A Service Creation Environment Based on End to End by Agarwal V., Dasgupta K., Karnik N.

By Agarwal V., Dasgupta K., Karnik N.

The call for for quick offering new purposes is more and more changing into a enterprise crucial this day. software improvement is frequently performed in an advert hoc demeanour, with no commonplace frameworks or libraries, hence leading to bad reuse of software program resources. net companies have got a lot curiosity in as a result of their strength in facilitating seamless business-to-business or firm program integration. an online companies composition instrument may help automate the method, from growing company method performance, to constructing executable paintings ows, to deploying them on an execution atmosphere. notwithstanding, we and that the most methods taken so far to standardize and compose internet prone are piecemeal and insucient. The company global has followed a (distributed) programming technique during which net provider circumstances are defined utilizing WSDL, composed into ows with a language likeBPEL and invoked with the cleaning soap protocol. Academia has propounded the AI process of officially representing net provider functions in ontologies, and reasoning approximately their composition utilizing goal-oriented inferencing recommendations from making plans. We current the ♀rst built-in paintings in composing net providers finish to finish from specifcation to deployment by way of synergistically combining the strengths of the above ways. We describe a prototype provider construction atmosphere besides a use-case situation, and show the way it can signi♀cantly accelerate the time-to-market for brand spanking new companies.

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With the increasing research interest on ontology and semantic web, ontologybased semantic search over relational databases has become a ‘hot’ research topic in database community [17, 18]. So, exploiting ontology to improve the effectiveness of KSORD receives increasing attention. 3 Efficiency Improvements on KSORD In recent years, we have developed many techniques to optimize the efficiency of online KSORD systems. Aiming at improving SO-KSORD systems, we proposed a new preprocessing approach PreCN [21] to improve the generation efficiency of CN, and CLASCN [24] and QuickCN [26] methods to improve the execution efficiency of CN.

This is shown in Figure 4. Essentially, the system extracts the context of the document (again, a set of keywords for the purpose of this example) and uses this context as an anchor into the DB2 database. The relational data can be presented in to the user in a browse-able manner. 34 P. Roy and M. Mohania Clearly, such functionality cannot be achieved by querying DB2 and CM independently. In the first case CM uses the context retrieved from DB2 to identify relevant documents, while in the second case DB2 uses the context retrieved from CM to identify the relevant database fragment.

As for boolean-OR semantic keyword queries in IR-Style [8] and SEEKER [5], we find out that Gts patterns can be viewed as user keyword query patterns for a given Gs . All CNs under the limitation of MaxCNsize and Maximum allowed Keyword Number(MaxKeywNum) can be generated in advance through a breadth-first traversal of the maximum Gts , and then stored in the database. When a user query arrives, its proper CNs are directly retrieved from the database. This method is called PreCN [21]. PeCN is simpler and more efficient than that in [22].

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