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

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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

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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

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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

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Analyses

Quantitative– Summarized information– Aggregation, filters

Social network analyses Historical retrospective

– Based on timeline views

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Quantitative analyses

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Timeline view (1)

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Timeline view (2)

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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

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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

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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

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Clojure(.org)

LISP on JVM Better Java than Java Dynamic functional homoiconic language Lazy evaluation for sequences Concurrent programming made easy

– STM– Immutable data

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Open Questions

Formal description for patterns Filter out similar results

– But provide means to display them, if requested

Return also partial matches

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Database for logs

Mysql MonetDB (column oriented) Key/Value storage (CouchDB) Graph storage

– Neo4j (JSON)– Allegro graph (SPARQL)

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Thank you for your attention

Jozef.Wagner@tuke.sk

Frantisek.Babic@tuke.sk

Jan.Paralic@tuke.sk

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