Distributed Search and Recommendation with Profile Diversity
INRIA & CNRS, University Montpellier –
With the advent of Web 3.0, the Internet of things, and citizen science applications, users are producing bigger and bigger amounts of diverse data, which are stored in a large variety of systems. Since the users’ data spaces are scattered among those independent systems, data sharing becomes a challenging problem. Distributed search and recommendation provides a general solution for data sharing and among its various alternatives, gossip-based approaches are particularly interesting as they provide scalability, dynamicity, autonomy and decentralized control. Generally, in these approaches each participant maintains a cluster of “relevant” users, which are later employed in query processing. However, only considering relevance in the construction of the cluster introduces a significant amount of redundancy among users, which in turn leads to reduced recall. Indeed, when a query is submitted, due to the high similarity among the users in a cluster, the probability of retrieving the same set of relevant items increases, thus limiting the number of distinct results that can be obtained. In this talk I will present the resultant new gossip-based clustering algorithms and validate them through experimental evaluation over four real datasets, we show that taking into account diversity based clustering score enables to obtain major gains in terms of recall. In addition, I will also present same ongoing work on scientific data management carried by Zenith Inria team.
Esther Pacitti is a full professor of Computer Science at University of Montpellier in the south of France. She is co-head of the Zenith team (Inria&Cnrs), pursuing her research in distributed data management and scientific data management. She teaches in an engineering school (Polytech’ Montpellier) where she is responsible for international relations, welcoming foreign students. Previously, she was an assistant professor at the University of Nantes (2002-2009). Her teaching and research interests include data replication, recommendation systems, query processing in large-scale distributed systems (cluster, P2P, cloud) and scientific workflow management. She has published more than 90 technical papers. She has served or is serving as program committee member of major international conferences including SIGMOD, ICDE, CIKM ,VLDB, EDBT, etc.
Date: 2018-Jun-11 Time: 14:30:00 Room: 336
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OLISSIPO Summer School in Lisbon | Computational phylogenetics to analyse the evolution of cells and communities
We are happy to announce the OLISSIPO Summer School on Computational phylogenetics to analyse the evolution of cells and communities, which will be held in Lisbon, Portugal, at INESC-ID, between July 2-7, 2023.
David Posada, University of Vigo (class)
João Alves, University of Vigo (hands-on)
Nadia El-Mabrouk, Université de Montréal (class)
Mattéo Delabre, Université de Montréal (hands-on)
Ran Libeskind-Hadas, Claremont McKenna College (class and hands-on)
Russell Schwartz, Carnegie Mellon University (class and hands-on)
See the preliminary agenda at: https://olissipo.inesc-id.pt/tree-tango-school
Registration is mandatory. You can register at: https://forms.gle/VsASFHW5E7MJvaCc9
The registration fee is 250€ for students and OLISSIPO members and 350€ for postdocs or other researchers (meals indicated at the schedule of the school are included, accommodation and flights are not). All details will be made available upon registration.
We will have slots for flash talks (3-10 min depending on the number of submissions) to present yourself and the work you have been developing in your research.
The 13th Lisbon Machine Learning School | LxMLS 2023
The Lisbon Machine Learning Summer School (LxMLS) takes place yearly at Instituto Superior Técnico (IST). LxMLS 2023 will be a 6-day event (14-20 July, 2023), scheduled to take place as an in-person event.
The school covers a range of machine learning topics, from theory to practice, that are important in solving natural language processing problems arising in different application areas. It is organized jointly by Instituto Superior Técnico (IST), a leading Engineering and Science school in Portugal, the Instituto de Telecomunicações, the Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa (INESC-ID), the Lisbon ELLIS Unit for Learning and Intelligent Systems (LUMLIS), Unbabel, Zendesk, and IBM Research.
Check online for information about past editions: LxMLS 2011, LxMLS 2012, LxMLS 2013, LxMLS 2014, LxMLS 2015, LxMLS 2016, LxMLS 2017, LxMLS 2018, LxMLS 2019, LxMLS 2020, LxMLS 2021, LxMLS 2022 (you can also watch the videos of the lectures for 2016, 2017, 2018, and 2020).
31st International Conference on Information Systems Development (ISD 2023)
The 31st International Conference on Information Systems Development (ISD 2023) conference provides a forum for research and developments in the field of information systems. The theme of ISD 2023 is “Information systems development, organizational aspects and societal trends”. New trends in developing information systems emphasize the continuous collaboration between developers and operators in order to optimize the software delivery time. The conference promotes research on methodological and technological issues and how IS developers and operators are transforming organizations and society through information systems.
The ISD 2023 conference held this year also provides an opportunity for researchers and practitioners to promote their research, practical experience, and to discuss issues related to Information Systems through papers, posters, and journal-first paper presentations.
ISD 2023 will be hosted by Instituto Superior Técnico, in Lisbon, Portugal, on August 30–September 1, 2023.