Artificial Intelligence (3 Years) [BSc]

Documents, Services and Data on the Web


Unit code: COMP38120
Credit Rating: 20
Unit level: Level 3
Teaching period(s): Full year
Offered by School of Computer Science
Available as a free choice unit?: Y

Requisites

Prerequisite

Additional Requirements

Students who are not from the School of Computer Science must have permission from both Computer Science and their home School to enrol.

Aims

The aim of this course unit is to provide insights into and experience of techniques relating to documents, services and data on the web. The approach is that fundamental drivers, concepts and techniques for web documents, services and data are presented and discussed in workshop settings, and that a laboratory applies and evaluates the techniques in practice.

Overview

This unit explores the web as a computational artifact, covering all of documents, services and data at web scale. This includes both the capabilities that are available to web users and how they are supported behind the scenes. Thus, for example, students will have experience using a cloud platform to develop scalable applications using techniques that underpin web search engines.

Learning outcomes

Learning outcomes are detailed on the COMP38120 course unit syllabus page on the School of Computer Science's website for current students.

Employability skills

  • Analytical skills
  • Innovation/creativity
  • Problem solving

Assessment methods

  • Written exam - 60%
  • Written assignment (inc essay) - 40%

Syllabus

Enabling the web

  • The internet and the web.
  • Basic platform: URI, HTTP, DNS.
  • Recurring themes: browsing, searching, crawling, linking, annotating, dynamism, scale.
  • Web standards: HTTP, XML, RDF.

The document web

  • Document management.
  • Crawling and analysing the web.
  • Information retrieval: meeting information needs, indexing, ranking.
  • Web graph mining, including PageRank.
  • Enhancing search through analytics and annotation.

The services web

  • Services and the web.
  • Types of service: software, platform, infrastructure.
  • Cloud services: drivers and challenges.
  • Developing scalable cloud services, including map/reduce.

The web of data

  • Data on the web, shallow and deep web.
  • Linked open data, and the linked data principles.
  • Linked data design.
  • Publishing linked data.
  • Consuming and aggregating linked data.

Recommended reading

COMP38120 reading list can be found on the School of Computer Science website for current students.

Feedback methods

The unit consists of workshops and laboratories: both such formats are interactive and enable continuous formative feedback. Summative feedback will be provided on two assessed laboratory activities.

Study hours

  • Practical classes & workshops - 46 hours
  • Independent study hours - 154 hours

Teaching staff

Norman Paton - Unit coordinator

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