Robert M. Losee – författare

Information Retrieval performance measures are usually retrospective in nature, representing the effectiveness of an experimental process. However, in the sciences, phenomena may be predicted, given parameter values of the system. After developing a measure that can be applied retrospectively or can be predicted, performance of a system using a single term can be predicted given several different types of probabilistic distributions. Information Retrieval performance can be predicted with multiple terms, where statistical dependence between terms exists and is understood. These predictive models may be applied to realistic problems, and then the results may be used to validate the accuracy of the methods used. The application of metadata or index labels can be used to determine whether or not these features should be used in particular cases. Linguistic information, such as part-of-speech tag information, can increase the discrimination value of existing terminology and can be studied predictively.

This work provides methods for measuring performance that may be used predictively. Means of predicting these performance measures are provided, both for the simple case of a single term in the query and for multiple terms. Methods of applying these formulae are also suggested.

Information is an important concept that is studied extensively across a range of disciplines, from the physical sciences to genetics to psychology to epistemology. Information continues to increase in importance, and the present age has been referred to as the “Information Age.”

One may understand information in a variety of ways. For some, information is found in facts that were previously unknown. For others, a fact must have some economic value to be considered information. Other people emphasize the movement through a communication channel from one location to another when describing information. In all of these instances, information is the set of characteristics of the output of a process. Yet Information has seldom been studied in a consistent way across different disciplines. 

Information from Processes provides a discipline-independent and precise presentation of both information and computing processes.  Information concepts and phenomena are examined in an effort to understand them, given a hierarchy of information processes, where one process uses others. Research about processes and computing is applied to answer the question of what information can and cannot be produced, and to determine the nature of this information (theoretical information science). The book also presents some of the basic processes that are used in specific domains (applied information science), such as those that generate information in areas like reasoning, the evolution of informative systems, cryptography, knowledge, natural language, and the economic value of information.