145,802 research outputs found
Using regular expressions to express bowing patterns for string players
The study of bowing is critically important for string players. Traditional bowing annotations are a valuable part of orchestral and individual documentation, but they do not help the performer to search a piece for other passages that should be bowed the same way, or to identify alternative bowing styles. We introduce a notation based on regular expressions that describes patterns of notes in the music, as well as the bowing to be applied to the pattern. These expressions support complex bowings, and not just single annotations without musical context. The notation is simpler than general tools for regular expressions used in some software, and is suitable for use by students and musicians. We have developed a music editor that implements the notation and edits documents in Lilypond. The approach has been evaluated by experimenting with the editor on six violin sonatas by Mozart. The experiments demonstrate that the regular expression notation
is successful at finding passages and inserting the bowings; that the patterns occur a number of times; and the bowings can be inserted automatically and consistently
Regular Expression Search on Compressed Text
We present an algorithm for searching regular expression matches in
compressed text. The algorithm reports the number of matching lines in the
uncompressed text in time linear in the size of its compressed version. We
define efficient data structures that yield nearly optimal complexity bounds
and provide a sequential implementation --zearch-- that requires up to 25% less
time than the state of the art.Comment: 10 pages, published in Data Compression Conference (DCC'19
Processing SPARQL queries with regular expressions in RDF databases
Background: As the Resource Description Framework (RDF) data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf) or Bio2RDF (bio2rdf.org), SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users' requests for extracting information from the RDF data as well as the lack of users' knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph.
Results: In this paper, we propose a novel framework for supporting regular expression processing in SPARQL query. Our contributions can be summarized as follows. 1) We propose an efficient framework for processing SPARQL queries with regular expression patterns in RDF databases. 2) We propose a cost model in order to adapt the proposed framework in the existing query optimizers. 3) We build a prototype for the proposed framework in C++ and conduct extensive experiments demonstrating the efficiency and effectiveness of our technique.
Conclusions: Experiments with a full-blown RDF engine show that our framework outperforms the existing ones by up to two orders of magnitude in processing SPARQL queries with regular expression patterns.X113sciescopu
A lexical database tool for quantitative phonological research
A lexical database tool tailored for phonological research is described.
Database fields include transcriptions, glosses and hyperlinks to speech files.
Database queries are expressed using HTML forms, and these permit regular
expression search on any combination of fields. Regular expressions are passed
directly to a Perl CGI program, enabling the full flexibility of Perl extended
regular expressions. The regular expression notation is extended to better
support phonological searches, such as search for minimal pairs. Search results
are presented in the form of HTML or LaTeX tables, where each cell is either a
number (representing frequency) or a designated subset of the fields. Tables
have up to four dimensions, with an elegant system for specifying which
fragments of which fields should be used for the row/column labels. The tool
offers several advantages over traditional methods of analysis: (i) it supports
a quantitative method of doing phonological research; (ii) it gives universal
access to the same set of informants; (iii) it enables other researchers to
hear the original speech data without having to rely on published
transcriptions; (iv) it makes the full power of regular expression search
available, and search results are full multimedia documents; and (v) it enables
the early refutation of false hypotheses, shortening the
analysis-hypothesis-test loop. A life-size application to an African tone
language (Dschang) is used for exemplification throughout the paper. The
database contains 2200 records, each with approximately 15 fields. Running on a
PC laptop with a stand-alone web server, the `Dschang HyperLexicon' has already
been used extensively in phonological fieldwork and analysis in Cameroon.Comment: 7 pages, uses ipamacs.st
Fast and Compact Regular Expression Matching
We study 4 problems in string matching, namely, regular expression matching,
approximate regular expression matching, string edit distance, and subsequence
indexing, on a standard word RAM model of computation that allows
logarithmic-sized words to be manipulated in constant time. We show how to
improve the space and/or remove a dependency on the alphabet size for each
problem using either an improved tabulation technique of an existing algorithm
or by combining known algorithms in a new way
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