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Module Specifications

Archived Version 2009 - 2010

Module Title Information Access
Module Code CA652
School School of Computing

Online Module Resources

Module Co-ordinatorProf Alan SmeatonOffice NumberL2 39A
Level 1 Credit Rating 7.5
Pre-requisite None
Co-requisite None
Module Aims
The aim of this module is to familiarise the student with aspects of information management, which impact the e-commerce area. This includes conventional databases, access to text documents and to multimedia information as well as the evolving area of metadata standards.

Learning Outcomes
The learning outcomes are equivalent to the aims. Upon completing the course, the student should be familiar with aspects of information management, which impact the e-commerce area. Specifically this involves access to databases and unstructured data in conventional test retrieval engines and multimedia retrieval engines as well as the evolving area of metadata standards.

Indicative Time Allowances
Hours
Lectures 36
Tutorials
Laboratories 24
Seminars
Independent Learning Time 52.5

Total 112.5
Placements
Assignments
NOTE
Assume that a 7.5 credit module load represents approximately 112.5 hours' work, which includes all teaching, in-course assignments, laboratory work or other specialised training and an estimated private learning time associated with the module.

Indicative Syllabus
What is information access in the context of eCommerce ? Information access now - types of information access people are doing - principally web search - hypertext searching vs DB searching: Web searching and web search engines -text-based IR, Boolean, weighted terms, ranking, Hal Varian''s economics of search, using links information in web searching, question-answering (TREC); Information access to non-text - Audio Image and Video leading on to digital TV and covering encoding formats and current technologies for capturing, storing, presenting and accessing such media; Databases - relational - info access to non-structured - basic organisation of information as tables with foreign/primary keys and constraints - take a complex worked example, such as NAPSTER and show it as a R.DBMS, just for illustration; Data mining from web usage information -what information can we extract from web usage, and how, and what can we use it for; XML and XML databases - all the history, the terminology, the status, the trends - how XML is/can be used in B2B, CEC (consumer-oriented eCommerce) -what are the pitfalls and the potential. Students will use DCU as a worked example from a practical perspective and as the basis for projects.
Assessment
Continuous Assessment30% Examination Weight70%
Indicative Reading List
Modern Information Retrieval Ricardo Baeza-Yates, Berthier Ribiero-Neto Addison Wesley; 2 edition (15 Sep 2008)Understanding Search Engines: Mathematical Modeling and Text RetrievalMichael W. Berry, Murray Society for Industrial Mathematics; 2 edition (1 May 2005)
Programme or List of Programmes
BSSAStudy Abroad (DCU Business School)
BSSAOStudy Abroad (DCU Business School)
CAPDPhD
CAPMMSc
CAPTPhD-track
ECSAStudy Abroad (Engineering & Computing)
ECSAOStudy Abroad (Engineering & Computing)
EEPDPhD
EEPMMEng
EEPTPhD-track
HMSAStudy Abroad (Humanities & Soc Science)
HMSAOStudy Abroad (Humanities & Soc Science)
MECTMSc in Electronic Commerce (Technical)
MEPDPhD
MEPMMEng
MEPTPhD-track
NAVNMUNon Award Visitors- UCD/DCU
SHSAStudy Abroad (Science & Health)
SHSAOStudy Abroad (Science & Health)
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