Ilio Catallo

Vita-Salute San Raffaele University

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Co-Authors

Davide Martinenghi

Politecnico di Milano

Piero Fraternali

Politecnico di Milano

Eleonora Ciceri

Vita-Salute San Raffaele University

Marco Tagliasacchi

Google (Switzerland)

Carlo Bernaschina

Politecnico di Milano

Sauro Vicini

Vita-Salute San Raffaele University

Alberto Sanna

Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele

Alessandro Bozzon

Delft University of Technology

Martha Larson

Radboud University Nijmegen

Maurizio Ferrari

Istituti di Ricovero e Cura a Carattere Scientifico

Cooperative Institutions

Politecnico di Milano

Vita-Salute San Raffaele University

Istituti di Ricovero e Cura a Carattere Scientifico

Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele

IRCCS Ospedale San Raffaele

Ingegneria dei Sistemi (Italy)

University of Trento

Atos (Spain)

L3S Research Center

University of Palermo

Author Statistics

Papers

Citation

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On the Role of Task Design in Crowdsourcing Campaigns

Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (2015)

Carlo Bernaschina Ilio Catallo Piero Fraternali Davide Martinenghi

Despite the success of crowdsourcing marketplaces, fully harnessing their massive workforce remains challenging. In this work we study the effect on crowdsourcing campaigns of different feedback and payment strategies. Our results reveal the joint effect of feedback and payment on the quality and quantity of the outcome.

Crowdsourcing

10.1609/hcomp.v3i1.13247

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Citations (1)

The CUBRIK project

Piero Fraternali Marco Tagliasacchi Davide Martinenghi Alessandro Bozzon Ilio Catallo

The Cubrik Project is an Integrated Project of the 7th Framework Programme that aims at contributing to the multimedia search domain by opening the architecture of multimedia search engines to the integration of open source and third party content annotation and query processing components, and by exploiting the contribution of humans and communities in all the phases of multimedia search, from content processing to query processing and relevance feedback processing. The CUBRIK presentation will showcase the architectural concept and scientific background of the project and demonstrate an initial scenario of human-enhanced content and query processing pipeline.

10.1145/2187980.2188023

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Citations (5)

SECONDARY USE OF CLINICAL DATA FOR SCIENTIFIC RESEARCH PURPOSES IN THE DITAS PROJECT

Paola Aurucci Ilio Catallo Mariet NouriJanian Andrea Micheletti Alberto Sanna

Thanks to the advent of the digital revolution, coupled with advances in computing power, medical research is becomingincreasingly data intensive. Extracting meaningful information from data sets and continuous flood of data is a challengebut

10.33965/eh2019_201910l002

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Citations (0)

When Food Matters: Identifying Food-related Events on Twitter.

Eleonora Ciceri Ilio Catallo Davide Martinenghi Piero Fraternali

Food communities in Twitter are growing every year, and food-related content permeates everyday conversations. Users meet on Twitter to share recipes, give cooking advices or simply inform others about what they are eating. While some of these food-related conversations are not associated with any special occurrence, many conversations take place instead during specific events. The detection of food-related events gives interesting insights: people do not talk only about Halloween and Easter, but they also create their own food-related events, such as the promotion of products (e.g., an online petition to propose the production of bacon-flavored chips) or themed home-made recipes (e.g., a day of recipes dedicated to chocolate). In this paper, we propose an approach that accurately captures food-related content from the tweet live stream, and analyze the detected conversations to identify food-related events. The proposed technique is general as it can be applied to the identification of other thematic events in digital streams.

