Modeling Knowledge Worker Activity

Tadej Štajner, Dunja Mladeniƈ
Proceedings of the First Workshop on Applications of Pattern Analysis, PMLR 11:127-133, 2010.

Abstract

This paper describes an approach to constructing a probabilistic process model representing knowledge worker activity out of a log of primitive events, such as e-mails, web page visits and document accesses. Firstly, we present the process of enriching the primitive events into abstract actions, executed in different contexts. We explain the process of obtaining both context and action for each event by clustering the events via two different views. Secondly, we present an application of probabilistic deterministic finite automata to model the transitions between consecutive actions within the same context and demonstrate the approach on real-world knowledge worker data for the purpose of understanding knowledge processes and demonstrating the feasibility of the proposed approach, where a process model is constructed out of low-level events.

Cite this Paper

BibTeX
@InProceedings{pmlr-v11-stajner10a, title = {Modeling Knowledge Worker Activity}, author = {Štajner, Tadej and Mladeniƈ, Dunja}, booktitle = {Proceedings of the First Workshop on Applications of Pattern Analysis}, pages = {127--133}, year = {2010}, editor = {Diethe, Tom and Cristianini, Nello and Shawe-Taylor, John}, volume = {11}, series = {Proceedings of Machine Learning Research}, address = {Cumberland Lodge, Windsor, UK}, month = {01--03 Sep}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v11/stajner10a/stajner10a.pdf}, url = {https://proceedings.mlr.press/v11/stajner10a.html}, abstract = {This paper describes an approach to constructing a probabilistic process model representing knowledge worker activity out of a log of primitive events, such as e-mails, web page visits and document accesses. Firstly, we present the process of enriching the primitive events into abstract actions, executed in different contexts. We explain the process of obtaining both context and action for each event by clustering the events via two different views. Secondly, we present an application of probabilistic deterministic finite automata to model the transitions between consecutive actions within the same context and demonstrate the approach on real-world knowledge worker data for the purpose of understanding knowledge processes and demonstrating the feasibility of the proposed approach, where a process model is constructed out of low-level events.} }
Endnote
%0 Conference Paper %T Modeling Knowledge Worker Activity %A Tadej Štajner %A Dunja Mladeniƈ %B Proceedings of the First Workshop on Applications of Pattern Analysis %C Proceedings of Machine Learning Research %D 2010 %E Tom Diethe %E Nello Cristianini %E John Shawe-Taylor %F pmlr-v11-stajner10a %I PMLR %P 127--133 %U https://proceedings.mlr.press/v11/stajner10a.html %V 11 %X This paper describes an approach to constructing a probabilistic process model representing knowledge worker activity out of a log of primitive events, such as e-mails, web page visits and document accesses. Firstly, we present the process of enriching the primitive events into abstract actions, executed in different contexts. We explain the process of obtaining both context and action for each event by clustering the events via two different views. Secondly, we present an application of probabilistic deterministic finite automata to model the transitions between consecutive actions within the same context and demonstrate the approach on real-world knowledge worker data for the purpose of understanding knowledge processes and demonstrating the feasibility of the proposed approach, where a process model is constructed out of low-level events.
RIS
TY - CPAPER TI - Modeling Knowledge Worker Activity AU - Tadej Štajner AU - Dunja Mladeniƈ BT - Proceedings of the First Workshop on Applications of Pattern Analysis DA - 2010/09/30 ED - Tom Diethe ED - Nello Cristianini ED - John Shawe-Taylor ID - pmlr-v11-stajner10a PB - PMLR DP - Proceedings of Machine Learning Research VL - 11 SP - 127 EP - 133 L1 - http://proceedings.mlr.press/v11/stajner10a/stajner10a.pdf UR - https://proceedings.mlr.press/v11/stajner10a.html AB - This paper describes an approach to constructing a probabilistic process model representing knowledge worker activity out of a log of primitive events, such as e-mails, web page visits and document accesses. Firstly, we present the process of enriching the primitive events into abstract actions, executed in different contexts. We explain the process of obtaining both context and action for each event by clustering the events via two different views. Secondly, we present an application of probabilistic deterministic finite automata to model the transitions between consecutive actions within the same context and demonstrate the approach on real-world knowledge worker data for the purpose of understanding knowledge processes and demonstrating the feasibility of the proposed approach, where a process model is constructed out of low-level events. ER -
APA
Štajner, T. & Mladeniƈ, D.. (2010). Modeling Knowledge Worker Activity. Proceedings of the First Workshop on Applications of Pattern Analysis, in Proceedings of Machine Learning Research 11:127-133 Available from https://proceedings.mlr.press/v11/stajner10a.html.

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