<div dir="auto"><div><div class="gmail_quote"><div dir="ltr">Sorry for cross-posting.</div><div dir="ltr"><br></div><div dir="ltr">Online at:</div><div dir="ltr"><a href="https://exampledotorg.blogspot.com/2018/10/request-for-comments-ii.html">https://exampledotorg.blogspot.com/2018/10/request-for-comments-ii.html</a><br></div><div dir="auto"><div style="margin:16px 0px" dir="auto"><div><div dir="auto"><div dir="auto">Draft: could a framework of patterns leverage SW / ML adoption for end to end business applications / BI / user centered use cases?</div><div dir="auto"><br></div><div dir="auto">Semantic Web / RDF as the 'glue' of / for ML dataflow encoded input 'features' / output 'tensors' and ontology aligments. Mappings for knowledge input / augmented (learning) output rows (RDBMS example) processed by ML models in semantic alignments.</div><div dir="auto"><br></div><div dir="auto">SW contexts encodes 'meaning' into translated input features / obtained learning output tensors via RDF CSPO quads Resource ID creation / assignment algorithm. Tensor shapes rendered as algorithmically Resource ID enabled (ANNs activation functions) operating over and preserving Resource IDs / Statements integrity (validation).</div><div dir="auto"><br></div><div dir="auto">Dataflow semantic 'forms' application language: encode code and data functionally as Context RDF quad statements. Context activations performs functional intra / inter Context transforms across layers statements. Encoded 'form' statement resolves to getters / setters applications by means of algorithm to obtain resulting inferred 'forms' (templates: system resource encoded quads).</div><div dir="auto"><br></div><div dir="auto">Tools:</div><div dir="auto"><br></div><b>TensorFlow / ML:</b><div dir="auto"><br><div dir="auto">I/O: Tensors (features / classes, discrete values in 'shapes').</div><div dir="auto"><br></div><div dir="auto">Learning:<br><div dir="auto">Classification: class / instance identification. "Messi: Player : 10"</div><div dir="auto"><br></div><div dir="auto">Learning:</div><div dir="auto">Clustering: similarity (common attributes / links resolution). "Messi player of Barcelona".</div><div dir="auto"><br></div><div dir="auto">Learning:</div><div dir="auto">Regression (discrete value in function of input features, roles in contexts: value / event for x when y was z in w). "Messi captain of Barcelona in last tournament".</div><div dir="auto"><br></div><div dir="auto">Semantic Microservices (proposed component):</div><div dir="auto"><br></div><div dir="auto">I/O: RDF encoded features / outputs CSPO quad statements (reactive stream events bus). Resource ID creation / assignation algorithm (Semantic IDs: operable, tensor embeddings).</div><div dir="auto"><br></div><div dir="auto">Augmentation:</div><div dir="auto">Aggregations: data, schema, behavior statement layers dimensional aggregation. Type inference by attributes / values aggregation.</div><div dir="auto"><br></div><div dir="auto">Alignments:</div><div dir="auto">ID resolution: class / instance identity discovery (ontology / schema matching) ML models.</div><div dir="auto">Attributes / links resolution: clustering ML models</div><div dir="auto">Roles in contexts resolution: regression ML models</div><div dir="auto"><br></div><div dir="auto"><b>Distribution / Dataflow:</b></div><div dir="auto"><br></div><div dir="auto"><div dir="auto">Integration / Discovery / Activations.</div></div><div dir="auto">Contexts / Layers: Dimensional upper ontology layers alignments between Contexts (data, domain, application levels).</div><div dir="auto"><br></div><div dir="auto">Reactive Extensions (RX). Dataflow 'forms' enabled 'templates' inter context levels.</div><div dir="auto"><br></div><div dir="auto">Activation: Resources Context's streams as observers / observables (RX) of Context / upper layers events. Event ('form') fires node augmentation (learning) / resolves to nodes emmiting knowledge 'forms' events related to their knowledge of the source event.</div><div dir="auto"><br></div><div dir="auto"><b>Use Cases:</b></div><div dir="auto"><br></div><div dir="auto">Semantic Microservices Adapters (endpoints, integration / transforms).</div><div dir="auto"><br></div><div dir="auto">GraphQL: adapters schema / tenmplate transforms. Forms functional language translation (I/O: integration).</div><div dir="auto"><br></div><div dir="auto">Adapters: Workflows / API Rendering (OData, REST: Spring HATEOAS / HAL).</div><div dir="auto"><br></div><div dir="auto">Refine / ETL (Adapters I/O).<br></div><div dir="auto"><br></div><div dir="auto">Big Data Deployments (Adapters I/O).</div><div dir="auto"><br></div><div dir="auto">BI / Dashboards (Adapters I/O).</div><div dir="auto"><br></div><div dir="auto">Declarative Business Applications Framework (Adapters I/O).<br></div><div dir="auto"><br></div><div dir="auto"><b>Links:</b></div><div dir="auto"><br></div><div dir="auto">OData: <a href="https://www.odata.org/" target="_blank" rel="noreferrer">https://www.odata.org</a></div><div dir="auto">Spring HATEOAS: <a href="https://spring.io/projects/spring-hateoas" target="_blank" rel="noreferrer">https://spring.io/projects/spring-hateoas</a></div><div dir="auto">HAL: <a href="http://stateless.co/hal_specification.html" target="_blank" rel="noreferrer">http://stateless.co/hal_specification.html</a></div><div dir="auto"><a href="http://openrefine.org/" target="_blank" rel="noreferrer">http://openrefine.org/</a></div><div dir="auto"><a href="http://www.opencalais.com/" target="_blank" rel="noreferrer">http://www.opencalais.com</a><br></div><div dir="auto"><a href="https://solid.mit.edu/" target="_blank" rel="noreferrer">https://solid.mit.edu</a><br></div><div dir="auto"><br></div></div></div></div></div></div>Sebastian Samaruga.<div dir="auto"><a href="http://exampledotorg.blogspot.com" target="_blank" rel="noreferrer">http://exampledotorg.blogspot.com</a></div></div>
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