Philippe Lamarre

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.

Knowledge, Certainty, Belief, and Conditionalisation (abbreviated version)

We offer a system to capture the relationship between knowledge and belief, which also sheds new light on each of them in isolation. In the case of knowledge, we strongly reject the property of negative introspection. In the case of belief, we propose a distinction between belief (whose defeasibility is recognized by the agent) and certainty (whose defeasibility is not). The relationship between the three notions - knowledge, certainty, and belief - goes far beyond mere hierarchy. In particular, knowledge has the flavor of belief that is stable under incorporation of correct facts. We explore these first through a model theory, which is based on the notions of the agents subconscious biases and its conscious preferences (or plausibility measure). We then provide a sound and complete axiomatic system, and point to some of its illuminating properties. We compare our construction to previous ones in AI and philosophy, and in particular point to connections with recent work in AI based on conditionals. (Proofs of our theorems are omitted from this version of the article, hence the subtitle.)

A self-adaptable query allocation framework for distributed information systems

In large-scale distributed information systems, where participants are autonomous and have special interests for some queries, query allocation is a challenge. Much work in this context has focused on distributing queries among providers in a way that maximizes overall performance (typically throughput and response time). However, preserving the participants’ interests is also important. In this paper, we make the following contributions. First, we provide a model to define the participants’ perception of the system regarding their interests and propose measures to evaluate the quality of query allocation methods. Then, we propose a framework for query allocation called Satisfaction-based Query Load Balancing (SQLB, for short), which dynamically trades consumers’ interests for providers’ interests based on their satisfaction. Finally, we compare SQLB, through experimentation, with two important baseline query allocation methods, namely Capacity based and Mariposa-like. The results demonstrate that SQLB yields high efficiency while satisfying the participants’ interests and significantly outperforms the baseline methods.

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.

Trust Evaluation of a System for an Activity

When users need to perform a digital activity, they evaluate available systems according to their functionality, ease of use, QoS, and/or economical aspects. Recently, trust has become another key factor for such evaluation. Two main issues arise in the trust management research community. First, how to define the trust in an entity, knowing that this can be a person, a digital or a physical resource. Second, how to evaluate such value of trust in a system as a whole for a particular activity. Defining and evaluating trust in systems is an open problem because there is no consensus on the used approach. In this work we propose an approach applicable to any kind of system. The distinctive feature of our proposal is that, besides taking into account the trust in the different entities the user depends on to perform an activity, it takes into consideration the architecture of the system to determine its trust level. Our goal is to enable users to have a personal comparison between different systems for the same application needs and to choose the one satisfying their expectations. This paper introduces our approach, which is based on probability theory, and presents ongoing results.

SocioPath: Bridging the Gap between Digital and Social Worlds

Everyday, people use more and more digital resources (data, application systems, Internet, etc.) for all aspects of their life, like financial management, private exchanges, collaborative work, etc. This leads to non-negligible dependences on the digital distributed resources that reveal strong reliance at the social level. Users are often not aware of their real autonomy regarding the management of their digital resources. People underestimate social dependences generated by the system they use and the resulting potential risks. We argue that it is necessary to be aware of some key aspects of system’s architectures to be able to know dependences. This work proposes SocioPath, a generic meta-model to derive dependences generated by system’s architectures. It focuses on relations, like access, control, ownership among different entities of the system (digital resources, hardware, persons, etc.). Enriched with deduction rules and definitions, SocioPath reveals the dependence of a person on each entity in the system. This meta-model can be useful to evaluate a system, as a modeling tool that bridges the gap between the digital and the social worlds.

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.

Trust Evaluation of a System for an Activity with Subjective Logic

Recently, trust emerged as a momentous aspect to evaluate resources, services or persons. In our work, the trust notion focuses on a system as a whole and from the point of view of a particular user to do a particular digital activity as editing a document, mailing, chatting, etc. Our general goals are (i) to enable users to have a personal comparison of applications allowing them to do an activity such that they can choose the one satisfying their personal expectations and (ii) to know how trustworthy their system is to do a particular activity (all applications together). We consider a system as a graph composed of paths where the source is a person and the target is a final application or data. We consider that trust in a system depends on its architecture and we identify two problems (i) how to evaluate trust in a graph having dependent paths i.e., paths having common nodes, and (ii) how to express and deal with uncertainty in evaluating trust in a system. Concerning the first problem, trust approaches based on graphs have been proposed in the domain of social networks. Their solution for dependent paths is either removing paths or just choosing one of them what causes loss of information. Considering the second problem, subjective logic emerged to express trust as a subjective opinion with a degree of uncertainty. In this paper we present SubjectiveTrust, an approach that relies on subjective logic to evaluate trust in distributed systems. It proposes two solutions to treat dependent paths and takes into account the shape of the system architecture in trust evaluation. We analyze SubjectiveTrust in a series of experiments that show its accuracy.

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