for image retrieval systems. Step one of the review is image processing for retrieval sorted by color, texture, and local geometry. Features for retrieval are discussed next, sorted by: accumulative and global features, salient points, object and shape features, signs, and structural combinations thereof

to be an important determinant of fund flows. High performance appears to be most salient for funds that exert higher marketing effort, as measured by higher fees. Flows are directly related to the size of the fund’s complex as well as the current media attention received by the fund, which lower consumers ’ search

where each node captures an abstraction such as, e.g., goal, action, agent, entity, or event, and where the edges capture semantic links between such abstractions. Well-formedness properties on nodes and links constrain their instances - that is, elements of requirements models. Requirements acquisition

incorporates features not found in earlier proposals; it is easier to use and has greater expressive power. Some of the salient features of our language are: ffl Precise model-theoretic semantics. ffl A very expressive form of path expressions that not only can do joins, selections and unnesting, but can also

This paper describes the Structure-Mapping Engine (SME), a program for studying analogical processing. SME has been built to explore Gentner's Structure-mapping theory of analogy, and provides a "tool kit" for constructing matching algorithms consistent with this theory. Its flexibility enhances cognitive simulation studies by simplifying experimentation. Furthermore, SME is very efficient, making it a useful component in machine learning systems as well. We review the Structure-mapping theory and describe the design of the engine. We analyze the complexity of the algorithm, and demonstrate that most of the steps are polynomial, typically bounded by O (N 2 ). Next we demonstrate some examples of its operation taken from our cognitive simulation studies and work in machine learning. Finally, we compare SME to other analogy programs and discuss several areas for future work. This paper appeared in Artificial Intelligence, 41, 1989, pp 1-63. For more information, please contact forbu...

One of the fundamental principles of the database approach is that a database allows a nonredundant, unified representation of all data managed in an organization. This is achieved only when methodologies are available to support integration across organizational and application boundaries. Methodologies for database design usually perform the design activity by separately producing several schemas, representing parts of the application, which are subsequently merged. Database schema integration is the activity of integrating the schemas of existing or proposed databases into a global, unified schema. The aim of the paper is to provide first a unifying framework for the problem of schema integration, then a comparative review of the work done thus far in this area. Such a framework, with the associated analysis of the existing approaches, provides a basis for identifying strengths and weaknesses of individual methodologies, as well as general guidelines for future improvements and extensions.

Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech tagging, text segmentation and information extraction. In these cases, the observations are usually modeled as multinomial distributions over a discrete vocabulary, and the HMM parameters are set to maximize the likelihood of the observations. This paper presents a new Markovian sequence model, closely related to HMMs, that allows observations to be represented as arbitrary overlapping features (such as word, capitalization, formatting, part-of-speech), and defines the conditional probability of state sequences given observation sequences. It does this by using the maximum entropy framework to fit a set of exponential models that represent the probability of a state given an observation and the previous state. We present positive experimental results on the segmentation of FAQ’s. 1.

... structure. As Levin has addressed (Levin 1985), the decomposition of verbs is proposed for the purposes of accounting for systematic semantic-syntactic correspondences. This results in a series of problems for MT systems: inflexible verb sense definitions; difficulty in handling metaphor and new usages; imprecise lexical selection and insufficient system coverage. It seems one approach is to apply probability methods and statistical models for some of these problems. However, the question reminds: has PSR exhausted the potential of the knowledge-based approach? If not, are there any alternatives that can improve the handling of these problems? We suggest an alternative that represents verb semantic knowledge and accounts for not only fine-tuned systematic semantic-syntactic correspondences, but also semantic-interpretation correspondences. A verb is not represented by a predicate or simple primitives, but by a set of semantic components that are sensitive to the syntactic altern

The difficulties inherent in obtaining con-sistent and adequate diagnoses for the pur-poses of research and therapy have been pointed out by a number of authors. Pasamanick12 in a recent article viewed the low interclinician agreement on diagnosis as an indictment of the present state of psychiatry and called for "the development of objective, measurable and verifiable criteria of classification based not on per-sonal or parochial considerations, but- on behavioral and other objectively measurable manifestations." Attempts by other investigators to subject clinical observations and judgments to ob-jective measurement have resulted in a wide variety of psychiatric rating ~ c a l e s. ~ J ~ These have been well summarized in a re-view article by Lorr l1 on "Rating Scales and Check Lists for the E v a 1 u a t i o n of Psychopathology. " In the area of psy-chological testing, a variety of paper-and-pencil tests have been devised for the purpose of measuring specific personality traits; for example, the Depression-Elation Test, de-vised by Jasper in 1930. This report describes the development of an instrument designed to measure the behavioral manifestations of depression. In the planning of the research design of a project aimed at testing certain psychoanalyt-ic formulations of depression, the necessity for establishing an appropriate system for identifying depression was recognized. Be-cause of the reports on the low degree of interclinician agreement on diagnosis,13 we could not depend on the clinical diagnosis, but had to formulate a method of defining depression that would be reliable and valid. The available instruments were not con-sidered adequate for our purposes. The Min-nesota Multiphasic Personality Inventory, for example, was not specifically designed Submitted for publication Nov. 29, 1960. This investigation was supported by Research

Agent-oriented techniques represent an exciting new means of analysing, designing and building complex software systems. They have the potential to significantly improve current practice in software engineering and to extend the range of applications that can feasibly be tackled. Yet, to date, there have been few serious attempts to cast agent systems as a software engineering paradigm. This paper seeks to rectify this omission. Specifically, it will be argued that: (i) the conceptual apparatus of agent-oriented systems is well-suited to building software solutions for complex systems and (ii) agent-oriented approaches represent a genuine advance over the current state of the art for engineering complex systems. Following on from this view, the major issues raised by adopting an agent-oriented approach to software engineering are highlighted and discussed.