Identification

Promotion (chess)

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Citations (0)

Top-k diversity queries over bounded regions

ACM Transactions on Database Systems (2013)

Ilio Catallo Eleonora Ciceri Piero Fraternali Davide Martinenghi Marco Tagliasacchi

Top-k diversity queries over objects embedded in a low-dimensional vector space aim to retrieve the best k objects that are both relevant to given user's criteria and well distributed over a designated region. An interesting case is provided by spatial Web objects, which are produced in great quantity by location-based services that let users attach content to places and are found also in domains like trip planning, news analysis, and real estate. In this article we present a technique for addressing such queries that, unlike existing methods for diversified top- k queries, does not require accessing and scanning all relevant objects in order to find the best k results. Our Space Partitioning and Probing (SPP) algorithm works by progressively exploring the vector space, while keeping track of the already seen objects and of their relevance and position. The goal is to provide a good quality result set in terms of both relevance and diversity. We assess quality by using as a baseline the result set computed by MMR, one of the most popular diversification algorithms, while minimizing the number of accessed objects. In order to do so, SPP exploits score-based and distance-based access methods, which are available, for instance, in most geo-referenced Web data sources. Experiments with both synthetic and real data show that SPP produces results that are relevant and spatially well distributed, while significantly reducing the number of accessed objects and incurring a very low computational overhead.

Relevance

10.1145/2487259.2487262

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Citations (27)

An Open-Source Tool for Managing Time-Evolving Variant Annotation

Lecture notes in computer science (2019)

Ilio Catallo Eleonora Ciceri Stefania Stenirri Stefania Merella Alberto Sanna

10.1007/978-3-030-14160-8_1

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Citations (0)

A workload-dependent task assignment policy for crowdsourcing

World Wide Web (2017)

Ilio Catallo Stefano Coniglio Piero Fraternali Davide Martinenghi

Crowdsourcing

10.1007/s11280-016-0428-7

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Citations (7)

Orchestrating Privacy Enhancing Technologies and Services with BPM Tools

Proceedings of the 17th International Conference on Availability, Reliability and Security (2017)

Nicolás Notario Eleonora Ciceri Alberto Crespo Eduardo González Real Ilio Catallo

Privacy is a highly complex subject, especially when it comes to balancing data subjects' expectations, requirements and needs with i) the objectives of service providers and data controllers, and ii) the variety of legal obligations that dictate protection rights of data subjects and responsibilities of data controllers. This requires to provide technical solutions capable of matching different and adequate levels of privacy, while still attending to data subjects' preferences and business objectives. The Data Protection Orchestrator (DPO) developed in the context of the WITDOM project1 meets this challenge by interacting with different Protection Enhancing Technologies or Services following a set of pre-defined protection processes, so as to support automated management trade-offs between privacy, performance and utility. By leveraging Business Process Management standards, the DPO is capable of making data protection processes and practices (such as automated anonymization or management of data subject's consent) integral to other business core services, as intended with the data protection by design and by default approach in the EU's GDPR. The DPO capabilities will be explained in the context of two complementary scenarios: the eHealth scenarios, where the DPO will be used for protecting genomic data and the financial scenario where the DPO will be responsible for protecting the transaction history and personal attributes of the bank's customers.

10.1145/3098954.3104057

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Citations (3)

Towards an unbiased approach for the evaluation of social data geolocation

Carlo Bernaschina Ilio Catallo Eleonora Ciceri Roman Fedorov Piero Fraternali

We present a study that reveals a significant statistical bias in the distributions of geolocated and non-geolocated social data. We state that this bias affects the real performance of social geolocation algorithms and can impair the results of these algorithms, which are commonly trained and tested on datasets consisting of crawled geolocated data. At last, we propose the construction of an a-posteriori geolocated dataset for an unbiased estimation of new and state-of-the-art algorithms alike.

Geolocation

Unbiased Estimation

10.1145/2837689.2837697

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Citations (2)

Champagne

Carlo Bernaschina Ilio Catallo Piero Fraternali Davide Martinenghi Marco Tagliasacchi

We present Champagne, a web tool for the execution of crowdsourcing campaigns. Through Champagne, task requesters can model crowdsourcing campaigns as a sequence of choices regarding different, independent crowdsourcing design decisions. Such decisions include, e.g., the possibility of qualifying some workers as expert reviewers, or of combining different quality assurance techniques to be used during campaign execution. In this regard, a walkthrough example showcasing the capabilities of the platform is reported. Moreover, we show that our modular approach in the design of campaigns overcomes many of the limitations exposed by the major platforms available in the market.

Crowdsourcing

Software walkthrough

10.1145/2740908.2742838

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Citations (5)