Sentence examples for context model can be from inspiring English sources

This context model can be used to support and enhance user interaction with an IDE or to improve the accuracy and timing of recommendations produced by RSSEs.

Finally, an activity context model can be constructed, which has both the probability and the temporal relations.

Since the context model can be established to increase the probability of the encoded symbol, the subinterval representing the probability will correspond to be enlarged.

The methods used during the creation of the context model can be grouped into three major parts: a factor identification phase, a model generation phase and a model validation phase (see Figure 2).

In this context, modelling can be very useful, for decision support, as an investigative tool to forecast the outcome of various scenarios, to guide current management in order to meet future targets and to develop integrated frameworks for management accordingly to the Water Framework Directive (WFD).

Moreover, we investigated the use of Markov random field models to introduce spatial coherence in the final classification and show that the two types of context models can be integrated successfully.

In the latter context, models can be erroneous by leaving out "negligible" factors and, at least for reasonable times, our model predictions do not differ significantly with the target systems we are modeling (wait long enough, however, and such predictions will differ significantly).

For instance, models will not provide accurate numerical predictions of outcomes in this context; models can be used to forecast only in fairly gross terms.

In this context, models can be used to quantitatively characterise how drugs affect the dynamics of biological systems as well as the regulatory mechanisms triggered by a given pharmacological intervention [ 3].

In such complex contexts, modeling can be useful since it allows isolating factors and it can play the role of reference for comparisons.

The stepwise reduction, starting from the full context-dependent model, can be seen in Figure 9, with the corresponding log Bayes Factors for each step given in Table 10.