Description
Algorithm design techniques for modern data sets arising in, for example, data mining, web analytics, search engines and social networks. Topics may include locality-sensitive hashing, data streaming, clustering, recommendation systems, link analysis, dimensionality reduction, online algorithms, social network analysis, graph partitioning, and randomized algorithms.
Prerequisites
- Prerequisite(s): COMP 2804 with a minimum grade of B+ .
Conditions and arrangements
- Precludes additional credit for Precludes additional credit for COMP 3801 (no longer offered).
- Prerequisite(s): COMP 2804 with a minimum grade of B+ .
- Lecture three hours a week.
Reference text in its original language
Algorithm design techniques for modern data sets arising in, for example, data mining, web analytics, search engines and social networks. Topics may include locality-sensitive hashing, data streaming, clustering, recommendation systems, link analysis, dimensionality reduction, online algorithms, social network analysis, graph partitioning, and randomized algorithms.
- Prerequisite(s): COMP 2804 with a minimum grade of B+ .
- Precludes additional credit for Precludes additional credit for COMP 3801 (no longer offered).
- Lecture three hours a week.
Sources and references
Dates and sources are retained to help you verify the information. Translations are provided to facilitate reading; the official source governs conditions and requirements.
Source reference : https://calendar.carleton.ca/undergrad/courses/COMP/