Hierarchical Structure Information Research Articles

A Functional Approach to the Hierarchical Structure of Information

Describes a method of construction and representation of scientific knowledge, as a hierarchical information structure, using the propositional form of semanti‐net formulism. The method can be used for developing knowledge‐based systems and, in particular, Computer‐Assisted Learning (CAL) programs. The method is theoretically based on issues taken from both psychology and computer sciences, and particularly the cognitive aspects of memory organization and the conversation and comprehension processes. Scientific knowledge is regarded as being made up of three types of information: definitions, methods and procedures. Each type consists of information represented by separate and meaningful properties, together with their relationships and the processes that may occur in using this information during comprehension and conversation.

A grammar-based approach towards unifying hierarchical data models

A simple model for representing the hierarchical structure of information is proposed. This model, called the grammatical model, is based on trees that are generated by grammars; the grammars describe the hierarchy of the information represented by the trees. Two transformation languages, an algebra and a calculus, are presented and shown to be equally expressive.

Generating intonational support for discourse

Proper intonation can make a spoken message more intelligible by marking information as old or new and communicating the hierarchical structure of information. Use of intonational variation is especially feasible in a system that synthesizes speech from an abstract representation (instead of from text) because the program already knows the structure of the information to be conveyed. This paper presents a schema for assigning pitch range and choosing pitch accents. The schema draws upon work on discourse [B. J. Grosz and C. L. Sidner, Comput. Linguist. 12, 175–204 (1986)] and on intonational meaning [J. Hirschberg and J. Pierrehumbert, Proc. 24th Meet. Assoc. Comput. Ling., 136–144 (1986)]. The model has been tested with a program which generates spoken directions for driving in Cambridge [J. Davis, Proc. Am. Voice I/O Soc.(1986)].

Forecasting the Forecasts of Others

This paper explores the formulation and analysis of linear equilibrium models of investment in which learning is perpetual and informationally decentralized firms need never share the same beliefs concerning time series relevant to their decisions. Recursive, Kalman filtering techniques are shown to be applicable in an illustrative, hierarchical information structure, and a nonlinear technique of undetermined coefficients is shown to be applicable in an illustrative, symmetric information structure in which there is a confounding of laws of motion with forecasting problems. The equilibrium time series of these models can display interesting movement in response to shocks and measurement errors, including persistence, certain cross-correlation properties, and damped oscillations. That is, forecasts errors are serially correlated over decision makers and serially correlated over time in a certain crucial sense. More generally, these models do place restrictions on observed time series and can be fitted to data.

線形連続系の階層的精報構造のもとにおける最適制御

線形連続系の階層的精報構造のもとにおける最適制御