DI-322 Web Technologies Lecture 09: Search technologies, SEO, the Semantic Web and framework evaluation
DI-322 Web Technologies
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Lecture 09: Search technologies, SEO, the Semantic Web and framework evaluation

Outcomes and readiness

You can outline crawl-index-query-ranking, improve a page without manipulative SEO, express a small RDF graph and SPARQL query, and evaluate an unfamiliar framework with stable criteria. Readiness: explain semantic HTML and an XML/JSON data model.

Search pipeline

A crawler discovers permitted URLs, retrieves representations, extracts content and links, canonicalizes signals, and contributes documents to an index. A query system retrieves candidates and ranks them using many signals. Discovery, crawling, indexing, and ranking are different stages; a sitemap can aid discovery but does not guarantee indexing or rank.

Worked SEO review

For a DI-322 page:

  • Use a descriptive title and one clear h1.
  • Link it from the course catalog with meaningful anchor text.
  • Keep important content as accessible text in the DOM.
  • Supply accurate metadata and canonical/localized relationships when needed.
  • Make the page secure, fast, mobile-usable, and semantically structured.

Repeating keywords invisibly or creating misleading doorway pages harms users and is not a sound strategy. SEO improves understandable, accessible content; it does not guarantee first position.

Semantic Web model

RDF expresses triples: subject – predicate – object. Example: DI322 teachesTopic HTTP. A graph can combine independently identified concepts. SPARQL matches graph patterns.

SELECT ?topic WHERE {
  <https://example.edu/course/DI-322> <https://example.edu/vocab/teachesTopic> ?topic .
}

XML query languages operate on XML trees; SPARQL operates on RDF graphs. Do not merge those models merely because both use Web identifiers.

Faded framework evaluation

A new framework promises “zero configuration and infinite scale.” Hint 1: replace marketing claims with testable questions. Hint 2: consider runtime, accessibility, security, ecosystem, migration, and team skill. Solution: build a small representative slice, measure bundle/server cost, test rendering and forms, inspect maintenance and upgrade paths, and record trade-offs against requirements.

Common mistakes

  • robots.txt controls crawling behavior; it is not an access-control mechanism.
  • Structured data must match visible page content.
  • “Future framework” should be taught as evaluation capability, not a brand prediction that quickly expires.

Practical – DI322-LAB09

Audit one course page: title, headings, crawlable links, mobile layout, visible text, metadata, status, and performance risks. Create five RDF triples for courses/topics and one SPARQL query. Score one framework from 1-5 on seven stated criteria, with evidence.

Independent check

Q1 Does a sitemap guarantee ranking? No. Q2 Good SEO title? Unique, concise, accurate. Q3 RDF unit? Triple. Q4 Best future-framework skill? Evidence-based evaluation against requirements.

Homework – DI322-A09-H1

Write a search/discovery plan for a bilingual course site. Include URL/locale structure, internal links, metadata, sitemap, canonical strategy, Urdu queries, structured data, and measurement. Rubric: technical plan 4, bilingual handling 2, ethical/user focus 2, measurable checks 2.

Revision

Search is a pipeline, SEO is not a ranking guarantee, semantic graphs add machine-readable relationships, and framework choice is a trade-off decision.

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