Adding Bits of Precision to Usage Models
نویسنده
چکیده
For interactive systems, usage models are an important component of the requirements specification. In the spirit of agile methods and “just enough" written communication, well-understood user activities might be communicated by XP user stories and subsequent discussions. In cloudier areas, more details should be written to reduce the risk of misunderstanding. This paper describes nine techniques that you can use to increase the precision of your usage models. Each technique can be used alone or in combination to supplement your current practice. Readers are assumed to have a basic understanding of use cases.
منابع مشابه
Using Regression based Control Limits and Probability Mixture Models for Monitoring Customer Behavior
In order to achieve the maximum flexibility in adaptation to ever changing customer’s expectations in customer relationship management, appropriate measures of customer behavior should be continually monitored. To this end, control charts adjusted for buyer’s/visitor’s prior intention to repurchase or visit again are suitable means taking into account the heterogeneity across customers. In the ...
متن کاملUsing Parse Features for Preposition Selection and Error Detection
We evaluate the effect of adding parse features to a leading model of preposition usage. Results show a significant improvement in the preposition selection task on native speaker text and a modest increment in precision and recall in an ESL error detection task. Analysis of the parser output indicates that it is robust enough in the face of noisy non-native writing to extract useful information.
متن کاملComparison of Adders for optimized Exponent Addition circuit in IEEE754 Floating point multiplier using VHDL
Floating point arithmetic has a vast applications in DSP, digital computers, robots due to its ability to represent very small numbers and big numbers as well as signed numbers and unsigned numbers. In spite of complexity involved in floating point arithmetic, its implementation is increasing day by day. Here we compare three different types of adders while calculating the addition of exponent ...
متن کاملBit Grooming: statistically accurate precision-preserving quantization with compression, evaluated in the netCDF Operators (NCO, v4.4.8+)
Geoscientific models and measurements generate false precision (scientifically meaningless data bits) that wastes storage space. False precision can mislead (by implying noise is signal) and be scientifically pointless, especially for measurements. By contrast, lossy compression can be both economical (save space) and heuristic (clarify data limitations) without compromising the scientific inte...
متن کاملCommon Sense Based Joint Training of Human Activity Recognizers
Given sensors to detect object use, commonsense priors of object usage in activities can reduce the need for labeled data in learning activity models. It is often useful, however, to understand how an object is being used, i.e., the action performed on it. We show how to add personal sensor data (e.g., accelerometers) to obtain this detail, with little labeling and feature selection overhead. B...
متن کامل