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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

Sören Auer – Leipzig, Germany

Digitalization of Scholarly Communication - Towards a Knowledge Graph for Science
Despite an improved digital access to scientific publications in the last decades, the fundamental principles of scholarly communication remain unchanged and continue to be largely...
Mastering Digitalization - Towards the Data-driven Enterprise
Mastering the digitalization challenge requires enterprises to radically innovate. Data, information and knowledge become increasingly important assets for realizing innovative digital...
Tackling the Variety Dimension of Big Data - From Linked to Cognitive Data
In recent years, we have seen an increasing attention to data. Some initiatives in this regard are open, big or smart data. The availability of large-scale datasets has unleashed an...

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 – Rajam, 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...

Syed Ahmad Chan Bukhari – CT, United States

Experimental Reproducibility, Standardization and FAIR Scientific Data
B and T cells form the two pillars of the adaptive immune system, and both express antigen-specific receptors at their surface, namely, B cell receptors (BCRs) and T cell receptors (TCRs),...

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...

Marcus Foth – Brisbane, QLD, Australia

Smart Cities beyond Fad and Hype: Connecting People, Place and Technology
Ubiquitous computing, mobile devices, and big data come together to give rise to a new urban paradigm being celebrated by many technology corporations and local governments alike: the smart...

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...

Laura M Haas – San Jose, CA, United States

Accelerating Data Discovery for Better Health
The volumes of healthcare data are sky-rocketing, and new sources and types of patient, biology, medical and contextual information are proliferating; we can now get more data on patients and...
Accelerating the Discovery of Insights from Data
Today, businesses and scientists alike struggle to get to the value in their data. Their challenges include finding and gaining access to the data they need, “wrangling” the...
The Power Behind the Throne: Information Integration in the Age of Data-Driven Discovery
Integrating data has always been a challenge. The information management community has made great progress in tackling this challenge, both on the theory and the practice. But in the...

Panos Ipeirotis – New York, NY, United States

Detecting Misconduct and Malfeasance within Financial Institutions
Misbehavior in the online world manifests itself in several forms, and often depends on the domain at hand. In the financial domain, firms have the regulatory obligation to self-monitor the...
Targeted Crowdsourcing with a Billion (Potential) Users
We describe Quizz, a gamified crowdsourcing system that simultaneously assesses the knowledge of users and acquires new knowledge from them. Quizz operates by asking users to complete short...

Seiji Isotani – Sao Carlos - SP, Brazil

Understanding Ontologies and Ontology Engineering
Computer science borrows the term ontology from a branch of philosophy (metaphysics) that studies the nature of “being” and “existence.” For philosophers, ontology aims at...

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...

Uri Kartoun – Cambridge, MA, United States

Advancing Informatics with Electronic Medical Records Bots
Electronic medical records (EMRs) contain sensitive and detailed documentation on a variety of conditions at the individual level. Because EMRs are subject to confidentiality requirements,...
How to Develop Prediction Models Using Electronic Medical Records
Recent remarkable advancements in computer hardware and software and the growing accessibility of electronic medical records (EMRs) have accelerated research on predicting patient outcomes....
How to Develop a Disease Classification Algorithm Using Electronic Medical Records
A patient might be associated with a disease, but the disease may not be clearly documented in the patient’s medical profile. Often, a disease may be mentioned in the context of being...
Why and How to Invent in the Era of Software
Throughout my employment in corporate environments (Microsoft, IBM), as well as in start-ups, I have had the opportunity to solely invent many items and apply for patents. My inventions...

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...

Georgia Koutrika – Athens, Greece

Deep learning in recommender systems
Deep learning methods have dramatically improved the state-of-the-art in computer vision, speech recognition, natural language processing (NLP) and many other domains. Deep learning started to...
Modern recommender systems in action (I know what movie you will watch in Netflix)
Recommender systems provide advice on items that may be of interest to a user (e.g., movies, products, travel, and leisure activities) by learning user preferences and relationships between users...
Modern recommender systems: matrices, bandits, and neurons
The proliferation of digital content in a plurality of forms (including e-news, movies, and online courses), along with the popularity of portable devices has created immense opportunities as well...
Multi-armed bandits in recommender systems
Traditional recommender systems can provide meaningful recommendations at an individual level by leveraging users' interests as demonstrated by their past activity. However, in many web-based...

Dongwon Lee – State College, PA, United States

Human Computation in Data Science
As a novel computation paradigm, human computation (a.k.a. crowdsourcing) is being actively pursued in diverse academic disciplines. Within computer science, many sub-fields have also embraced the...
LIKEs-R-Us: Analyzing LIKEs in Social Media
The recent dramatic increase in the usage and prevalence of social media has led to the creation and sharing of a significant amount of information in various formats such as texts, photos, or...

