Automatic composition of information-providing web services based on query rewriting

ArticleinSciece China. Information Sciences 55(11):1-17 · January 2010with13 Reads
DOI: 10.1007/s11432-011-4341-5
Abstract
Compared with normal web services, information-providing services have unique features that have seldom been considered in existing research on the automatic composition of web services. In this paper, we present a simple, yet well-formed, semantic-based capability model for information-providing web services, which can express such features as not modifying the world state and not requiring all input/output parameters to be supplemented with class information as semantics. We then present a corresponding automatic composition method derived from a query rewriting algorithm, MiniCon, used in the data integration field. This method adequately utilizes previous features, enables primitive semantic reasoning, and can generate executable BPEL scripts automatically. Performance of the method is complementary to traditional search-based ones. Experiments on a typical type of problem show that the method is usable in practice. Keywordsweb services–automatic composition–query rewriting–data integration–ontology–semantic web
    • "We review the most important ones that considered the class of data web services. The authors in [28] use the service profile IOPE of the OWL-S ontology to model the capacities of data services. Moreover, they extended the MiniCon query rewriting algorithm [19] to automatically compose data services based on their profiles. "
    [Show abstract] [Hide abstract] ABSTRACT: Currently, a good portion of datasets on Internet are accessed through data services, where user's queries are answered as a composition of multiple data services. Defining the semantics of data services is the first step towards automating their composition. An interesting approach to define the semantics of data services is by describing them as semantic views over a domain ontology. However, defining such semantic views cannot always be done with certainty, especially when the service's returned data are too complex. In such case, a data service is associated with several possible semantic views. In addition, complex correlations maybe present among these possible semantic views, mainly when data services encapsulate the same data sources. In this paper, we propose a probabilistic approach to model the semantic uncertainty of data services. Services along with their possible semantic views are represented in probabilistic service registry. The correlations among service semantics are modeled through a directed probabilistic graphical model (Bayesian network). Based on our modeling, we study the problem of com- positing correlated data services to answer a user query, and propose an efficient method to compute the different possible compositions and their probabilities.
    Full-text · Article · Mar 2015
    • "We review the most important ones that considered the class of data web services. The authors in [28] use the service profile IOPE of the OWL-S ontology to model the capacities of data services. Moreover, they extended the MiniCon query rewriting algorithm [19] to automatically compose data services based on their profiles. "
    [Show abstract] [Hide abstract] ABSTRACT: With the emergence of the open data movement, hundreds of thousands of datasets from various concerns are now freely available on Internet. The access to a good number of these datasets is carried out through Web services which provide a standard way to interact with data. In this context, user’s queries often require the composition of multiple dataWeb services to be answered. Defining the semantics of data services is the first step towards automating their composition. An interesting approach to define the semantics of data services is by describing them as semantic views over a domain ontology. However, defining such semantic views cannot always be done with certainty, especially when the service’s outputs are too complex. In this paper, we propose a probabilistic approach to model the semantics uncertainty of data services. In our approach, a data service with an uncertain semantics is described by several possible semantic views, each one is associated with a probability. Services along with their possible semantic views are represented in a Block-Independent-Disjoint (noted BID) probabilistic service registry, and interpreted based on the Possible Worlds Semantics. Based on our modeling, we study the problem of interpreting an existing composition involving services with uncertain semantics. We also study the problem of compositing uncertain data services to answer a user query, and propose an efficient method to compute the different possible compositions and their probabilities.
    Full-text · Article · Sep 2014
    • "As commonly agreed, Web services fall into two categories depending on their functionality world-altering services and information-providing ones [1]. The latter ones are regarded as specific database views with binding patterns. "
    [Show abstract] [Hide abstract] ABSTRACT: In the domain of DaaS {DaaS: Data-as-a-Service or information-providing service), completing a query means calling many services which are heterogeneous and built independently from the context in which they will be used. This heterogeneity leads to several compatibility problems during DaaS composition. In order to solve them, we propose a semantic description model which allows context characterization. The proposed model enables data mediation in the composition for resolving the conflicts caused by heterogeneities between DaaSs. We rely on two-layered mediated ontology for deriving automatically DaaSs compositions that incorporate necessary mediation services. A preliminary evaluation has been performed based on our initial investigation leading to better improvement.
    Full-text · Article · Nov 2011 · IEEE Transactions on Knowledge and Data Engineering
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