A5000949710- Optimization and Search Problems
- Data Management and Algorithms
- Complex Network Analysis Techniques
- Complexity and Algorithms in Graphs
- Algorithms and Data Compression
- Opinion Dynamics and Social Influence
- Social Media and Politics
- Privacy-Preserving Technologies in Data
- Misinformation and Its Impacts
- Wikis in Education and Collaboration
- Web Data Mining and Analysis
- Financial Distress and Bankruptcy Prediction
- Topic Modeling
- Caching and Content Delivery
- Spam and Phishing Detection
- Digital Media Forensic Detection
- Advanced Database Systems and Queries
- Imbalanced Data Classification Techniques
- Advanced Graph Neural Networks
- Advanced Queuing Theory Analysis
- Auction Theory and Applications
- Media Influence and Politics
- Scheduling and Timetabling Solutions
- Distributed systems and fault tolerance
- Mobile Crowdsensing and Crowdsourcing
Sapienza University of Rome
2015-2024
Weatherford College
2021
Flint Institute Of Arts
2021
Max Planck Institute for Informatics
2013
Yahoo (United Kingdom)
2006-2008
Yahoo (United States)
2006-2008
Brown University
2003-2006
John Brown University
2001-2006
In many online social systems, ties between users play an important role in dictating their behavior. One of the ways this can happen is through influence, phenomenon that actions a user induce his/her friends to behave similar way. systems where influence exists, ideas, modes behavior, or new technologies diffuse network like epidemic. Therefore, identifying and understanding tremendous interest from both analysis design points view.
We study the problem of online team formation. consider a setting in which people possess different skills and compatibility among potential members is modeled by social network. A sequence tasks arrives an fashion, each task requires specific set skills. The goal to form new upon arrival task, so that (i) possesses all required (ii) has small communication overhead, (iii) workload performing balanced fairest possible way.
With the fast growth of smart devices and social networks, a lot computing systems collect data that record different types activities. An important computational challenge is to analyze these data, extract patterns, understand activity trends. We consider problem mining networks identify interesting events, such as big concert or demonstration in city, trending keyword user community network.
No abstract available.
The internet has enabled the collaboration of groups at a scale that was unseen before. A key problem for large is to be able allocate tasks effectively. An effective task assignment method should consider both how fit teams are each job as well fair team members, in terms no one overloaded or unfairly singled out. done automatically semi-automatically given it difficult and time-consuming keep track skills workload person. Obviously do this must also computationally efficient.
The annual cost of vehicle insurance fraud is estimated to exceed 40 billion dollars. This an enormous amount considering the number new vehicles insured yearly. In terms higher premiums, it implies that incurs additional each U.S. family $400 $700, on average. Many frauds can be attributed previously reported damages, which are submitted a second time company. these cases, does not suffice check customer's history identify them: Damaged car panels removed from one and reassembled another...
This work introduces distance-based criteria for segmentation of object trajectories. Segmentation leads to simplification the original objects into smaller, less complex primitives that are better suited storage and retrieval purposes. Previous on trajectory attacked problem locally, segmenting separately each database. Therefore, they did not directly optimize inter-object separability, which is necessary mining operations such as searching, clustering, classification large databases. In...
Contextual Advertising is a type of Web advertising, which, given the URL page, aims to embed into page (typically via JavaScript) most relevant textual ads available. For static pages that are displayed repeatedly, matching can be based on prior analysis their entire content; however, need matched also new or dynamically created cannot processed ahead time. Analyzing body such on-the-fly entails prohibitive communication and latency costs. To solve three-horned dilemma either low-relevance...
Query recommendation is an integral part of modern search engines. The goal query to facilitate users while searching for information. also allows explore concepts related their information needs.
Few IoT systems monitoring energy consumption in buildings have focused on the educational community. domain can jump-start a process of sustainability awareness and behavioral change toward savings, as well provide tangible financial savings. We present real-world multisite deployment, comprising 19 school buildings, aiming at enabling IoT-based lectures, promoting energy-saving behaviors supported by data. discuss scenarios where IoT-enabled applications are integrated into life, providing...
Abstract Context The risk stratification of patients with differentiated thyroid cancer (DTC) is crucial in clinical decision making. most widely accepted method to assess recurrent/persistent disease described the 2015 American Thyroid Association (ATA) guidelines. However, recent research has focused on inclusion novel features or questioned relevance currently included features. Objective To develop a comprehensive data-driven model predict persistent/recurrent that can capture all...
We consider the problem of efficiently sampling Web search engine query results. In turn, using a small random sample instead full set results leads to efficient approximate algorithms for several applications, such as:
Designing advanced health monitoring systems is still an active research topic. Wearable and remote devices enable of physiological clinical parameters (heart rate, respiration temperature, etc.) analysis using cloud-centric machine-learning applications decision-support to predict critical states. This paper moves from a totally concept more distributed one, by transferring sensor data processing tasks the edges network. The resulting solution enables interpretation sensor-data traces...
Motivated by applications that concern graphs are evolving and massive in nature, we define a new general framework for computing with such graphs. In our framework, the graph changes over time an algorithm can only track these explicitly probing graph. This captures inherent tradeoff between complexity of maintaining up-to-date view quality results computed available view. We apply this to two classical connectivity problems, namely, path minimum spanning trees, obtain efficient algorithms.
We study opinion dynamics in multi-agent networks when a bias toward one of two possible opinions exists, for example reflecting status quo versus superior alternative. Our aim is to investigate the combined effect bias, network structure, and on convergence system agents as whole. Models such evolving processes can easily become analytically intractable. In this paper, we consider simple yet mathematically rich setting, which all initially share an initial representing quo. The evolves...
Co-clustering is the simultaneous partitioning of rows and columns a matrix such that blocks induced by row/column partitions are good clusters. Motivated several applications in text mining, market-basket analysis, bioinformatics, this problem has attracted severe attention past few years. Unfortunately, to date, most algorithmic work on been heuristic nature.
Graph neural networks (GNNs) excel in learning from network-like data but often lack interpretability, making their application challenging domains requiring transparent decision-making. We propose the Kolmogorov-Arnold Network (GKAN), a novel GNN model leveraging spline-based activation functions on edges to enhance both accuracy and interpretability. Our experiments five benchmark datasets demonstrate that GKAN outperforms state-of-the-art models node classification, link prediction, graph...
We study the unsplittable flow on a path problem (UFP), which arises naturally in many applications such as bandwidth allocation, job scheduling, and caching. Here we are given with nonnegative edge capacities set of tasks, characterized by subpath, demand, profit. The goal is to find most profitable subset tasks whose total demand does not violate capacities. Not surprisingly this has received lot attention research community. If each task at small enough fraction δ capacity along its...
The spreading of unsubstantiated rumors on online social networks (OSN) either unintentionally or intentionally (e.g., for political reasons even trolling) can have serious consequences such as in the recent case about Ebola causing disruption to health-care workers. Here we show that indicators aimed at quantifying information consumption patterns might provide important insights virality false claims. In particular, address driving forces behind popularity contents by analyzing a sample...