Larry R. Harris

User oriented data base query with the ROBOT natural language query system

Now that large data bases of valuable information are in existence, we must face the problem of putting this information in the hands of the end user. This is not a task to be taken lightly, since it is a very difficult problem due to the mismatch between the users conceptualization of the data and its actual structure. By analyzing this problem in some detail we argue that this mismatch must be consciously resolved in a single process, and that the use of natural language instead of an artificial query language is the only means by which this can be done. The technical feasibility of this approach is demonstrated by the ROBOT natural language query processor. Actual dialogs and end user experiences are used to show the resulting increase in end user orientation. The impact of natural language processing on the various DBMS architectures is also discussed.

The heuristic search under conditions of error

Abstract By placing various restrictions on the heuristic estimator it is possible to constrain the heuristic search process to fit specific needs. This paper introduces a new restriction upon the heuristic, called the “bandwidth” condition, that enables the ordered search to better cope with time and space difficulties. In particular, the effect of error within the heuristic is considered in detail. Beyond this, the bandwidth condition quite naturally allows for the extension of the heuristic search to MIN/MAX trees. The resulting game playing algorithm affords many desirable practical features not found in minimax based techniques, as well as maintaining the theoretical framework of ordered searches. The development of this algorithm provides some additional insight to the general problem of searching game trees by showing that certain, somewhat surprising changes in the cost estimates are required to properly search the tree. Furthermore, the use of an ordered search of MIN/MAX trees brings about a rather provocative departure from the conventional approach to computer game playing.

A system for primitive natural language acquisition

Natural language acquisition deals with two very difficult problems in artificial intelligence: computer learning and natural language processing. This system focuses on the problems involved in the acquisition of primitive linguistic capability. That is when words are first correlated to concepts and when the ordering of the words of utterance first become important. With these beginnings the techniques developed herein eventually acquire the capability to deal with nested dependent clauses. This work is of interest in the field of computer learning in as much as it provides an example of an adaptive system that, rather than tuning numeric weights, actually varies its primary structural element, namely the grammar that defines its current language. This work is of interest in the field of natural language processing in as much as it requires the development of a parsing algorithm robust enough to deal with grammars and dictionaries that vary with time. The ability to automatically extend the,grammar to include new sentence forms is also requisite for language acquisition.

USING THE DATA BASE AS A SEMANTIC COMPONENT TO AID IN THE PARSING OF NATURAL LANGUAGE DATA BASE QUERIES

Many of the recent advances in artificial intelligence (Al) have been brought about through the use of domain specific knowledge. In this same spirit, this paper presents an approach to understanding natural language data base queries that employs the use of domain specific knowledge to aid the parsing process. The unique aspect of 1he data base query environment relative to other AI problem domains is that the required body of knowledge already exists in the form of the data base being queried. Thus, there is an important benefit of making use of this knowledge in the form in which it is maintained by the data base management system, since the very difficult problems of gathering and representing this information can be circumvented. The paper describes the problems encountered in the parsing of data base queries that can be solved by the semantic use of the data base, as well as a precise description of how these problems can be solved by existing data base systems. The proposed use of the data base as ...

The heuristic search: An alternative to the alpha—beta minimax procedure

Many current computer chess programs use a full-width tree search (e.g., CHESS 4.5 from Northwestern (see Chapter 4), KAISSA from the Institute of Control Science, Moscow [2], and TECH II from MIT). Other programs, such as Berliner’s [12], attempt to perform a highly selective search using extremely sophisticated heuristics. Recent improvements in chess play have come primarily from the programs using the “brute force” procedure. In particular the Northwestern program improved markedly when its plausible move selector was replaced by a full-width search. The development of specialized computer hardware, such as the chess-specific central processor which is being developed at MIT, will further benefit this “brute-strength” approach.

Status report on the ROBOT natural language query processor

This is the first in a series of reports to acquaint the AI community with the first commercially available natural language processor for data base query. The system, called ROBOT, is being marketed by the Artificial Intelligence Corporation of Kensington, Maryland, and is currently installed in three commercial sites. In this report we trace the origins of the system, the installation and acceptance testing performed by the user sites, and the impact the system has had on the trade medias view of AI.

Natural language interfaces

The panel will focus on the different approaches to creating natural language interfaces to DBMS. Of particular interest is the manner in which database definition information, user feedback dialogues, storage of the lexicon and database path selection are handled. The panelists have all been involved in implementing such interfaces.