Philippe Capet

A Risk Assessment System with Automatic Extraction of Event Types

In this article we describe the joint effort of experts in linguistics, information extraction and risk assessment to integrate EventSpotter, an automatic event extraction engine, into ADAC, an automated early warning system. By detecting as early as possible weak signals of emerging risks ADAC provides a dynamic synthetic picture of situations involving risk. The ADAC system calculates risk on the basis of fuzzy logic rules operated on a template graph whose leaves are event types. EventSpotter is based on a general purpose natural language dependency parser, XIP, enhanced with domain-specific lexical resources (Lexicon-Grammar). Its role is to automatically feed the leaves with input data.

Proposition of a semi-automatic possibilistic information scoring process

This paper proposes a semi-automatic three step information scoring process that starts from constructs representing structured pieces of information and a user query. It first identifies the constructs relevant to answer the user question, based on their similarity to the query. The relevant items are then individually scored, taking into account both the reliability of their source and the certainty the latter expresses through its choice of linguistic terms. Lastly, these individual scores are fused, modeling a corroboration process that takes into account information obsolescence and source relations. This procedure is performed in the framework of possibility theory, relying on the definition of the appropriate aggregation operators.

Two methods for Internet buzz detection exploiting the citation graph

This paper addresses the task of detecting Internet buzzes, defined as amplification phenomena, i.e. the diffusion on a very large scale of an Internet content, massively taken up within a short period of time. It proposes two approaches based on the citation graph that represents hyperlinks relation between websites. The first method detects temporal abnormalities in the number of citations of an information source, identifying information sources that undergo a surge of their direct citations. The second method exploits higher level cues, based on the definition of the dynamic cumulative visibility of an article. It captures the notion of citation cascade that is central to the specific type of buzzes related to rumour. Both detection approaches are illustrated, respectively on real data extracted from the Web and on realistic simulated data. The experimental study shows the relevance of the proposed methods and highlights their differences.