SIR: A Computer Program for Semantic Information Retrieval

SIR is a computer system, programmed in the LISP language, which accepts information and answers questions expressed in a restricted form of English. This system demonstrates what can reasonably be called an ability to "understand" semantic information. SIR's semantic and deductive ability is based on the construction of an internal model, which uses word associations and property lists, for the relational information normally conveyed in conversational statements. A format-matching procedure extracts semantic content from English sentences. If an input sentence is declarative, the system adds appropriate information to the model. If an input sentence is a question, the system searches the model until it either finds the answer or determines why it cannot find the answer. In all cases SIR reports its conclusions. The system has some capacity to recognize exceptions to general rules, resolve certain semantic ambiguities, and modify its model structure in order to save computer memory space. Judging from its conversational ability, SIR, is a first step toward intelligent man-machine communication. The author proposes a next step by describing how to construct a more general system which is less complex and yet more powerful than SIR. This proposed system contains a generalized version of the SIR model, a formal logical system called SIR1, and a computer program for testing the truth of SIR1 statements with respect to the generalized model by using partial proof procedures in the predicate calculus. The thesis also describes the formal properties of SIR1 and how they relate to the logical structure of SIR.

Generating Semantic Descriptions From Drawings of Scenes With Shadows

The research reported here concerns the principles used to automatically generate three-dimensional representations from line drawings of scenes. The computer programs involved look at scenes which consist of polyhedra and which may contain shadows and various kinds of coincidentally aligned scene features. Each generated description includes information about edge shape (convex, concave, occluding, shadow, etc.), about the type of illumination for each region (illuminated, projected shadow, or oriented away from the light source), and about the spacial orientation of regions. The methods used are based on the labeling schemes of Huffman and Clowes; this research provides a considerable extension to their work and also gives theoretical explanations to the heuristic scene analysis work of Guzman, Winston, and others.

Presentation Based User Interface

A prototype presentation system base is described. It offers mechanisms, tools, and ready-made parts for building user interfaces. A general user interface model underlies the base, organized around the concept of a presentation: a visible text or graphic for conveying information. Te base and model emphasize domain independence and style independence, to apply to the widest possible range of interfaces. The primitive presentation system model treats the interface as a system of processes maintaining a semantic relation between an application data base and a presentation data base, the symbolic screen description containing presentations. A presenter continually updates the presentation data base from the application data base. The user manipulates presentations with a presentation editor. A recognizer translates the user's presentation manipulation into application data base commands. The primitive presentation system can be extended to model more complex systems by attaching additional presentation systems. In order to illustrate the model's generality and descriptive capabilities, extended model structures for several existing user interfaces are discussed. The base provides support for building the application and presentation data bases, linked together into a single, uniform network, including descriptions of classes of objects as we as the objects themselves. The base provides an initial presentation data base network graphics to continually display it, and editing functions. A variety of tools and mechanisms help create and control presenters and recognizers. To demonstrate the base's utility, three interfaces to an operating system were constructed, embodying different styles: icons, menu, and graphical annotation.

Context Mediation in the Semantic Web: Handling OWL Ontology and Data Disparity through Context Interchange

The COntext INterchange (COIN) strategy is an approach to solving the problem of interoperability of semantically heterogeneous data sources through context mediation. COIN has used its own notation and syntax for representing ontologies. More recently, the OWL Web Ontology Language is becoming established as the W3C recommended ontology language. We propose the use of the COIN strategy to solve context disparity and ontology interoperability problems in the emerging Semantic Web – both at the ontology level and at the data level. In conjunction with this, we propose a version of the COIN ontology model that uses OWL and the emerging rules interchange language, RuleML.