Web- and Multimedia-based Information Systems

Assessment Presentation Programming Assignment

Presentations Document Management Systems & OCR – Market Overview – Algorithm Introduction Video on Demand – Real Media – Technology Authoring Systems – Macromedia Products

Presentations Content Management – Functionality – Market Overview – Opencms Application Server – Functionality – Market Overview

Presentations VRML – Syntax Introduction – Exercise SMIL : Multimedia Synchronisation – Syntax Introduction – Exercise

Presentations Software / Frontend Ergonomics (HCI) Usability Navigation

What are Information Systems? Store Information Retrieval

Information Textual Audiovisual – Images – Audio – Video Multimedia Documents

Information System Classification Expert Systems Transaction Processing Systems Office Automation Systems Management/Executive Information Systems Geographic Information Systems Information Retrieval Systems

Expert Systems Problem Solving Artificial Intelligence Replace an Expert Multiple operational Implementations Often Implemented using Prolog

Transaction Processing Systems Records Events of interest to an organization Supports the operational level of the business High data volume

TPS applications Manufactoring and Production Sales and Marketing Finance and Accounting Human Resources

Office Automation Personal Productivity Groupware & Communications

Management/Executive Information Systems Analysis of TPS data Higher Level Reports Drill Down to detailed Information possible

Geographic Information Systems Different Sources Spatial Data Visualization

Information Retrieval

Information Retrieval System Manages Documents = Records of Information Presents relevant Documents on a Query

Information Retrieval System Examples POTS directory assistance Library Catalog World Wide Web Search Engine

Information Retrieval Deals with the – Representation of – Storage of – Organization of – Access to Information items

History Early Example: Book‘s Table of Contents Indices in libraries Only recently automatic indexing The Web – Easy & cheap access – Variety of sources – Freedom of Publication, Interactivity

Data Retrieval vs Information Retrieval Exact match Looks for matching items Complete Query Data with well defined structure and semantics Best match Looks for Relevant Items Incomplete Query Natural Language Documents

Information Retrieval and the Web IR originally Text Indexing and Searching Web is highly heterogenous System, no common data model Navigation is ineffiecient Information Retrieval promises to structure information and ease fulfilling information needs

Usage: Information Retrieval User has Information need User translates this need into a machine- understandable Query System retrieves relevant Information

The User Retrieval Browsing Database

Logical Views of a Document Full text Set of Index Terms – Specified by human expert – Text Operations Elimination of Stopwords Stemming Compression Intermediate Logical Views Structure Recognition

Retrieval Process User Interface Text Operations Text Database DB Manager Module Index Searching Ranking

Operational Modes Ad Hoc – Fixed Database, changing Queries Filtering – Fixed Queries, changing Database – User Profiles

Information Retrieval Data Structures

Data Structures Linear list Sequentially ordered file Indexed file

Linear List Unsorted list of documents Easy addition of files Traversal required for a search Author D Author E Author A Author F Author B Author G Author C

Sequentially Ordered File Sorted by the values of a Key Addition of documents more involved Binary search possible Author A Author B Author C Author D Author E Author F Author G

Indices A1B2...F6A1B2...F6 Author A Author B Author C Author D Author E Author F

Inverted Indices An index of all the words in the texts Vocabulary – Different Words in the text – Little Space required after Text Operations Occurences – Positions – More Space required, ~30-40% of text size

Inverted Indices Block Addressing – Smaller Pointers – References in one block are collapsed – Online Search required for exact positions – Fixed Size Blocks or Natural Cuts Fully Inverted Indices – For less readily accessable collections if exact position is required

Information Retrieval Models

Classic IR Models Boolean Vector Probabilistic

Common Concepts Index Terms Weigths for varying relevance

Boolean Model Pro Easy to understand Precise Semantics of a query Contra Binary Decision Difficult for users

Boolean Model Example Query Q = 1 AND ( 2 OR NOT 3) AND 1 OR 2NOT 3

Boolean Model – Set Operations AND : Intersection (Durchschnitt) OR : Union (Vereinigung) NOT : Complement (Komplement) – Seldom used on its own