We present a system for collecting content from 3D multi-user virtual worlds for use in a cross-world search engine, an enabling technology for linking virtual worlds to the wider web. We use an intelligent agent crawler designed to collect user-generated content without relying on access to private internal server databases. The agents navigate autonomously through the world and interact with content to discover regions, parcels of land within regions, user-created objects, other avatars, and user associations. The experiments we performed are the first which focus on the content within a large virtual world. Our results show that virtual worlds can be effectively crawled using autonomous agent crawlers that emulate normal user behavior. Additionally, we find that the collection of interactive content enhances our ability to identify dynamic, immersive environments within the world.

Object-oriented database systems (OODBS), which aim at meeting the data modeling, performance, cooperative design, and version management requirements of next-generation applications, such as CAD, CAM, CASE, hypermedia, and expert systems, are discussed. Key features of OODBS are presented, a taxonomy of approaches is provided, and architectural and implementation issues, design alternatives, and tradeoffs are examined. A variety of OODB systems, both research prototypes and commercial systems, are summarized. Industry efforts to accelerate a consensus that can lead to standards in the OODB are discussed.>

Explorer is a LISP Machine from Texas Instruments. Its software starts with a vast body of software developed at MIT. Texas Instruments has stabilized that software and added more packages and utilities. This paper describes certain innovations in Texas Instrument's software for the Explorer. TI's software innovations were in two areas: increasing the learnability of this sophisticated system and adding software components as an aid to prototypers and software developers. Learning aid innovations are embodied in Suggestions Menus and the Universal Command Loop. Software component innovations are embodied in the Universal Command Loop, the Graphics Window System and Graphics Editor, the Relational Table Manager, and the Menu-Based Natural Language Interface. The innovations represented are of two kinds: innovations in concept(Suggestions Menus, Universal Command Loop, and Menu-Based Natural Language Interface) and innovations in design (Graphics Window System, Relational Table Manager).

This paper describes the NLMenu System, a menu-based natural language understanding system. Rather than requiring the user to type his input to the system, input to NLMenu is made by selecting items from a set of dynamically changing menus. Active menus and items are determined by a predictive left-corner parser that accesses a semantic grammar and lexicon. The advantage of this approach is that all inputs to the NLMenu System can be understood thus giving a 0% failure rate. A companion system that can automatically generate interfaces to relational databases is also discussed.

Conventional natural language interfaces suffer from several ease-of-use problems. They require a user to type and to formulate questions in a way that the system can understand. They have high failure rates which often frustrate users, and users often do not use features of the systems because they are unaware of them or don't trust them. In addition, conventional natural language systems are expensive to build and require large amounts of storage to use. This paper describes a new approach to natural language interfaces called menu-based natural language understanding. This new approach solves the problems listed above. The paper compares the menu-based natural language approach to conventional natural language interfaces and to other forms of interface and discusses the advantages and limitations of this new approach.