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Information Systems, Search, Information Retrieval, Database Systems, Data Mining, Data Science

Information Systems, Search, Information Retrieval, Database Systems, Data Mining, Data Science

Available Speakers on this Topic

Ricardo Baeza-Yates – Palo Alto, CA, United States

Information Retrieval
This tutorial covers all the main concepts behind search: relevance, retrieval models, quality evaluation, indexing and ranking. At the same time, we explain all the elements of the architecture...
Web Data Mining
The Web continues to grow and evolve very fast, changing our daily lives. This activity represents the collaborative work of the millions of institutions and people that contribute content to the...

Santhosh Kumar Balan – Hyderabad, India

Data Analysis using Jupyter Notebook
Data analysis is a cycle of reviewing, purging, changing and demonstrating data with the objective of finding valuable data, advising ends and supporting dynamic. Data analysis has various...
Data Science
Data is the center of ventures and organizations in the present time. With the ascent in Big Data associations around the world are taking a gander at the capability of data available to...
Data Science for Beginners
Data Science is the zone of study which includes extricating experiences from huge measures of data by the utilization of different logical techniques, calculations, and cycles. It...
Data Science-Art of Life
As the world entered the period of enormous data, the requirement for its stockpiling likewise developed. It was the primary test and worry for the undertaking enterprises until 2010. The...
Research issues in Data Mining
Data Mining is characterized as the methodology of extricating data from gigantic arrangements of data. At the end of the day, we can say that data mining will be mining information from...

Athman Bouguettaya – Sydney, NSW, Australia

From IoT Data to Services
The Internet of Things (IoT) is fast becoming a reality with a range of everyday “things” becoming sensor-equipped and internet connected. Ultimately, everything that we see and...
Taming Big Data
Big data is here and in a big way. Big data is coming from all sorts of sources and means, including sensors, deep space exploration, social media, smartphones, genomic, etc. The cloud...

Sharma Chakravarthy – Bedford, TX, United States

Data-Driven Analysis: Decomposition-Based Approach for Multilayer Networks (MLNs)
We are on the cusp of holistically analyzing a variety of data being collected in every walk of life in diverse ways. For this, current analytics and science are being extended (Big Data...
Video Situation Analysis Using Stream Data Processing
We are on the cusp of holistically analyzing a variety of data being collected in every walk of life in diverse ways. For this, current analytics and science are being extended (Big Data...

Gianluca Demartini – Queensland, Australia

Knowledge Graphs for Entity-centric Information Access
Knowledge Graphs (KGs) contain structured information about entities such as persons, locations, and organizations. Modern web search engines leverage such KGs to power entity-oriented...
The Power of Big Data
More and more data is being generated around us by every activity in our daily life. Such large amounts of data are changing the way in which we do things and are used by companies and...

Ujwal Gadiraju – Delft, Netherlands

Supporting Knowledge Gain in Web Search Sessions
More than half of the world’s population has access to the Internet today. Satisfying one’s information needs has never been easier and more ubiquitous. We can catch ourselves turning...

Javier Gonzalez-Sanchez – Tempe, AZ, United States

Affect-Driven Self-Adaptation: A Step Forward in Human-Centered Software
Affect signals what humans care about and is involved in rational decision-making and action selection. Many technologies may be improved by the capability to recognize human affect and to...

Giancarlo Guizzardi – Bolzano, Italy

A Relational View on Services, Contracts, Trust, Value, and Risk
The Relationship construct is one of the most fundamental constructs in the conceptual modeling/knowledge engineering toolbox.

In this talk, I present...
A World of Objects and Events
Different disciplines have been established to deal with the representation of entities of different ontological natures: the business process modeling discipline focuses mostly on...
Carving Reality at its Digital Joints: The Role of Philosophical Ontology in Designing Future Sociotechnical Systems
We live much of our lives immersed in the world of made up structures that we call Social Reality. In other words, much of our lives are governed by socially constructed (and, hence,...
It's Patterns all the Way Down: Ontological Patterns, Anti-Patterns and Pattern Languages for Next-Generation Conceptual Modeling
In his ACM Turing Award Lecture entitled “The Humble Programmer”, E. W. Dijkstra discusses the sheer complexity one has to deal with when programming large computer systems. His...
Ontology, Interoperability and the "I" of FAIR
According to the FAIR (Findable, Accessible, Interoperable, Reusable) guiding principles for Data Management, one of the central attributes for maximizing the added value of information...
What's in a (Conceptual) Model?: A Philosophical Account
This talk discusses the philosophical foundations of conceptual modeling by addressing a number of foundational questions such as: What is a conceptual model? Among models used in computer...

Nikolas Ioannou – Zurich, Switzerland

Reaping the performance of solid-state storage
The high-performance storage landscape is being shaped by three main developments: a) Flash memories are scaling to extreme densities (e.g., 3D-TLC, QLC), b) new storage devices offer...
Toward a better understanding and benchmarking of tree data structures on flash SSDs
Solid-state drives (SSDs) are extensively used to deploy persistent data stores, as they provide low latency random access, high write throughput, high data density, and low cost....

Anura Jayasumana – Fort Collins, CO, United States

Finding Emergent Patterns of Behaviors in Dynamic Heterogeneous Social and Behavioral Data: Experience with Violent Extremist Radicalization Trajectories
The search for individuals or entities undertaking latent or emergent behaviors has applicability in the areas of homeland security, consumer analytics, behavioral health, and cybersecurity. In...
On Sampling and Reconstruction of Large-Scale Networks using Graph Geodesics, Matrix Completion and Machine Learning
Extracting connectivity information in massive social networks is important for many applications. We present a method to extract the network topology from a small sample of geodesics...

