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As more and more companies and organizations encapsulate and publish their business data or resources to the Internet in the form of APIs, the number of web APIs has grown exponentially. For this reason, it has become challenging to quickly and effectively find web APIs from such a large‐scale web API collection, which meet the requirements of mashup developers. To this end, this article focuses on...
Metal additive manufacturing (AM) processes are very complex and the process parameters required to fabricate quality parts can be very complicated and challenging to determine. For this reason, there is a continuous demand for AM simulations which can assist users to determine optimal process parameters in a timely manner. However, current commercial simulation packages are expensive and not designed...
Data sparsity and cold-start remains to be the main limitations and weaknesses in recommendation systems that employ collaborative filtering (CF). These limitations cause lack of convergence in CF recommendation algorithms which ultimately affect the overall accuracy of the recommendation system. Efforts to alleviate these limitations typically require additional user or item information such as social...
The growing number of Additive Manufacturing Web (AMW) services, offered by different providers over the Internet, makes it challenging for consumers to compare these AMW services to select a service of their choice. In addition, it is even more challenging for consumers to compare these AMW services against their personal preferences. This is because, consumers personal preferences on multiple non-functional...
Existing service recommendation methods, that employ memory-based collaborative filtering (CF) techniques, compute the similarity between users or items using nonfunctional attribute values obtained at service invocation. However, using these nonfunctional attribute values from invoked services alone in similarity computation for personalized service recommendation is not sufficient. This is because...
In this paper we propose a method for aggregating ranked services. The ranked services are generated from multiple user requests for the same service domain. First, a service search for each individual request is performed and the search results are ranked based on the user's personalized non-functional attributes and trade-offs. Next, the ranked lists of services are then aggregated and top-ranked...
Web service selection based on quality of service (QoS) has been a research focus in an environment where many similar web services exist. Current methods of service selection usually focus on a single service request at a time and the selection of a service with the best QoS at the user's own discretion. The selection does not consider multiple requests for the same functional web services. Usually,...
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