Upside-down Deduction

Over the recent years, several proposals were made to enhance database systems with automated reasoning. In this article we analyze two such enhancements based on meta-interpretation. We consider on the one hand the theorem prover Satchmo, on the other hand the Alexander and Magic Set methods. Although they achieve different goals and are based on distinct reasoning paradigms, Satchmo and the Alexander or Magic Set methods can be similarly described by upside-down meta-interpreters, i.e., meta-interpreters implementing one reasoning principle in terms of the other. Upside-down meta-interpretation gives rise to simple and efficient implementations, but has not been investigated in the past. This article is devoted to studying this technique. We show that it permits one to inherit a search strategy from an inference engine, instead of implementing it, and to combine bottom-up and top-down reasoning. These properties yield an explanation for the efficiency of Satchmo and a justification for the unconventional approach to top-down reasoning of the Alexander and Magic Set methods

Human Computation and Economics

This article is devoted to economical aspects of Human Computation (HC) and to perspectives of HC in economics. As of economical aspects of HC, it is first observed that much of what makes HC systems effective is economical in nature suggesting that complexity being reconsidered as a “HC complexity” and the conception of efficient HC systems as a “HC economics”. This article also points to the relevance of HC in the development of standard software and to the importance of competition in HC systems. As of HC in economics, it is first argued that markets can be seen as HC systems avant la lettre. Looking more closely at financial markets, the article then points to a speed differential between transactions and credit risk awareness that compromises the efficiency of financial markets. Finally, a HCbased credit risk rating is proposed that, overcoming the afore mentioned speed differential, holds promise for better functioning financial markets

On the Number of 1-Factors of Locally Finite Graphs

AbstractEvery infinite locally finite graph with exactly one 1-factor is at most 2-connected is shown. More generally a lower bound for the number of 1-factors in locally finite n-connected graphs is given

Logic Programming as Constructivism

The features of logic programming that seem unconventional from the viewpoint of classical logic can be explained in terms of constructivistic logic. We motivate and propose a constructivistic proof theory of non-Horn logic programming. Then, we apply this formalization for establishing results of practical interest. First, we show that 'stratification can be motivated in a simple and intuitive way. Relying on similar motivations, we introduce the larger classes of 'loosely stratified' and 'constructively consistent' programs. Second, we give a formal basis for introducing quantifiers into queries and logic programs by defining 'constructively domain independent* formulas. Third, we extend the Generalized Magic Sets procedure to loosely stratified and constructively consistent programs, by relying on a 'conditional fixpoini procedure

The XML Query Language Xcerpt: Design Principles, Examples, and Semantics

Most query and transformation languages developed since the mid 90es for XML and semistructured data—e.g. XQuery [1], the precursors of XQuery [2], and XSLT [3]—build upon a path-oriented node selection: A node in a data item is specified in terms of a root-to-node path in the manner of the file selection languages of operating systems. Constructs inspired from the regular expression constructs , +, ?, and “wildcards” give rise to a flexible node retrieval from incompletely specified data items. This paper further introduces into Xcerpt, a query and transformation language further developing an alternative approach to querying XML and semistructured data first introduced with the language UnQL [4]. A metaphor for this approach views queries as patterns, answers as data items matching the queries. Formally, an answer to a query is defined as a simulation [5] of an instance of the query in a data item

Temporal Stream Algebra

Data stream management systems (DSMS) so far focus on event queries and hardly consider combined queries to both data from event streams and from a database. However, applications like emergency management require combined data stream and database queries. Further requirements are the simultaneous use of multiple timestamps after different time lines and semantics, expressive temporal relations between multiple time-stamps and exible negation, grouping and aggregation which can be controlled, i. e. started and stopped, by events and are not limited to fixed-size time windows. Current DSMS hardly address these requirements. This article proposes Temporal Stream Algebra (TSA) so as to meet the afore mentioned requirements. Temporal streams are a common abstraction of data streams and data- base relations; the operators of TSA are generalizations of the usual operators of Relational Algebra. A in-depth 'analysis of temporal relations guarantees that valid TSA expressions are non-blocking, i. e. can be evaluated incrementally. In this respect TSA differs significantly from previous algebraic approaches which use specialized operators to prevent blocking expressions on a "syntactical" level

Analysing Temporal Relations – Beyond Windows, Frames and Predicates

This article proposes an approach to rely on the standard operators of relational algebra (including grouping and ag- gregation) for processing complex event without requiring window specifications. In this way the approach can pro- cess complex event queries of the kind encountered in appli- cations such as emergency management in metro networks. This article presents Temporal Stream Algebra (TSA) which combines the operators of relational algebra with an analy- sis of temporal relations at compile time. This analysis de- termines which relational algebra queries can be evaluated against data streams, i. e. the analysis is able to distinguish valid from invalid stream queries. Furthermore the analysis derives functions similar to the pass, propagation and keep invariants in Tucker's et al. \Exploiting Punctuation Seman- tics in Continuous Data Streams". These functions enable the incremental evaluation of TSA queries, the propagation of punctuations, and garbage collection. The evaluation of TSA queries combines bulk-wise and out-of-order processing which makes it tolerant to workload bursts as they typically occur in emergency management. The approach has been conceived for efficiently processing complex event queries on top of a relational database system. It has been deployed and tested on MonetDB

A Molecular Biology Database Digest

Computational Biology or Bioinformatics has been defined as the application of mathematical and Computer Science methods to solving problems in Molecular Biology that require large scale data, computation, and analysis [18]. As expected, Molecular Biology databases play an essential role in Computational Biology research and development. This paper introduces into current Molecular Biology databases, stressing data modeling, data acquisition, data retrieval, and the integration of Molecular Biology data from different sources. This paper is primarily intended for an audience of computer scientists with a limited background in Biology

Constrained Query Answering

Traditional answering methods evaluate queries only against positive and definite knowledge expressed by means of facts and deduction rules. They do not make use of negative, disjunctive or existential information. Negative or indefinite knowledge is however often available in knowledge base systems, either as design requirements, or as observed properties. Such knowledge can serve to rule out unproductive subexpressions during query answering. In this article, we propose an approach for constraining any conventional query answering procedure with general, possibly negative or indefinite formulas, so as to discard impossible cases and to avoid redundant evaluations. This approach does not impose additional conditions on the positive and definite knowledge, nor does it assume any particular semantics for negation. It adopts that of the conventional query answering procedure it constrains. This is achieved by relying on meta-interpretation for specifying the constraining process. The soundness, completeness, and termination of the underlying query answering procedure are not compromised. Constrained query answering can be applied for answering queries more efficiently as well as for generating more informative, intensional answers