computer science

Self-Service Semantic Suite

Self-Service Semantic Suite is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Self-Service Semantic Suite rather than just read about it. In short: The Self-Service Semantic Suite (S4) provides on-demand access to text mining and linked open data technology in the cloud. The S4 stack is based on enterprise-grade technology from Ontotext including their leading RDF engine (GraphDB, formerly OWLIM) and high performance text mining solutions successfully applied in some of the largest enterprises in the world.

Key takeaways

Self-Service Semantic Suite belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Self-Service Semantic Suite to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Self-Service Semantic Suite from memory before moving on to harder problems.

Reference excerpt

The Self-Service Semantic Suite (S4) provides on-demand access to text mining and linked open data technology in the cloud. The S4 stack is based on enterprise-grade technology from Ontotext including their leading RDF engine (GraphDB, formerly OWLIM) and high performance text mining solutions successfully applied in some of the largest enterprises in the world.

History It was launched in the summer of 2014.

Overview S4 offers a suite of text analytics and linked data management in the cloud. You can analyze news, social media, biomedical documents and query Linked Data knowledge graphs. You can also create your own RDF knowledge graphs using GraphDB™. S4 is low cost, on demand and pay-as-you-go providing affordable, easy access to companies of any size. The RDF triplestore included with S4 is GraphDB™ which is known for scalability and query performance. GraphDB™ is the only triplestore that performs inferencing at scale. Users realize improved query speed, data availability and accurate analysis. With GraphDB it is possible to store, manage and search semantic triples extracted from S4 text mining or to create private Knowledge Graphs integrating structured and unstructured data with facts from public LOD datasets.

Usability All functionality of the S4 can be accessed via RESTful services. Users are provided with Getting Started guide. Also there is a complete set of documentation and sample code in JAVA, C#, Python and JavaScript.

Feature Events Presentation 4-5 Dec 2014 - LT-Accelerate Conference - Brussels

References

Worked examples

Example 1 — a first encounter with Self-Service Semantic Suite

Start with the simplest possible case. Write down what Self-Service Semantic Suite claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Self-Service Semantic Suite before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Self-Service Semantic Suite ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Self-Service Semantic Suite

In research: Self-Service Semantic Suite appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Self-Service Semantic Suite in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Self-Service Semantic Suite is common in secondary-school and first-year university syllabi. It links to neighbouring topics 2014 software, Data mining and machine learning software, so understanding it makes those chapters shorter.
In everyday life: Look for Self-Service Semantic Suite outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “Self-Service Semantic Suite” →

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Self-Service Semantic Suite in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Self-Service Semantic Suite means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Self-Service Semantic Suite out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Self-Service Semantic Suite in simple terms?

Why does Self-Service Semantic Suite matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Self-Service Semantic Suite?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Self-Service Semantic Suite.