We address the problems of pattern matching and approximate pattern matching in the sketching model. We show that it is impossible to compress the text into a small sketch and use only the sketch to decide whether a given pattern occurs in the text. We also prove a sketch size lower bound for approximate pattern matching, and show it is tight up to a logarithmic factor.

Consistent with the ultimate goals of AGI, we can expect that deductive consequences of large and grammatically varied text bases would not be generated by sequential application of inference rules but would instead be recognized in a single massively parallel pattern matching operation on their semantic structures which executes near instantaneously. We describe an approach to realizing such a...

The problem of pattern matching with rotation is that of 2nding all occurrences of a twodimensional pattern in a text, in all possible rotations. We prove an upper and lower bound on the number of such di4erent possible rotated patterns. Subsequently, given an m × m array (pattern) and an n × n array (text) over some 2nite alphabet , we present a new method yielding an O(nm) time algorithm for ...

1. Introduction In an earlier report [1], a model for string pattern matching in the style of SNOBOL4 was developed using Icon. That report showed how most of the pattern-matching mechanism of SNOBOL4 could be translated into Icon and, in effect, provided a model for implementing pattern matching in the style of SNOBOL4.

In this paper, we study the pattern matching problem in given intervals. Depending on whether the intervals are given a priori for pre-processing, or during the query along with the pattern or, even in both cases, we develop solutions for different variants of this problem. In particular, we present efficient indexing schemes for each of the above variants of the problem.

This paper describes a novel approach to inducing lexico-structural transfer rules from parsed bi-texts using syntactic pattern matching, statistical cooccurrence and error-driven filtering. We present initial evaluation results and discuss future directions.

We introduce a novel method for embedding and detecting a chaotic watermark in the digital spatial domain of color facial images, based on localizing salient facial features. These features define a certain area on which the watermark is embedded and detected. An assessment of the watermarking robustness is done experimentally, by testing resistance to several attacks, such as compression, filt...