science

Semantic matching

Semantic matching is a 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 Semantic matching rather than just read about it. In short: Semantic matching is a technique used in computer science to identify information that is semantically related. Given any two graph-like structures, e.g. classifications, taxonomies database or XML schemas and ontologies, matching is an operator which identifies those nodes in the two structures which semantically correspond to one another.

Key takeaways

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

Reference excerpt

Semantic matching is a technique used in computer science to identify information that is semantically related. Given any two graph-like structures, e.g. classifications, taxonomies database or XML schemas and ontologies, matching is an operator which identifies those nodes in the two structures which semantically correspond to one another. For example, applied to file systems, it can determine that a folder labeled "car" is semantically equivalent to another folder "automobile" because they are synonyms in English. This information can be taken from a linguistic resource like WordNet. In recent years many of them have been offered. S-Match is an example of a semantic matching operator. It works on lightweight ontologies, namely graph structures where each node is labeled by a natural language sentence, for example in English. These sentences are translated into a formal logical formula (according to an artificial unambiguous language) codifying the meaning of the node taking into account its position in the graph. For example, in case the folder "car" is under another folder "red" we can say that the meaning of the folder "car" is "red car" in this case. This is translated into the logical formula "red AND car". The output of S-Match is a set of semantic correspondences called mappings attached with one of the following semantic relations: disjointness (⊥), equivalence (≡), more specific (⊑) and less specific (⊒). In our example, the algorithm will return a mapping between "car" and "automobile" attached with an equivalence relation. Information semantically matched can also be used as a measure of relevance through a mapping of near-term relationships. Such use of S-Match technology is prevalent in the career space where it is used to gauge depth of skills through relational mapping of information found in applicant resumes. Semantic matching represents a fundamental technique in many applications in areas such as resource discovery, data integration, data migration, query translation, peer-to-peer networks, agent communication, schema, and ontology merging. Its use is also being investigated in other areas such as event processing. In fact, it has been proposed as a valid solution to the semantic heterogeneity problem, namely managing the diversity in knowledge. Interoperability among people of different cultures and languages, having different viewpoints, and using different terminology has always been a huge problem. Especially with the advent of the Web and the consequential information explosion, the problem seems to be emphasized. People face the concrete problem of retrieving, disambiguation, and integrating information coming from a wide variety of sources.

See also Ontology alignment Semantic integration Semantic unification Semantic technology Minimal mappings

References

External links "Semantic Matching". Semanticmatching.eu. Retrieved 21 December 2018. "S-Match is a semantic matching framework". Sourceforge.net. Retrieved 21 December 2018.

Worked examples

Example 1 — a first encounter with Semantic matching

Start with the simplest possible case. Write down what Semantic matching claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In 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 Semantic matching 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 Semantic matching 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 Semantic matching

In research: Semantic matching appears in 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 Semantic matching 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: Semantic matching is common in secondary-school and first-year university syllabi. It links to neighbouring topics Ontology (information science), Semantic Web, so understanding it makes those chapters shorter.
In everyday life: Look for Semantic matching 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.

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How to study Semantic matching in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Semantic matching 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 Semantic matching out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Semantic matching in simple terms?

Why does Semantic matching matter?

Because it connects several 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 Semantic matching?

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 Semantic matching.