This paper describes a text chunking system based on a generalization of the Winnow algorithm. We propose a general statistical model for text chunking which we then convert into a classification problem. We argue that the Winnow family of algorithms is particularly suitable for solving classification problems arising from NLP applications, due to their robustness to irrelevant features. Howeve...

In this paper we discuss a rule-based approach to chunking implemented using the LT-XML2 and LT-TTT2 tools. We describe the tools and the pipeline and grammars that have been developed for the task of chunking. We show that our rule-based approach is easy to adapt to different chunking styles and that the mark-up of further linguistic information such as nominal and verbal heads can be added to...

Responding to individual key-specific stimuli in entirely unfamiliar keying sequences is said to involve a reaction mode. With practice, short keying sequences can be executed in the chunking mode. This is indicated by the first stimulus sufficing for rapid execution of the entire sequence. The present study explored whether an associative mode develops also in participants who practice short k...

Sequence data structures, i.e., data structures that provide operations on an ordered set of items, are heavily used by many applications. For sequence data structures to be efficient in practice, it is important to amortize expensive data-structural operations by chunking a relatively small, constant number of items together, and representing them by using a simple but fast (at least in the sm...

Chunks have long been proposed as a basic organizational unit for human memory. More recently chunks have been used to model human learning on simple perceptual-motor skills. In this paper we describe recent progress in extending chunking to be a general learning mechanism by implementing it within a general problem solver. Using the Soar problem-solving architecture, we take significant steps ...

Most existing systems solved the phrase chunking task with the sequence labeling approaches, in which the chunk candidates cannot be treated as a whole during parsing process so that the chunk-level features cannot be exploited in a natural way. In this paper, we formulate phrase chunking as a joint segmentation and labeling task. We propose an efficient dynamic programming algorithm with pruni...

Dissemination systems are used to route information received from many publishers individually to multiple subscribers. The core of a dissemination system consists of an efficient filtering engine deciding what part of an incoming message goes to which recipient. Within this paper we are proposing a chunking framework of XML documents to speed up the filtering process for a set of registered su...

We present a method for Noun Phrase chunking in Hebrew. We show that the traditional definition of base-NPs as nonrecursive noun phrases does not apply in Hebrew, and propose an alternative definition of Simple NPs. We review syntactic properties of Hebrew related to noun phrases, which indicate that the task of Hebrew SimpleNP chunking is harder than base-NP chunking in English. As a confirmat...

Story statements cluster into episodes, so we expected the memory representations of statements to cluster into separate episode chunks in memory. Experiment 1 confirmed this chunking idea by showing that the recall of episode actions depends on the length of that episode, but not on the lengths of other episodes. Specifically, adding more actions to an episode increased recall of the original ...

It is generally believed that transfer decreases with expertise. Several existing models explain this by different forms of chunking, but each is specific to a particular task. The new PRIM theory of cognitive skill transfer allows a more generalized approach to study this phenomenon. To demonstrate this, I present a model of the Frensch (1991) experiment of transfer that explains why a short t...