In this paper we motivate how personal knowledge models can make knowledge workers more productive. The external representation can help him to tackle typical cognitive limits. They do so by allowing a knowledge worker to efficiently and effectively model her or his personal knowledge in a mix

persons, organizations, products, etc. with their semantic relationships – and in quantity by increasing the number of facts by more than an order of magnitude. Our empirical evaluation of fact correctness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable

motivated work behavior to develop; (b) the characteristics of jobs that can create these psychological states; and (c) the attributes of individuals that determine how positively a person will respond to a complex and challenging job. The model was tested for 658 employees who work on 62 different jobs

and metric assumptions are open to question. It has been argued by many authors that dimensional representations are appropriate for certain stimuli (e.g., colors, tones) but not for others. It seems more appropriate to represent faces, countries, or personalities in terms of many qualitative features than

;once removed." The research question becomes: How are intrafamilial processes affected by extrafamilial conditions? Paradigm Parameters In tracing the evolution of research models in developmental science, Bronfenbrenner and Crouter (1983) distinguished a series of progressively more sophisticated

workers acquire knowledge about the most common or easiest problems confronted, and specialized problem solvers deal with the more exceptional or harder problems. The paper shows that the model is consistent with stylized facts in the theory of organizations and uses it to analyze the impact of changes

, person, employee, product) and relations (e.g., employed_by, produced_by) of interest when creating the knowledge base. The second is a set of training data consisting of labeled regions of hypertext that represent instances of these classes and relations. Given these inputs, the system learns to extract

by introducing cognitive modeling. Cognitive models go beyond behavioral models in that they govern what a character knows, how that knowledge is acquired, and how it can be used to plan actions. To help build cognitive models, we develop the cognitive modeling language CML. Using CML, we can imbue a character

One of the fundamental assumption driving technology investment is more the merrier. The benefits achieved at task level for individuals are expected to eventually roll-up to organization-level productivity improvements. This paper explores the un-intended impacts of technology that stifles users

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