Cooperative answers in database systems

A major concern of researchers who seek to improve human-computer communication involves how to move beyond literal interpretations of queries to a level of responsiveness that takes the user's misconceptions, expectations, desires, and interests into consideration. At Maryland, we are investigating how to better meet a user's needs within the framework of the cooperative answering system of Gal and Minker. We have been exploring how to use semantic information about the database to formulate coherent and informative answers. The work has two main thrusts: (1) the construction of a logic formula which embodies the content of a cooperative answer; and (2) the presentation of the logic formula to the user in a natural language form. The information that is available in a deductive database system for building cooperative answers includes integrity constraints, user constraints, the search tree for answers to the query, and false presuppositions that are present in the query. The basic cooperative answering theory of Gal and Minker forms the foundation of a cooperative answering system that integrates the new construction and presentation methods. This paper provides an overview of the cooperative answering strategies used in the CARMIN cooperative answering system, an ongoing research effort at Maryland. Section 2 gives some useful background definitions. Section 3 describes techniques for collecting cooperative logical formulae. Section 4 discusses which natural language generation techniques are useful for presenting the logic formula in natural language text. Section 5 presents a diagram of the system

Intensional Query Optimization

We have introduced a new query optimization framework called intensional query optimization (IQO), which enables existing optimization techniques to be applied to queries that use views. In particular, we consider that view definitions may employ unions. Advanced database technologies and applications--such as federation and mediation over heterogeneous database sources--lead to such complex view definitions, and to the need to handle complex, expensive queries. Query rewriting techniques have been proposed which exploit semantic query caches, materialized views, and semantic knowledge about the database domain to optimize query evaluation. These can augment syntactic optimization to reduce evaluation costs further. Such techniques include semantic query caching, query folding, and semantic query optimization. However, most proposed rewrite techniques ignore views in queries; that is, the views are considered as other tables. The IQO framework enables rewrites to be applied to various expansions of the query, even when no such rewrite is applicable directly to the query itself. With IQO, we optimize the query tree, not just the query. The IQO framework introduces the notion of a discounted query, which is a query with some of its expansions "separated out", so the query can be recast into pieces that can be optimized. For this approach to be effective, the sum of the costs of evaluating each piece must be less than the cost of evaluating the query itself. This includes the discounted query. We develop an evaluation plan for discounted queries that is generally more efficient than the evaluation of the queries themselves. (Also cross-referenced as UMIACS-TR-96-72

Semantic Query Optimization for Bottom-Up Evaluation

Semantic query optimization uses semantic knowledge in databases (represented in the form of integrity constraints) to rewrite queries and logic programs for the purpose of more efficient query evaluation. Much work has been done to develop various techniques for optimization. Most of it, however, is only applicable to top-down query evaluation strategies. Moreover, little attention has been paid to the cost of the optimization itself. In this paper, we address the issue of semantic query optimization for bottom-up query evaluation strategies with an emphasis on overall efficiency. We restrict our attention to a single optimization technique, join elimination. We discuss various factors that influence the cost of semantic optimization, and present two abstract algorithms for different optimization approaches. The first one pre-processes a query statically before it is evaluated; the second approach combines query evaluation with semantic optimization using heuristics to achieve the largest possible savings. (Also cross-referenced as UMIACS-TR-95-109

A Rule-based Skyline Computation over a dynamic database

Skyline query which relies on the notion of Pareto dominance filters the data items from a database by ensuring only those data items that are not worse than any others are selected as skylines. However, the dynamic nature of databases in which their states and/or structures change throughout their lifetime to incorporate the current and latest information of database applications, requires a new set of skylines to be derived. Blindly computing skylines on the new state/structure of a database is inefficient, as not all the data items are affected by the changes. Hence, this paper proposes a rule-based approach in tackling the above issue with the main aim at avoiding unnecessary skyline computations. Based on the type of operation that changes the state/structure of a database, i.e. insert/delete/update a data item(s) or add/remove a dimension(s), a set of rules are defined. Besides, the prominent dominance relationships when pairwise comparisons are performed are retained; which are then utilised in the process of computing a new set of skylines. Several analyses have been conducted to evaluate the performance and prove the efficiency of our proposed solution

Inshore and offshore marine migration pathways of Atlantic salmon post-smolts from multiple rivers in Scotland, England, Northern Ireland and Ireland

The migratory behavior of Atlantic salmon (Salmo salar) post-smolts in coastal waters is poorly understood. In this collaborative study, 1914 smolts, from 25 rivers, in four countries were tagged with acoustic transmitters during a single seasonal migration. In total, 1105 post-smolts entered the marine study areas and 438 (39.6%) were detected on a network of 414 marine acoustic receivers and an autonomous underwater vehicle. Migration pathways (defined as the shortest distance between two detections) of up to 575 km and over 100 days at sea were described for all 25 populations. Post-smolts from different rivers, as well as individuals from the same river, used different pathways in coastal waters. Although difficult to generalize to all rivers, at least during the year of this study, no tagged post-smolts from rivers draining into the Irish Sea were detected entering the areas of sea between the Hebrides and mainland Scotland, which is associated with a high density of finfish aquaculture. An important outcome of this study is that a high proportion of post-smolts crossed through multiple legislative jurisdictions and boundaries during their migration. This study provides the basis for spatially explicit assessment of the impact risk of coastal pressures on salmon during their first migration to sea