|
|
Graduate Courses
|
|
Course: |
CS2531, Advanced Topics in Data Management Systems
|
|
Description: |
Information Integration, Data Warehousing and OLAP: Review of relational
databases and query languages. Conjunctive queries. Information
integration. Data warehousing concepts. On-line analytic processing.
|
|
Prerequisites: |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Course: |
CS2525, Research Topics in Data Management
|
|
Description: |
Advanced graduate reading course in data
management research. Past topics have included Data Mining, Data Integration,
and Data Management in Peer-to-Peer Systems. See course web page for
information on current topic. This is an advanced graduate seminar.
Students should be ready to undertake novel research in data
management research. |
|
Prerequisites: |
CS2508, Graduate standing, |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Course: |
CS2510, Topics in Information Systems
|
|
Description: |
The topics discussed in this course vary from
year to year. Spring 2000 topic: Conceptual Modeling. This
course is intended to teach conceptual modelling notations and how to use
them. The bulk of the course is dedicated to introductions of three
different modelling notations and their features.
These are the Unified Modelling Language (UML), CLASSIC, and KAOS. UML is
an object-oriented modelling language, for modelling all aspects of a
software system. CLASSIC is a description-based knowledge representation
language which supports a tractable form of inference. KAOS is a formal
requirements modelling language for specifying goals, entities,
relationships, actions and agents.
In addition to covering in detail these three notations, the course
reviews the history of conceptual modelling, and covers more advanced
topics, such as modelling intentions and social settings. |
|
Prerequisites: |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Course: |
CS2509, Data Management Systems
|
|
Description: |
The use, management and theory of databases,
especially relational databases. Topics to be selected from the following:
the relational model: relations, operations on relations, relational
algebra and calculi; defining and manipulating data: SQL, embedded SQL,
Query-by-Forms, database applications programming; query optimization:
indices, algebraic optimization, hypergraph representation of queries,
optimization algorithms; transaction management: concurrency,
serializability, deadlocks, transaction protocols, time stamps, crash
recover; design theory for relational databases: functional dependencies,
normal forms, decomposition of relations; security and integrity of data;
distributed databases. |
|
Prerequisites: |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Course: |
CS2508, Information: Quantification, Representation and Manipulation
|
|
Description: |
File structures for use in database implementation. Measurement of information using discrete information
theory; efficient representation of information through data compression
and data compaction; costs and benefits of redundancy in inforamtion; the
tradeoff between retention and recomputation. Information of order and
placement in sequential, indexed and hashed file structures; file
structures for growing files; multiple-key file structures for emulating
associative memory; adaptation of information structures to dynamic usage
patterns. Representation and manipulation of non-textual information:
images, audio, facts, etc; distinguishing content from representation.
Comparison of various file structures to computational models of
information storage and processing in the human mind.
|
|
Prerequisites: |
Familiarity with basic concepts
of computer science, mathematics and programming, |
|
|
|
|
|
|
|
|
|
|
|
|
|
