Machine Learning of Probabilistic Phonological Pronunciation Rules from the Italian CLIPS Corpus

A blending of phonological concepts and technical analysis is proposed to yield a better modeling and understanding of phonological processes. Based on the manual segmentation and labeling of the Italian CLIPS corpus we automatically derive a probabilistic set of phonological pronunciation rules: a new alignment technique is used to map the phonological form of spontaneous sentences onto the phonetic surface form. A machine-learning algorithm then calculates a set of phonologi- cal replacement rules together with their conditional probabilities. A critical analysis of the resulting probabilistic rule set is presented and discussed with regard to regional Italian accents. The rule set presented here is also applied in the newly published web-service WebMAUS that allows a user to segment and phonetically label Italian speech via a simple web-interface

P-CSREC: A New Approach for Personalized Cloud Service Recommendation

It is becoming a challenging issue for users to choose a satisfied service to fit their need due to the rapid growing number of cloud services and the vast amount of service type varieties. This paper proposes an effective cloud service recommendation approach, named personalized cloud service recommendation (P-CSREC), based on the characterization of heterogeneous information network, the use of association rule mining, and the modeling and clustering of user interests. First, a similarity measure is defined to improve the average similarity (AvgSim) measure by the inclusion of the subjective evaluation of users’ interests. Based on the improved AvgSim, a new model for measuring the user interest is established. Second, the traditional K-Harmonic Means (KHM) clustering algorithm is improved by means of involving multi meta-paths to avoid the convergence of local optimum. Then, a frequent pattern growth (FP-Growth) association rules algorithm is proposed to address the issue and the limitation of traditional association rule algorithms to offer personalization in recommendation. A new method to define a support value of nodes is developed using the weight of user’s score. In addition, a multi-level FP-Tree is defined based on the multi-level association rules theory to extract the relationship in higher level. Finally, a combined user interest with the improved KHM clustering algorithm and the improved FP-Growth algorithm is provided to improve accuracy of cloud services recommendation to target users. The experimental results demonstrated the effectiveness of the proposed approach in improving the computational efficiency and recommendation accuracy

Towards a flexible service integration through separation of business rules

Driven by dynamic market demands, enterprises are continuously exploring collaborations with others to add value to their services and seize new market opportunities. Achieving enterprise collaboration is facilitated by Enterprise Application Integration and Business-to-Business approaches that employ architectural paradigms like Service Oriented Architecture and incorporate technological advancements in networking and computing. However, flexibility remains a major challenge related to enterprise collaboration. How can changes in demands and opportunities be reflected in collaboration solutions with minimum time and effort and with maximum reuse of existing applications? This paper proposes an approach towards a more flexible integration of enterprise applications in the context of service mediation. We achieve this by combining goal-based, model-driven and serviceoriented approaches. In particular, we pay special attention to the separation of business rules from the business process of the integration solution. Specifying the requirements as goal models, we separate those parts which are more likely to evolve over time in terms of business rules. These business rules are then made executable by exposing them as Web services and incorporating them into the design of the business process.\ud Thus, should the business rules change, the business process remains unaffected. Finally, this paper also provides an evaluation of the flexibility of our solution in relation to the current work in business process flexibility research

Exploiting rules and processes for increasing flexibility in service composition

Recent trends in the use of service oriented architecture for designing, developing, managing, and using distributed applications have resulted in an increasing number of independently developed and physically distributed services. These services can be discovered, selected and composed to develop new applications and to meet emerging user requirements. Service composition is generally defined on the basis of business processes in which the underlying composition logic is guided by specifying control and data flows through Web service interfaces. User demands as well as the services themselves may change over time, which leads to replacing or adjusting the composition logic of previously defined processes. Coping with change is still one of the fundamental problems in current process based composition approaches. In this paper, we exploit declarative and imperative design styles to achieve better flexibility in service composition

Combining goal-oriented and model-driven approaches to solve the Payment Problem Scenario

Motivated by the objective to provide an improved participation of business domain experts in the design of service-oriented integration solutions, we extend our previous work on using the COSMO methodology for service mediation by introducing a goal-oriented approach to requirements engineering. With this approach, business requirements including the motivations behind the mediation solution are better understood, specified, and aligned with their technical implementations. We use the Payment Problem Scenario of the SWS Challenge to illustrate the extension

Controlling services in a mobile context-aware infrastructure

Context-aware application behaviors can be described as logic rules following the Event-Control-Action (ECA) pattern. In this pattern, an Event models an occurrence of interest (e.g., a change in context); Control specifies a condition that must hold prior to the execution of the action; and an Action represents the invocation of arbitrary services. We have defined a Controlling service aiming at facilitating the dynamic configuration of ECA rule specifications by means of a mobile rule engine and a mechanism that distributes context reasoning activities to a network of context processing nodes. In this paper we present a novel context modeling approach that provides application developers and users with more appropriate means to define context information and ECA rules. Our approach makes use of ontologies to model context information and has been developed on top of web services technology