Latifur Rahman Khan – Plano, TX, United States

Big Data Stream Analytics & Its Applications
Data streams are continuous flows of data. Examples of data streams include network traffic, sensor data, call center records and so on. Data streams demonstrate several unique properties...
Data to Knowledge: Modernizing Political Event Data for Big Data Social Science
We have developed the software and big data infrastructure to provide machine coded event data from...

Wajahat Ali Khan – Derby, United Kingdom

Interoperability among Medical Systems
Over the last decade, rapid digitization in the field of healthcare information management, has compounded the problem of Heterogeneity, through the development of a...
Medical Silo Construction Methodology
This study will demonstrate silo construction process for different clinical domains such as cardiovascular, diabetes, epilepsy, kidney, ear throat nose (ENT), thyroid cancer, and head and neck...

Asad Masood Khattak – Abu Dhabi, United Arab Emirates

Cybersecurity Challenges of Critical Cyber Infrastructure
A smart city is a city which invests in ICT enhanced governance and participatory processes to develop appropriate public service, transportation, and energy infrastructure, that can ensure...
The Impact of Data Curation in Scientific Research
In recent years, the focus of experts and research in the field of Computer Science and Information Technology has shifted towards data driven fields e.g., Data Science, Data Analytics and Data...

Zitao Liu – Beijing, China

AI the Next Step for Education: Tech Innovations Making Our Classrooms Smarter
With the recent development of AI, there has been tremendous changes in both offline and online education. Entire in-class interactions and behaviors between students and instructors have been...

Kayal Padmanandam – Hyderabad, India

Data Science Foundation using R Programming
Data science is a multifaceted research domain that uses scientific methods, processes, algorithms, and systems to dredge knowledge and insights from structured and unstructured data. This...

Themis Palpanas – Paris, France

Scalable Machine Learning on Large Sequence Collections
There is an increasingly pressing need, by several applications in

diverse domains, for developing techniques able to analyze very large collections of sequences, or data...

Ebin Deni Raj – Pala, Kottayam, India

Houston, We have a problem with the Data !!! Data cleaning using R
The real ground data, most of the time will be really messy. Data cleaning is not only an essential component but also it is the one which takes most of the time in any data science...
Navigating the Dataways of Data Science:The process, steps and hype
This talk is about the significance and the overview of the process behind it. The ingredients to become a better data scientist and to also be cautious about the hype created by AI and Data...
Show me the figures! Statistical Modelling using R
Statistical data is a kind of summary of data. The summary can be a way to encapsulate patterns in data.

Some of these models are part of what’s called “machine...

Ashish Seth – Tashkent, Uzbekistan

Data Analysis Using R programming
Data have become a real resource of interest across most industries and is rightly considered the gateway to competitive advantage and disruptive strategy. Along with the rise of data,...

Neha Sharma – Pune, India

Demystifying Data Science
Data science is known as a "fourth paradigm" of science (empirical, theoretical, computational and now data science), mainly due to the present data surge. The society is transforming...
Journey from Data To Data Product
The APIs published by Netflix, LinkedIn, Twitter, Facebook etc are the examples of data product. The lecture would emphasize on the journey of data from being raw to getting converted to data...
Network Analytics
Network Analysis is a subset of unsupervised Analytics ie. Data Mining Process / Machine Learning....
Unchain the Block Chain
Blockchain technology or Distributed ledger technology (DLT) refers to a type of database spread over multiple locations, which can be used like a digital ledger to record and manage...
Use of Open Data for sustainable community
The contribution to Community and Environment is part of every body’s responsibility. The lecture on “Use of Open Data for Sustainable Community” is an attempt to bring out value...

Gautam Srivastava – Brandon, MB, Canada

Solving Cloud Computing as a Security Vulnerability
Many systems are encompassing both cloud storage and cloud computing in their architectures. However, these systems are still vulnerable to a very well-known class of security breaches...

Christoph Trattner – Bergen, Norway

Data Science on the Web for Better Food Decision Making
According to the World Health Organization around 80% of cases of heart disease, strokes and type 2 diabetes could be avoided if people were to implement a healthier diet. Computational data...
Online food recommendations
Similar to Online food recommendations: A complex problem? but also adresses the propblem of Similar food recommendations and gives insightes to the problme of collaborative filtering vs...
Online food recommendations: A complex problem?
The problem of recommending food to people has recently become an active field of research. While there is a growing body of work investigating how online food recommender systems could...

Athena Vakali – Thessaloniki, Greece

My tweets bring all the traits to the yard: Predicting personality and relational traits in online social networks
Activity of users in Online Social Networks (OSN) leaves traces that reflect their personality characteristics. The study of these traces is important for a number of fields, such as a social...
On the Aggression Diffusion Modeling and Minimization In Online Social Networks
Aggression in online social networks has been studied mostly from the perspective of machine learning which detects such behavior in a static context. However, the way aggression diffuses in the...
TG-OUT: Temporal outlier patterns detection in Twitter attribute induced graphs
Given a node-attributed network of Twitter users, can we capture their posting behavior over time and identify patterns that could probably describe, model or predict their activity? Based...
Wearable Analytics :a systematic survey and an evidence-based framework
In today’s connected society, many people rely on mHealth and self-tracking (ST) technology to help them break their sedentary lifestyle and stay fit. However, there is scarce...

Ingmar G Weber – Doha, Qatar

Introduction to Computational Social Science
Due to the increasing availability of large-scale data on human behavior collected on the social web, as well as advances in analyzing larger and larger data sets, interest in applying...