Showing papers on "Web query classification published in 1981"

Human Factors Studies of Database Query Languages: A Survey and Assessment

Abstract: Empirical studies have been undertaken to measure the ease-of-use of a query language, compare two or more such languages for ease-of-use, study controversial issues in query language design, and provide feedback to designers for improving a language. Some primitive at tempts at constructing abstract models related to query languages also exist. This paper discusses some of the techniques that have been used and results obtained. A primary goal is to show the reader unfamiliar with behavioral research what the results do and do not mean.

QUIST: a system for semantic query optimization in relational databases

Abstract: Semanfic query ophizotion is an approach to query optimization that uses knowledge of the semantics of the data to transform a query into another query that has the same answer but can be processed more efficiently. However, the indiscriminate application of semantic transformations can itself be excessively costly when there are many semantic rules upon which transformations can be based. This paper describes a semantic query optimization system called QUIST (Query lmprovement through Semantic Transformation). QUIST demonstrates significant cost reductions for a class of relational database queries. At the same time, QUIST uses knowledge about relational database structures and processing methods to insure that semantic transformations are applied selectively. This knowledge reflects cost models and optimization techniques developed in recent query optimization research. To integrate semantic, structure, and processing knowledge, QUIST analyzes a query at several levels of detail, along the lines of the plan-generate-test paradigm of artificial intelligence systems.

Query optimization by semantic reasoning

Abstract: The problem of database query optimization is to select an efficient way to process a query expressed in logical terms from among the alternative ways it can be carried out in the physical database. This thesis presents a new approach to this problem, called semantic query optimization. The goal of semantic query optimization is to produce a semantically equivalent query that is less expensive to process than the original query. Semantic query optimization actually transforms the original query into a new one by means of a process of inference. The transformations are limited to those that yield a semantically equivalent query, one that is guaranteed to produce the same answer as the original query in any permitted state of the database. This guarantee is achieved because the knowledge used to transform a query is the same knowledge used to insure the semantic integrity of the data stored in the database. Thus, semantic query optimization brings together the apparently separate research areas of query processing the database integrity. The thesis also addresses an important issue in current automatic planning research: production not just of a correct solution but of a "good" one, by means of an efficient problem solver. Semantic query optimization advances the notion of a problem reformulation step for problem-solving programs. In this step, equivalent statements of the original problem are sought, one of which may have a better solution than the original problem. This method avoids explicit and possibly costly analysis of efficiency factors during planning itself. Semantic query optimization can also be viewed as one aspect of intelligent database mediation. It applies knowledge of a problem domain and of the capabilities and limitations of the database to pose the most effective and easily processed queries to solve a user's problem. The thesis formally defines transformations that preserve semantic equivalence for queries in the relational calculus. In addition, it identifies several classes of cost-reducing query transformations for relational database queries, and provides quantitative estimates of the improvements they can produce, based upon widely accepted models of query processing. The thesis also discusses the design and implementation of a system that carries out semantic query optimization for an important class of relational database queries. The system is called QUIST, standing for QUery Improvement through Semantic Transformation. The QUIST system has analyzed a range of queries for which different transformations apply. For these queries, QUIST obtains substantial reductions in the cost of processing at a negligible cost for the analysis itself.

Query Languages: Design Recommendations Derived from the Human Factors Literature

Abstract: This paper reviews the human factors literature dealing with query languages. It covers natural and formal query languages, and such specific topics as quantifiers, data organization, mixed initiative dialogues, abbreviations, experimental evaluation of query language features, and research on person-to-person communication. Also discussed are issues to consider when determining a query language's suitability. A summary of the findings, in the form of a compendium of design recommendations, is presented as a result of this review.

How query systems can simplify models and aid analysis

Abstract: Publisher Summary This chapter describes the way in which query systems can simplify models and aid analysis. Commands should have telescopic/microscopic capability that allows increasingly finer and broader focus. In a matrix, the submatrix is analogous to a molecule. The query system should be able to change focus from atoms to molecules. The power of a query system can be measured in two ways: (1) the amount of information that can be eliminated as undesirable in response to a question and (2) the number of queries it takes to answer a question. The PERUSE system is used successfully to determine the root cause of infeasibility and unboundedness. The internal design of an analytical query system supports the external design and is transparent to the analyst. An operational maxim is that the internal design must support the external design and not vice versa. The access software and the data structure should be designed so that space and speed are optimized. In the data structure design, parsimony of space is important even in a virtual storage system. Information, usually stored in different places, should be consolidated in one place.

A Microprocessor Architecture for Bibliographic Retrieval System.

Abstract: In this paper the features of a microprocessor based architecture for bibliographic retrieval system are illustrated. The proposed system consists of the following three functional blocks: the “query processor”, the “simple query executers” and the “answer composer”. The query processor parses the queries and breaks the complex query into simple queries. Each simple query executer is able to perform the operations satisfying a simple query. Finally, the answer composer puts together the results of all simple query executers and produces the response to the query originally raised. This machine will allow the implementation of a very powerfull query language. The basic design goals are the system modularity and a whatever complex query's fulfilment. This is achieved through the proposed query language and by means of the system architecture allowing high parallelism in the performed operations.

Evolution of a query translation system

Abstract: This paper presents the motivation, history, and idiosyncrasy of a query translation system. Detail of the translation process has also been described.