Sylvie Cazalens

A Web site indexing process for an Internet information retrieval agent system

Bonom is a distributed agent based system to perform information retrieval on the Internet. The middle agents which perform the matching between site agents (information providers) and user agents (requesters) are numerous and can be world wide distributed. Moreover, the agents are structured into nested communities according to a hierarchy of information domains. This paper focuses on a Web site indexing process which uses disambiguated ontologies. It allows the site agent to know to which communities it has to subscribe to, in order to get requests it can accurately process.

A Flexible Mediation Process for Large Distributed Information Systems

We consider distributed information systems that are open, dynamic and provide access to large numbers of distributed, heterogeneous, autonomous information sources. Most of the work in data mediator systems has dealt with the problem of finding relevant information providers for a request. However, finding relevant requests for information providers is another important side of the mediation problem which has not received much attention. In this paper, we address these two sides of the problem with a flexible mediation process. Once the qualified information providers are identified, our process allows them to express their request interests via a bidding mechanism. It also requires to set up a requisition policy, because a request must always be answered if there are qualified providers. This work does not concern pure market mechanisms because we counter-balance the providers’ bids by considering their quality wrt a request. We validated our process on a set of simulations. The results show that the mediation process supports the providers in adequacy with the user expectations, even if they are sometimes imposed.

Gossiping correspondences to reduce semantic heterogeneity of unstructured P2P systems

In this paper we consider P2P data sharing systems in which each participant uses an ontology to represent its data. If all the participants do not use the same ontology, the system is said to be semantically heterogeneous. This situation of heterogeneity prevents perfect interoperability. Indeed participants could be unable to treat queries for which they do not understand some concepts. Intuitively, the more heterogeneous a system, the harder to communicate. We first define several measures to characterize the semantic heterogeneity of P2P systems according to different facets. Then, we propose a solution, called CorDis, to reduce the heterogeneity by decreasing the gap between peers. The idea is to gossip correspondences through the system so that peers become less disparate from each other. The experiments use the PeerSim simulator and ontologies from OntoFarm. The results show that CorDis significantly reduces some facets of semantic heterogeneity while the network traffic and the storage space are bounded.

Semantic Heterogeneity Measures of Unstructured P2P Systems

We consider P2P data sharing systems in which each participant uses an ontology to represent information. If all the partipants do not use the same ontology, the system is said to be semantically heterogeneous. Several methods have been proposed to reach a degree of interoperability but thorough evaluation of these methods is prevented by a lack of tools to describe the situations in which they have been tested. In this paper we identify components that impact on the semantic heterogeneneity, and we define several complementary measures to capture the different facets of heterogeneity. Proposed measures allow to characterize the situation in which a method is evaluated, or to measure the heterogeneity reduction produced by another method.

Scaling up query allocation in the presence of autonomous participants

In large-scale, heterogeneous information systems, mediators are widely used for query processing and the good operation of a system strongly depends on the way the mediator allocates queries. On the other hand, it is well known that a single mediator is a potential scalability and performance bottleneck as well as a single point of failure. Thus, multiple mediators should perform the query allocation process. This task is challenging in large-scale systems because participants typically have special interests that are not performance-related. Mediators should satisfy participants interests as if there was a single mediator in the system -- i.e., with no, or almost no, additional network traffic. In this paper, we propose a virtual money-based query allocation method, called VMbQA, to perform query allocation in the presence of multiple mediators and autonomous participants. A key feature of VMbQA is that it allows a system to scale up to several mediators with no additional network cost. The results show that VMbQA significantly outperforms baseline methods from both satisfaction and performance points of view

Reducing the Semantic Heterogeneity of Unstructured P2P Systems: A Contribution Based on a Dissemination Protocol

In resource sharing P2P systems with autonomous participants, each peer is free to use the ontology with which it annotates its resources. Semantic heterogeneity occurs when the peers do not use the same ontology. For example, a contributing peer A (e.g. a doctor) may annotate its photos, diagrams, data sets with some ontology of its own, while peer B (e.g. a genetician) uses another one. In order to answer a query issued in the system, peers need to know alignments that state correspondences between entities of two ontologies. Assuming that each peer has some partial initial knowledge of some alignments, we focus on correspondences sharing between the peers as a means to learn additional correspondences. We first provide several measures of semantic heterogeneity that enable to draw a semantic picture of the system and to evaluate the efficiency of protocols independently of query evaluation. We propose CorDis, a gossip-based protocol that disseminates the correspondences that the peers want to share in the system. To overcome the peers’ storage limitations, we propose to consider a history of past queries and to favor the correspondences involving frequently used entities. We study several policies that a peer may adopt in case of inconsistency i.e. when shared correspondences conflict with its own knowledge. We conduct experiments with a set of 93 ontologies actively used in the biomedical domain. We evaluate the CorDis protocol with respect to the proposed measures of semantic heterogeneity and show its good behavior for decreasing them in several contexts.

Flash Points: Discovering Exceptional Pairwise Behaviors in Vote or Rating Data

We address the problem of discovering contexts that lead well-distinguished collections of individuals to change their pairwise agreement w.r.t. their usual one. For instance, in the European parliament, while in overall, a strong disagreement is witnessed between deputies of the far-right French party Front National and deputies of the left party Front de Gauche, a strong agreement is observed between these deputies in votes related to the thematic: External relations with the union. We devise the method DSC (Discovering Similarities Changes) which relies on exceptional model mining to uncover three-set patterns that identify contexts and two collections of individuals where an unexpected strengthening or weakening of pairwise agreement is observed. To efficiently explore the search space, we define some closure operators and pruning techniques using upper bounds on the quality measure. In addition of handling usual attributes (e.g. numerical, nominal), we propose a novel pattern domain which involves hierarchical multi-tag attributes that are present in many datasets. A thorough empirical study on two real-world datasets (i.e., European parliament votes and collaborative movie reviews) demonstrates the efficiency and the effectiveness of our approach as well as the interest and the actionability of the patterns.

Computational Fact Checking: A Content Management Perspective

Data journalism designates journalistic work inspired by digital data sources. A particularly popular and active area of data journalism is concerned with fact-checking. The term was born in the journalist community and referred the process of verifying and ensuring the accuracy of published media content; since 2012, however, it has increasingly focused on the analysis of politics, economy, science, and news content shared in any form, but first and foremost on the Web (social and otherwise). These trends have been noticed by computer scientists working in the industry and academia. Thus, a very lively area of digital content management research has taken up these problems and works to propose foundations (models), algorithms, and implement them through concrete tools. Our tutorial: (i) Outlines the current state of affairs in the area of digital (or computational) fact-checking in newsrooms, by journalists, NGO workers, scientists and IT companies; (ii) Shows which areas of digital content management research, in particular those relying on the Web, can be leveraged to help fact-checking, and gives a comprehensive survey of efforts in this area; (iii) Highlights ongoing trends, unsolved problems, and areas where we envision future scientific and practical advances.

QTor: A Flexible Publish/Subscribe Peer-to-Peer Organization Based on Query Rewriting

Peer-to-peer publish/subscribe architectures are an interesting support for scalable distributed data stream applications. Most approaches, often based on brokers, have a static organization which is not much adaptive to different configurations of the participants’ capacities. We present QTor (Query Torrent) a generic organization that enables dynamic adaptation providing a continuum from centralized to fully decentralized solutions. Based on query rewriting and equivalence, QTor proposes a definition of communities and their relations that decouples the logical and physical aspects of the problem, while efficiently reducing organizational and functional costs.