Sentence examples for user specific features from inspiring English sources

We subsequently tried to leverage such user specific features along with accuracy to classify users as legitimate or attacker.

Let us now discuss the user specific social behavioral features we consider for our study, In this section we discuss about meticulously evaluated user specific features which we categorize as user social interaction behavior features.

Or maybe those are new consumer services or, for the enterprise users, specific features that make the lives of IT managers a bit easier.

This is due to the fact that the non-aggregated dataset also contains user-specific features and is thus able to perform predictions based on user similarity, thus, yielding more accurate predictions.

We propose a fixed bit-allocation-based discretization approach to extract a binary representation which is able to fulfill all the required criteria from each given set of user-specific features.

With that motivation in mind, we approached this problem in order to identify the distinctive user-specific features that lead us to discover fraud, or opinion spam in other words.

Fleksy 2.0 also introduces 'My Fleksy Cloud,' a syncing feature that unites Fleksy's user-specific features, including its individual-based language and writing style algorithm, across different installations of the software on multiple Android devices.

In general, the significance of our contribution is three-fold: a) We propose a fixed bit-allocation-based discretization approach to extract a binary representation which is able to fulfill all the required criteria from each given set of user-specific features.

Since sweeping is a common characteristic of different type features, the maximal swept features can serve as an intermediate representation for the different types of feature-based models; in particular, they can be conveniently converted into milling features or turning features, common features or user-specific features, and their alternatives.

An architecture for unsupervised estimation of user-specific feature space adaptation and normalization algorithms is also described and evaluated.

A two-step boosting feature selection (BFS) technique is proposed for selecting a compact and discriminant user-specific feature representation from a large number of feature extractions.