7,396 research outputs found
Exploiting non-constant safe memory in resilient algorithms and data structures
We extend the Faulty RAM model by Finocchi and Italiano (2008) by adding a
safe memory of arbitrary size , and we then derive tradeoffs between the
performance of resilient algorithmic techniques and the size of the safe
memory. Let and denote, respectively, the maximum amount of
faults which can happen during the execution of an algorithm and the actual
number of occurred faults, with . We propose a resilient
algorithm for sorting entries which requires time and uses safe memory words. Our
algorithm outperforms previous resilient sorting algorithms which do not
exploit the available safe memory and require time. Finally, we exploit our sorting algorithm for
deriving a resilient priority queue. Our implementation uses safe
memory words and faulty memory words for storing keys, and
requires amortized time for each insert and
deletemin operation. Our resilient priority queue improves the amortized time required by the state of the art.Comment: To appear in Theoretical Computer Science, 201
Co-occurrence Vectors from Corpora vs. Distance Vectors from Dictionaries
A comparison was made of vectors derived by using ordinary co-occurrence
statistics from large text corpora and of vectors derived by measuring the
inter-word distances in dictionary definitions. The precision of word sense
disambiguation by using co-occurrence vectors from the 1987 Wall Street Journal
(20M total words) was higher than that by using distance vectors from the
Collins English Dictionary (60K head words + 1.6M definition words). However,
other experimental results suggest that distance vectors contain some different
semantic information from co-occurrence vectors.Comment: 6 pages, appeared in the Proc. of COLING94 (pp. 304-309)
Error-Correcting Data Structures
We study data structures in the presence of adversarial noise. We want to
encode a given object in a succinct data structure that enables us to
efficiently answer specific queries about the object, even if the data
structure has been corrupted by a constant fraction of errors. This new model
is the common generalization of (static) data structures and locally decodable
error-correcting codes. The main issue is the tradeoff between the space used
by the data structure and the time (number of probes) needed to answer a query
about the encoded object. We prove a number of upper and lower bounds on
various natural error-correcting data structure problems. In particular, we
show that the optimal length of error-correcting data structures for the
Membership problem (where we want to store subsets of size s from a universe of
size n) is closely related to the optimal length of locally decodable codes for
s-bit strings.Comment: 15 pages LaTeX; an abridged version will appear in the Proceedings of
the STACS 2009 conferenc
Scaling language competition in a small island state : graphic verbs in Seychellois Creole and English
One of the sensitive aspects of a small country is the predicament of its language. Seychellois Creole, one of that country`s three official languages and the native language of its Creole population, is asserting its linguistic identity against the globally-established English and French, the other two official languages of the country. How resilient is Seychellois Creole in this language triangle? Are the challenges it faces related to the small number of speakers, citizens of the small country? To what extent, and in what particular way, does Seychellois Creole vulnerable position, as a small language neighboured by two international languages, affect its development? These questions are approached in this paper by means of the comparative analysis of some linguistic parameters of Seychellois Creole and English. Research has been carried out with a group of English and Seychellois Creole verbs conceptualizing the process of graphic representation. The paper focuses on the capacity of the two contrasted languages for concept lexicalisation, patterns of semantic development and syntactic shifting.peer-reviewe
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