjnqqkrskovlb64
Graph Mining and Graph Kernels
2008
Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD 08
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Social and biological networks have led to a huge interest in data analysis on graphs. ...
The goal of this tutorial is (i) to introduce newcomers to the field of graph mining, (ii) to introduce people with database background to graph mining using kernel machines, (iii) to introduce people ...
Target audience and prerequisites Target Audience This tutorial is intended for students, researchers and practitioners from graph mining, system biology, social network analysis, software engineering ...
doi:10.1145/1401890.1551565
fatcat:xpx2t6gq4ngcvisvqblh4bnwb4
Differential privacy in the wild
2016
Proceedings of the VLDB Endowment
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privacy preserving algorithms for a number of analysis tasks. ...
Research on differential privacy spanning a number of research areas, including theory, security, database, networks, machine learning, and statistics, over the last decade has resulted in a variety of ...
His research interests include privacy-preserving data analysis, data management, data mining, social networks, and privacy. ...
doi:10.14778/3007263.3007322
fatcat:g3egl7ajt5bzjphsj52hpeh7va
Aspect-based opinion mining from product reviews
2012
Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '12
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However, it is really difficult for a customer to read all of the reviews and make an informed decision on whether to purchase the product. ...
In this tutorial we will cover opinion mining in online product reviews with the focus on aspect-based opinion mining. ...
His current research interests include social network analysis, recommender systems, opinion mining, biological network analysis and high-throughput sequence data analysis. ...
doi:10.1145/2348283.2348533
dblp:conf/sigir/MoghaddamE12
fatcat:pymh7eyfyvhohpc6adyxmyrj2a
Differential Privacy in the Wild
2017
Proceedings of the 2017 ACM International Conference on Management of Data - SIGMOD '17
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privacy preserving algorithms for a number of analysis tasks. ...
Research on differential privacy spanning a number of research areas, including theory, security, database, networks, machine learning, and statistics, over the last decade has resulted in a variety of ...
His research interests include privacy-preserving data analysis, data management, data mining, social networks, and privacy. ...
doi:10.1145/3035918.3054779
dblp:conf/sigmod/Machanavajjhala17
fatcat:2daxnz427fhapnxwi6ezasbcjm
Combating fake news
2019
Proceedings of the VLDB Endowment
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The public popularity of social media and social networks has caused a contagion of fake news where conspiracy theories, disinformation and extreme views flourish. ...
The objective of this tutorial is two-fold. First, we wish to familiarize the database community with the efforts by other communities on combating fake news. ...
His research interests include data mining, social network analysis, and the design of scalable algorithms for graph problems. ...
doi:10.14778/3352063.3352117
fatcat:zvmwkilnifamjndncz6k5qqmr4
Ranking Mechanisms for Interaction Networks
2011
International Conference on Management of Data
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along with applications to social network analysis. ...
In the analysis of interaction networks, an important aspect is to determine a set of key nodes either with respect to positional power in the network or with respect to behavioral influence. ...
for the analysis of interaction networks. ...
dblp:conf/comad/MehtaNP11
fatcat:vrnd6m6iingblkr2zja7l4i4tm
Goals in Social Media, information retrieval and intelligent agents
2015
2015 IEEE 31st International Conference on Data Engineering
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It is the purpose of this tutorial to provide a solid framework for placing existing work into perspective and highlight critical open challenges that will act as a springboard for researchers and practitioners ...
This tutorial provides a comprehensive and cohesive overview of goal modeling and recognition approaches by the Information Retrieval, the Artificial Intelligence and the Social Media communities. ...
practitioners in database systems, social data, and the Web, as well as developers of web-based, database-driven, and social applications, to work towards more user-centric systems and applications. ...
doi:10.1109/icde.2015.7113421
dblp:conf/icde/PapadimitriouVK15
fatcat:qrbjikf4xngzvk5wrgbxbl4upu
Forecasting big time series
2018
Proceedings of the VLDB Endowment
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The objective of this tutorial is to provide a concise and intuitive overview of the most important methods and tools available for solving large-scale forecasting problems. ...
Time series forecasting is a key ingredient in the automation and optimization of business processes: in retail, deciding which products to order and where to store them depends on the forecasts of future ...
Additionally, this tutorial is suitable for practitioners who want a concise, intuitive overview of the state of the art. Prerequisites. ...
doi:10.14778/3229863.3229878
fatcat:dd3pfj3tgfckxcvb23622o5rnq
Mining and Forecasting of Big Time-series Data
2015
Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data - SIGMOD '15
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Time-series data analysis is becoming of increasingly high importance, thanks to the decreasing cost of hardware and the increasing on-line processing capability. ...
How can we statistically summarize all the sequences, and achieve a meaningful segmentation? What are the major tools for forecasting and outlier detection? ...
Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on. ...
doi:10.1145/2723372.2731081
dblp:conf/sigmod/SakuraiMF15
fatcat:dsmv2sqs35bm5ifeqr4qnuz6ty
Fair Graph Mining
2021
Proceedings of the 30th ACM International Conference on Information & Knowledge Management
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In today's increasingly connected world, graph mining plays a pivotal role in many real-world application domains, including social network analysis, recommendations, marketing and financial security. ...
We believe this tutorial could be attractive to researchers and practitioners in areas including data mining, artificial intelligence, social science and beneficial to a plethora of real-world application ...
INTENDED AUDIENCE The tutorial is designed for all researchers and practitioners in data mining, artificial intelligence, social science, as well as related areas. ...
doi:10.1145/3459637.3482030
fatcat:fzg6nb56cjcird7vfkcviqxtni
Graph-Based User Behavior Modeling
2015
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15
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In this tutorial we will answer these questions -connecting graph analysis tools for user behavior modeling to anomaly and fraud detection. ...
For each of these techniques we will give a brief explanation of the algorithms and the intuition behind them. ...
Subgraph patterns in social networks: [40] iii. Influence of subgraphs on recommendation: [41] iv. Co-clustering for recommendation: ACCAMS [6] C. ...
doi:10.1145/2783258.2789985
dblp:conf/kdd/BeutelAF15
fatcat:w2iuowx5dbfwtoonv7kyswo2tm
Building Structured Databases of Factual Knowledge from Massive Text Corpora
2017
Proceedings of the 2017 ACM International Conference on Management of Data - SIGMOD '17
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In this tutorial, we introduce data-driven methods on mining structured facts (i.e., entities and their relations/attributes for types of interest) from massive text corpora, to construct structured databases ...
We focus on methods that are minimally-supervised, domainindependent, and language-independent for timely StructDB construction across various application domains (news, social media, biomedical, business ...
Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon. ...
doi:10.1145/3035918.3054781
dblp:conf/sigmod/RenJSH17
fatcat:3mrzx3e3yzapnknx5ciwcwm4i4
From Complex Object Exploration to Complex Crowdsourcing
2015
Proceedings of the 24th International Conference on World Wide Web - WWW '15 Companion
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Analytics, Indexing, Query Processing and Optimization, Social Networks and Analysis, Graph Databases, Information Retrieval, and Modeling, Mining and Querying User Generated Content. ...
Team formation problems are prevalent in the area of social networks analysis and group recommendations, where the objective is to form a team to solve a problem, or consume some items together. ...
doi:10.1145/2740908.2741994
dblp:conf/www/Amer-YahiaR15
fatcat:53i72tccjjewjhvs62q7codpsa
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