A stochastic model of an information center

Stochastic model for computerized information handling facility with finite capacit

Key word in context index and bibliography on computer systems evaluation techniques

Selected bibliography of information pertinent to computer system

Key word in context index and bibliography on computer systems simulation and evaluation

Index program for bibliography on systems evaluation, simulation languages, mathematical models, and computer simulation technique

Global parallel unification for large question-answering systems

An efficient means of storing data in a first-order predicate calculus theorem-proving system is described. The data structure is oriented for large scale question-answering (QA) systems. An algorithm is outlined which uses the data structure to unify a given literal in parallel against all literals in all clauses in the data base. The data structure permits a compact representation of data within a QA system. Some suggestions are made for heuristics which can be used to speed-up the unification algorithm in systems

An analysis of some graph theoretical cluster techniques

Graph theoretic cluster techniques for automatic generation of information retrieval systems thesaur

Analysis of data processing systems

Mathematical simulation models and software monitoring of multiprogramming computer syste

Outline bibliography, and KWIC index on mechanical theorem proving and its applications

Bibliography and KWIC index on mechanical theorem proving and its application

Deficit of primitive compositions in binary asteroids and pairs

Context. Small binary asteroid systems and pairs are thought to form through fission induced by spin up via the Yarkovsky-O'Keefe-Radzievskii-Paddack (YORP) effect. This process is expected to depend on their structural strength, hence composition. Aims. We aim to determine how taxonomic classes, used as a proxy for composition, distribute amongst binary asteroids and asteroid pairs compared to the general population. Methods. We compare the distribution of taxonomic classes of binary systems and pairs with that of a reference sample of asteroids. We build this sample by selecting asteroids to reproduce the orbital and size distribution of the binaries and pairs to minimize potential biases between samples. Results. A strong deficit of primitive compositions (C, B, P, D types) among binary asteroids and asteroid pairs is identified, as well as a strong excess of asteroids with mafic-silicate rich surface compositions (S, Q, V, A types). Conclusions. Amongst low mass, rapidly rotating asteroids, those with mafic-silicate rich compositions are more likely to form multiple asteroid systems than their primitive counterparts.Comment: 12 pages, 7 figures, last 5 pages are table

When to Say What and How: Adapting the Elaborateness and Indirectness of Spoken Dialogue Systems

With the aim of designing a spoken dialogue system which has the ability to adapt to the user's communication idiosyncrasies, we investigate whether it is possible to carry over insights from the usage of communication styles in human-human interaction to human-computer interaction. In an extensive literature review, it is demonstrated that communication styles play an important role in human communication. Using a multi-lingual data set, we show that there is a significant correlation between the communication style of the system and the preceding communication style of the user. This is why two components that extend the standard architecture of spoken dialogue systems are presented: 1) a communication style classifier that automatically identifies the user communication style and 2) a communication style selection module that selects an appropriate system communication style. We consider the communication styles elaborateness and indirectness as it has been shown that they influence the user's satisfaction and the user's perception of a dialogue. We present a neural classification approach based on supervised learning for each task. Neural networks are trained and evaluated with features that can be automatically derived during an ongoing interaction in every spoken dialogue system. It is shown that both components yield solid results and outperform the baseline in form of a majority-class classifier