323 research outputs found
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
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
Bioinformatics Databases: State of the Art and Research Perspectives
Bioinformatics or computational biology, i.e. the application of mathematical and computer science methods to solving problems in molecular biology that require large scale data, computation, and analysis, is a research area currently receiving a considerable attention. Databases play an essential role in molecular biology and consequently in bioinformatics. molecular biology data are often relatively cheap to produce, leading to a proliferation of databases: the number of bioinformatics databases accessible worldwide probably lies between 500 and 1.000. Not only molecular biology data, but also molecular biology literature and literature references are stored in databases. Bioinformatics databases are often very large (e.g. the sequence database GenBank contains more than 4 × 10 6 nucleotide sequences) and in general grows rapidly (e.g. about 8000 abstracts are added every month to the literature database PubMed). Bioinformatics databases are heterogeneous in their data, in their data modeling paradigms, in their management systems, and in the data analysis tools they supports. Furthermore, bioinformatics databases are often implemented, queried, updated, and managed using methods rarely applied for other databases. This presentation aims at introducing in current bioinformatics databases, stressing their aspects departing from conventional databases. A more detailed survey can be found in [1] upon which thi
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