Discovering occurrences of user-defined patterns in historical data representing collaborative activities in virtual user environment Jozef Wagner František.

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Presentation transcript:

Discovering occurrences of user-defined patterns in historical data representing collaborative activities in virtual user environment Jozef Wagner František Babič Ján Paralič KKUI, FEI TU Kosice

Outline Background Source data Analysis Patterns Conclusion WIKT 2010, Bratislava, Slovakia2/16

Background (1) Virtual user environment as working or learning platform Collaborative activities within various groups of users. – Lead to new learning and knowledge practices All activities within virtual user environment are logged WIKT 2010, Bratislava, Slovakia 3/16

Background (2) Complex processes, Ill defined and not easily formulated Not all activities are captured – F2F meetings, field trials, minutes, interviews Researchers and Teachers wants to evaluate user behavior during these activities, identify and understand knowledge practices WIKT 2010, Bratislava, Slovakia 4/16

Source data Dedicated server accepts event logs from various end user tools participating in the learning process In each event – Identify user, object, working group – Type of action, Time – Custom properties WIKT 2010, Bratislava, Slovakia 5/16

Analyses Quantitative – Summarized information – Aggregation, filters Social network analyses Historical retrospective – Based on timeline views WIKT 2010, Bratislava, Slovakia 6/16

Quantitative analyses WIKT 2010, Bratislava, Slovakia 7/16

Timeline view (1) WIKT 2010, Bratislava, Slovakia 8/16

Timeline view (2) WIKT 2010, Bratislava, Slovakia 9/16

Timeline view (3) Visualization of performed events on the timeline in chronological order Interactive tool Filtering, zooming Possiblity to add external events and annotations Posibility to create and use patterns WIKT 2010, Bratislava, Slovakia 10/16

Patterns (1) Process discovery techniques are not applicable Our processes are not rigid, well defined Patterns help to identify critical points and best practices Attempt to formally and explicitly define parts of the process Interactive and iterative WIKT 2010, Bratislava, Slovakia 11/16

Patterns (2) Patterns is a sequence of pattern elements, each representing one generalized event Include logical operations, unification Beyond simple sequence, branching Define weight, multiplicity Searching generates tree of matches WIKT 2010, Bratislava, Slovakia 12/16

Clojure(.org) LISP on JVM Better Java than Java Dynamic functional homoiconic language Lazy evaluation for sequences Concurrent programming made easy – STM – Immutable data WIKT 2010, Bratislava, Slovakia 13/16

Open Questions Formal description for patterns Filter out similar results – But provide means to display them, if requested Return also partial matches WIKT 2010, Bratislava, Slovakia 14/16

Database for logs Mysql MonetDB (column oriented) Key/Value storage (CouchDB) Graph storage – Neo4j (JSON) – Allegro graph (SPARQL) WIKT 2010, Bratislava, Slovakia 15/16

Thank you for your attention WIKT 2010, Bratislava, Slovakia 16/16