Dirk Lewandowski – Hamburg, Germany

THE POWER OF SEARCH ENGINES
Search engines are the premier tools when it comes to finding information on the Internet. Newer technological developments show how search is changing from the query-results paradigm to...

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...

Sanjay Kumar Madria – Rolla, MO, United States

M-Grid: A Scalable Distributed Framework for Multidimensional Indexing and Querying Spatial Data
The widespread use of mobile devices and the real time availability of user-location information both facilitating the development of new personalized, location-based applications and...
Opportunistic Distributed Caching for Mission-oriented Delay-tolerant Networks
In this talk, a new caching scheme has been proposed which takes into consideration mission-oriented applications of Delay-tolerant Networks (DTNs) such as in Military. In such applications data...

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...

Vishnu S Pendyala – San Jose, CA, United States

Approaches to Establishing the Veracity of Big Data
In spite of their anthropomorphic role, unlike human beings, technological inventions such as the Web do not have a conscience. Still, there is often more reliance on the big data emanating...
Mining for Medical Expertise
There are huge masses of population in the world without access to sufficient healthcare. The World Health Organization (WHO) statistics show that disease and mortality rate greatly depend...
Statistical Modeling for Detecting Cognitive Hacking on Microblog Websites
Cognitive hacking and fraud on Social Media have been so rampantly impactful that sometime back, the Founder, Chairman, and CEO of Facebook, Mark Zuckerberg testified to the US congress...

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...

Shrisha Rao – Bangalore, India

Services Science and Services Computing
New models of computation such as cloud computing, Big Data, and the Internet of Things have fundamentally upended common assumptions about the nature and purposes of computation. One thing...

Abhishek Roy – San Francisco, United States

An in-depth Study on Smart Grids with special significance on South Korea
Smart Grid is an inevitable trend of power grid, and smart grid comprehensive assessment system can conduct a comprehensive assessment of the overall characteristics of smart grid, which can...
Demand Response in Smart Grid
Smart grids are conceived of as electric power grids, capable of delivering electricity in a controlled,smart way from energy generator to active consumers. Demand response (DR), by promoting the...
VISION OF IoT IN KOREA
After the World Wide Web in 1990s and the mobile internet in 2000s, we are gradually moving towards one of the potentially most distinct phase of internet revolution--The "Internet of Things...

Hanan Samet – College Park, MD, United States

Issues in Spatial Databases and Geographic Information Systems (GIS)
An introduction is given to the spatial database issues involved in the design of geographic information systems (GIS) from the perspective of a computer scientist. Some of the topics...
Reading News with Maps by Exploiting Spatial Synonyms
NewsStand is an example application of a general framework to enable people to search for information using a map query interface, where the information results from monitoring the output...
Scalable Network Distance Browsing in Spatial Databases*
An algorithm is presented for finding the k nearest neighbors in a spatial network in a best-first manner using network distance. The algorithm is based on precomputing the shortest paths...

Jibonananda Sanyal – Oak Ridge, TN, United States

Accelerated Global Human Settlement Discovery
Understanding where people live is fundamental to understanding what people do and what their social needs are with respect to energy security; policy and urban development; resiliency;...
Data and Sensemaking
Humans are generating data at an unprecedented scale and making sense of this data is increasingly a challenge. This talk weaves around experiences in deriving scientific knowledge from ensemble...
Deriving insight at the intersection of the Energy-Water Nexus
Energy and water generation and delivery systems are inherently interconnected. With demand for energy growing, the energy sector is experiencing increasing competition for water. ...
Ensemble-Aware Uncertainty Visualization
Understanding uncertainty in scientific simulations is fundamental in gaining reliable insight into a scientific process. In simulation and modeling, ensembles approaches are recognized as...

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...

Shan Suthaharan – Greensboro, NC, United States

Software engineering schema for data science and big data
This talk will present a newly created software development framework called SETh - it stands for software engineering theoretical framework. It comprises six visual models - TBoSE, TCoSE, TDoSE,...

André Tricot – Toulouse, France

The upward and downward links between credibility, trust and authority
The Internet and its main tools (Google, Wikipedia, Facebook, Tweeter) deeply raise and renew fundamental questions, that everyone asks almost everyday: Is this information or content true? Can I...

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...

Ping Zhang – Columbus, OH, United States

Predictive Modeling of Drug Effects: Learning from Biomedical Knowledge and Clinical Records
Drug discovery is a time-consuming and laborious process. Lack of efficacy and safety issues are the two major reasons for which a drug fails clinical trials, each accounting for around 30% of...