Maria Fasli

Automatic web service composition based on graph network analysis metrics

The web services paradigm has enabled an increasing number of providers to deploy and host autonomic and remotely accessible services. However, the true potential of such a distributed infrastructure can only be reached when such autonomic services can be combined together as parts of a workflow, in order to collectively achieve combined functionality. In this paper we present our work in the area of automatic workflow composition among web services with semantically described functionality capabilities. For that purpose, we are using a set of heuristics derived from the connectivity structure of the service repository in order to effectively guide the composition process. The methodologies described in this paper have been inspired by research in areas such as citation analysis and bibliometrics. In addition, we present comparative experimentation results in order to evaluate the presented techniques.

Automatically structuring domain knowledge from text: An overview of current research

This paper presents an overview of automatic methods for building domain knowledge structures (domain models) from text collections. Applications of domain models have a long history within knowledge engineering and artificial intelligence. In the last couple of decades they have surfaced noticeably as a useful tool within natural language processing, information retrieval and semantic web technology. Inspired by the ubiquitous propagation of domain model structures that are emerging in several research disciplines, we give an overview of the current research landscape and some techniques and approaches. We will also discuss trade-offs between different approaches and point to some recent trends.

On Commitments, Roles, and Obligations

This paper presents a formalisation of obligations, social commitments and roles for BDI agents. We present a formal analysis of general obligations and relativised-to-one obligations from a bearer to a single counterparty and we examine obligations and relativised-to-one obligations in the context of strong realism for BDI agents. We also discuss how relativised-to-one obligations arise as a result of social commitments and the adoption of roles. In our framework, if an agent adopts a role, then this role is associated with one or more social commitments. Social commitments give rise to relativised obligations and consequently, roles, social commitments and relativised obligations are interwoven.

Utilizing contextual ontological user profiles for personalized recommendations

As users may have different needs in different situations and contexts, it is increasingly important to consider user context data when filtering information. In the field of web personalization and recommender systems, most of the studies have focused on the process of modelling user profiles and the personalization process in order to provide personalized services to the user, but not on contextualized services. Rather limited attention has been paid to investigate how to discover, model, exploit and integrate context information in personalization systems in a generic way. In this paper, we aim at providing a novel model to build, exploit and integrate context information with a web personalization system. A context-aware personalization system (CAPS) is developed which is able to model and build contextual and personalized ontological user profiles based on the user’s interests and context information. These profiles are then exploited in order to infer and provide contextual recommendations to users. The methods and system developed are evaluated through a user study which shows that considering context information in web personalization systems can provide more effective personalization services and offer better recommendations to users.

Shopbots: A Syntactic Present, A Semantic Future

Despite high expectations, shopbots have yet to significantly facilitate a richer, more satisfying online shopping experience for users. By taking advantage of semantic Web and Web services technologies, however, researchers can overcome current technological limitations and finally realize the shopbots significant potential

e-Game: A platform for developing auction-based market simulations

Trading in electronic markets has been the focus of intense research over the last few years within Computer Science and Economics. This paper discusses the need for tools to support the design and implementation of electronic market simulations or games. Such games emulate real life problems and can be used in order to conduct research on market infrastructure, negotiation protocols and strategic behaviour. To this end, we present the e-Game platform which was developed to support the design, implementation and execution of market simulations involving auctions. How the development of market games is aided is demonstrated with an example game.

Employing Graph Network Analysis for Web Service Composition

The Web services paradigm has enabled an increasing number of providers to host remotely accessible services. However, the true potential of such a distributed infrastructure can only be reached when such autonomic services can be combined together as parts of a workflow, in order to collectively achieve combined functionality. In this article, we present our work in the area of automatic workflow composition among Web services with semantically described functionality capabilities. For this purpose, we use a set of heuristics derived from the connectivity structure of the service repository in order to effectively guide the composition process. The methodologies presented in this article have been inspired by research in areas such as graph network analysis, social network analysis, and bibliometrics. In addition, we present comparative experimentation results in order to evaluate the presented techniques.

Social interactions in multi-agent systems: a formal approach

The paper presents a formal analysis of social interactions within multi-agent systems. The fundamental building blocks of such systems are social agents which can be individuals or aggregations of agents whose structure can be formally characterised in terms of roles and relationships between them. Agents are free to join social agents while in pursuit of their own objectives, but at the same time they have to balance their preferences and their commitments. Stability and regulation of behaviour within a multi-agent system and within social agents is accounted for by means of commitments, obligations and rights.

Exploring ant colony optimisation for adaptive interactive search

Search engines have become much more interactive in recent years which has triggered a lot of work in automatically acquiring knowledge structures that can assist a user in navigating through a document collection. Query log analysis has emerged as one of the most promising research areas to automatically derive such structures. We explore a biologically inspired model based on ant colony optimisation applied to query logs as an adaptive learning process that addresses the problem of deriving query suggestions. A user interaction with the search engine is treated as an individual ants journey and over time the collective journeys of all ants result in strengthening more popular paths which leads to a corresponding term association graph that is used to provide query modification suggestions. This association graph is being updated in a continuous learning cycle. In this paper we use a novel automatic evaluation framework based on actual query logs to explore the effect of different parameters in the ant colony optimisation algorithm on the performance of the resulting adaptive query suggestion model. We also use the framework to compare the ant colony approach against a state-of-the-art baseline. The experiments were conducted with query logs collected on a university search engine over a period of several years.

From blurry numbers to clear preferences: A mechanism to extract reputation in social networks

Complex social networks are typically used in order to represent and structure social relationships that do not follow a predictable pattern of behaviour. Due to their openness and dynamics, these networks make participants continuously deal with uncertainty before any type of interaction. Reputation appears as a key concept helping users to mitigate such uncertainty. Most of the reputation mechanisms proposed in the literature are based on numerical opinions (ratings), and consequently, they are exposed to potential problems such as the subjectivity in the opinions and their consequent inaccurate aggregation. With these problems in mind, this paper presents a reputation mechanism based on the concepts of pairwise elicitation processes and knock-out tournaments. The main objective of this mechanism is to build reputation rankings from qualitative opinions, thereby removing the subjectivity problems associated with the aggregation of quantitative opinions. The proposed approach is evaluated with different data sets from the MovieLens and Flixster web sites.