Cornet – Page 8 – Laboratoire Informatique d’Avignon

Serial Speakers – Collection of Annotated TV Serials

4 December 2020

This dataset consists of 3 TV series with manual annotations: All three files are in .json format and contain TV Series annotated data. Each TV Series is defined by its name, A TV Series contains seasons, defined by their ids. Every season is made of episodes, defined by their ids, titles, duration and fps. Each episode contains two basic kinds of data: scenes and speech segments. Scenes are defined by starting points and are made of shots (Seasons 1 only).A shot is defined by starting and ending positions, and recurring shot ids. The speech segments are defined by their starting and ending points; textual content (here encrypted for copyright reasons); speaker; possible interlocutors.

WAC – Wikipedia Abusive Conversations

4 December 2020

This dataset contains conversations between Wikipedia editors, which are annotated in terms of various types of abuse, at the level of messages. It aligns two existing corpora:

Social Network of Emperor Trajan

4 December 2020

These scripts aim at analyzing a historical dataset describing the relationships between Roman emperor Trajan and his entourage. It does the following:

PhD defense of Cyril Sahuc – 1st December 2020

1 December 2020

On December 1st, 2020, at 2:00 PM in the meeting room of LIA. Title: Mathematical Approaches for Retail Area Planning: Linear Models, Algorithms, and Multi-Agent Systems. Thesis in collaboration with Cyrille Genre-Grandpierre (UMR Espace) as part of an industrial regional scholarship. Due to the situation, the defense will be held remotely (like all theses currently).

PhD defense of Carlos González – 18 December 2019

18 December 2019

Thesis defense of Carlos González entitled ‘Multimedia and Multilingual Automatic Summarization and Information Retrieval’ on Wednesday, December 18, 2019, at 2:00 PM in the Thesis Room (Saint Marthe – City Center). Jury: Abstract: As multimedia sources have become massively available online, helping users to understand the large amount of information they generate has become a major issue. One way to approach this is by summarizing multimedia content, thus generating abridged and informative versions of the original sources. This PhD thesis addresses the subject of text and audio-based multimedia summarization in a multilingual context. It has been conducted within the framework of the Access Multilingual Information opinionS (AMIS) CHISTERA-ANR project, whose main objective is to make information easy to understand for everybody. Text-based multimedia summarization uses transcripts to produce summaries that may be presented either as text or in their original format. The transcription of multimedia sources can be done manually or automatically by an Automatic Speech Recognition (ASR) system. The transcripts produced using either method differ from wellformed written language given their source is mostly spoken language. In addition, ASR transcripts lack syntactic information. For example, capital letters and punctuation marks are unavailable, which means sentences are nonexistent. To deal Plus d'infos

Multiple Partitioning of Multiplex Signed Networks

4 December 2019

These scripts were designed to analyze the European Parliament votes through a multiplex network-based approach. Our tool was applied to data representing the activity of the members of the European Parliament (MEPs) during the 7th term (from June 2009 to June 2014). The raw data describing this activity were retrieved from the It’s Your Parliament website. There were some minor issues with these data, which we had to correct: some MEPs were represented twice, some profiles were incomplete, the policy domains were not defined for all vote texts, etc. These cleaned data, as well as our figures and results, are available on Zenodo.

ANR DeCoMaP Project

1 September 2019

DeCoMaP: Detecting Corruption in Public Procurement The societal benefits of opening up public data are expected to be huge. This is particularly true with Public Procurement Data which are supposed to help discover and dismantle corrupt activities by facilitating critical information, tools, and mechanism for judicial enforcement. In a multidisciplinary project, bridging computer science, economics and law, DeCoMap is intended to collect, process and analyze French procurement data in order to create a software tool for automatic identification of corruption and fraud in public procurement (automated red flagging) and provide normative analytical grid by highlighting the main factors that public authorities should identify and pay attention to. Supported by Transparency International France and Open Contracting Partnership, DeCoMap brings together academic researchers from 7 universities, with strong expertise in procurement and digital law, procurement economics and econometrics, law and economics, graph optimization and complex network analysis. 4 members of Datactivist, a cooperative company that assists organizations from the public, private and non-profit sectors in producing and re-using Open Data, with strong expertise with open data of public procurement, open contracting and open government, complement the consortium. Date: 2019–2024 Website: https://decomap.univ-avignon.fr ANR page: https://anr.fr/Projet-ANR-19-CE38-0004

Random generation of signed graphs

3 December 2018

These scripts were designed to randomly generate signed graphs possessing some form of community structure, in order to assess partitioning algorithms. Various aspects of the graphs can be specified by the user.

Web-based event detection for political science

3 December 2018

This software takes the name of a public person and a period, and retrieve all events available online involving this person during this period. It first performs a Web search using various engines, then retrieves the corresponding Web pages, performs NER (named entity recognition), uses these entities to cluster the articles, and considers each cluster as the description of a specific event. It is designed to handle Web pages in French, but should work also for English.

Extraction and partition of voting networks

2 December 2018

These were designed for three purposes: Generate a variety of plots and statistics based on some raw data describing the voting activity of a population. Extract so-called vote networks from these data. Perform various analyses on these networks, in particular: estimate good partitions of the network, according to different measures. Our tool was applied to data representing the activity of the members of the European Parliament (MEPs) during the 7th term (from June 2009 to June 2014), as described in [MFL’15a, MFL’15b]. The raw data describing this activity were first retrieved from the VoteWatch website. However, these data were incomplete, so we later switched to another source: the It’s Your Parliament website. There were also some minor issues with these data, which we had to correct: some MEPs were represented twice, some profiles were incomplete, the policy domains were not defined for all vote texts, etc. These cleaned data are available on Zenodo here and there. URL: https://github.com/CompNet/NetVotes Production date: 2014–2018 Related publications: Nejat Arınık, Rosa Figueiredo et Vincent Labatut. « Signed Graph Analysis for theInterpretation of Voting Behavior ». In : International Conference on Knowledge Technologiesand Data-driven Business (i-KNOW) – International Workshop on Social NetworkAnalysis and Digital Humanities (SnanDig). T. 2025. CEUR Workshop Proceedings.Graz, Plus d'infos

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