ADVANCED INDEXING TECHNIQUES

Course Information
TitleΠΡΟΗΓΜΕΝΗ ΕΥΡΕΤΗΡΙΑΣΗ ΔΕΔΟΜΕΝΩΝ / ADVANCED INDEXING TECHNIQUES
CodeIS24
FacultySciences
SchoolInformatics
Cycle / Level2nd / Postgraduate
Teaching PeriodSpring
CoordinatorKonstantinos Tsichlas
CommonNo
StatusActive
Course ID40002454

Programme of Study: PPS School of Informatics (2014-today)

Registered students: 0
OrientationAttendance TypeSemesterYearECTS
TECΗNOLOGIES GNŌSĪS DEDOMENŌN KAI LOGISMIKOUElective Courses belonging to the selected specialization217.5
TECΗNOLOGIES PLĪROFORIAS KAI EPIKOINŌNIŌN STĪN EKPAIDEUSĪElective Courses217.5
PSĪFIAKA MESA- YPOLOGISTIKĪ NOĪMOSYNĪElective Courses217.5
DIKTYAKA SYSTĪMATAElective Courses217.5

Programme of Study: PPS of School of Informatics (2013-today)

Registered students: 0
OrientationAttendance TypeSemesterYearECTS
Information SystemsCompulsory Course217.5
Information And Communication Technologies In EducationElective Courses217.5
Digital MediaElective Courses217.5
Communication Systems and TechnologiesElective Courses217.5

Class Information
Academic Year2015 – 2016
Class PeriodSpring
Faculty Instructors
Weekly Hours3
Class ID
600011310
Type of the Course
  • Scientific Area
Course Category
Specific Foundation / Core
Mode of Delivery
  • Face to face
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
Learning Outcomes
The students will be able to grasp the basic techniques used to handle massive data. They acquire the necessary knowledge so that they can handle massive data sets supporting efficiently a particular set of operations
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Work in teams
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Algorithms and data structures with emphasis in massive data sets. External memory models. Algorithms and data structures for two level model (B-trees, Computational geometry algorithms in external memory, string algorithms in external memory). Algorithms and data structures for the Cache Oblivious model (Cache Oblivious B-trees). Advanced hashing techniques. Predecessor structures. Algorithms for data compression. Algorithms for the streaming model. Data structures in P2P networks (overlays).
Keywords
External Memory, Streaming model, Compression, Predecessor problem, Hashing
Educational Material Types
  • Notes
  • Slide presentations
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures391.3
Reading Assigment150.5
Project1113.7
Written assigments602
Total2257.5
Student Assessment
Description
The students must complete up to three programming projects. They must also present a paper related to the content of the course while they must also solve a set of theory exercises in order to understand the content of the course better. The evaluation criteria are published in the webpage of the course.
Student Assessment methods
  • Written Exam with Extended Answer Questions (Summative)
  • Written Assignment (Summative)
  • Performance / Staging (Summative)
  • Written Exam with Problem Solving (Formative)
  • Report (Summative)
Bibliography
Additional bibliography for study
1. J. Abello, P.M. Pardalos and M.G.C. Resende (editors). Handbook of Massive Data Sets. Kluwer Academic Publishers. 2002, ISBN: 1-4020-0489-3. 2. D. Menta and S Sahni, Handbook of Data Structures and Application. 2005, ISBN 1-5848-8435-5 3. J. Vitter, Algorithms and Data Structures for External Memory, Book, (http://www.ittc.ku.edu/~jsv/Papers/Vit.IO_book.pdf) 4. External Memory Geometric Data Structures. L. Arge, Duke University Lecture notes 5. Erik Demaine, Cache Oblivious Algorithms and Data-Structures, in Lecture Notes from the EEF Summer School on Massive Data Sets, Lecture Notes in Computer Science, BRICS, University of Aarhus, Denmark, June 27-July 1, 2002, (http://erikdemaine.org/papers/BRICS2002/) 6. *Muthu Muthukrishnan, Data Streams: Algorithms and Applications (ebook) (http://algo.research.googlepages.com/eight.ps)
Last Update
21-03-2016