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  3. Knowledge Technologies

Knowledge Technologies (COMP90049)

Graduate courseworkPoints: 12.5On Campus (Parkville)

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Overview

Year of offer2019
Subject levelGraduate coursework
Subject codeCOMP90049
Campus
Parkville
Availability
Semester 1
Semester 2
FeesSubject EFTSL, Level, Discipline & Census Date

AIMS

Much of the world's knowledge is stored in the form of unstructured data (e.g. text) or implicitly in structured data (e.g. databases). In this subject, students will learn algorithms and data structures for extracting, retrieving and analysing explicit knowledge from various data sources, with a focus on the web. Topics include: data encoding and mark-up, web crawling, regular expressions, document indexing, text retrieval, clustering, classification and prediction, pattern mining, and approaches to evaluation of knowledge technologies.

INDICATIVE CONTENT

Introduction to Knowledge Technologies; String search; Genomics; Text processing and search; Web search and retrieval; Introduction to Data Mining; Introduction to basic Probability; Classification; Association Rules; Clustering; Evaluation measures.

Examples of projects that students may complete are:

  • A method for automatically predicting the geo-location of a Twitter user on the basis of their posts
  • An automatic method for tagging multilingual Wikipedia documents with Wikipedia categories
  • A search engine for Twitter data, which takes into account the time stamp of the query and documents
  • A search engine for web user forum data
  • A search engine servicing mixed monolingual queries (as in monolingual queries from a range of languages) over a large-scale document collection
  • Classification and prediction of some real world problems using machine learning techniques
  • Unification and resolution
  • Nondeterminism, search, and backtracking

Intended learning outcomes

On completion of this subject the student is expected to:

  1. Apply the fundamentals of knowledge systems, including a representative selection of knowledge technology techniques in both theoretical and applied context
  2. Demonstrate practical skills with component technologies used in commonly-deployed knowledge technology systems

  3. Formulate a research methodology, especially relating to knowledge technology-related projects underway at The University of Melbourne

Generic skills

On completion of this subject, students should have the following generic skills:

  • An ability to undertake problem identification, formulation, and develop solutions
  • Synthesize complex systems and processes from fundamental knowledge
  • Apply systematic thinking to address complex problems

Last updated: 5 June 2019