16631800
Fast convergence with a greedy tag-phrase dictionary
Lexical categories have been shown to assist in giving good compression results when incorporated into context models. This paper describes a greedy dictionary-based model that maintains a dictionary of tag-phrases, along with separate lexicons for each unique tag. The text is tagged with part-of-speech (POS) labels and then given to the encoder, which uses the tags to construct the phrase dictionary in a manner similar to LZ78. The output is a sequence of arithmetically encoded phrase number coupled with the information needed to match the correct word with each tag in the phrase. Each unique word (defined as each novel word/tag pair) is transmitted once when it is first encountered, then retained in the appropriate dictionary and thereafter arithmetically encoded according to the empirical distribution for that dictionary whenever the word is encountered. We present results from some empirical tests showing that this "tag-phrase dictionary" technique achieves nearly identical compression as that obtainable using PPM, an explicit-context model. This goes against the widely held view that greedy dictionary schemes require much larger samples of text before they can compete with statistical context methods. Some interesting theoretical issues pertaining to text compression in general are implied, and these are also discussed.
11264916
Learning language using genetic algorithms
Strict pattern-based methods of grammar induction are often frustrated by the apparently inexhaustible variety of novel word combinations in large corpora. Statistical methods offer a possible solution by allowing frequent well-formed expressions to overwhelm the infrequent ungrammatical ones. They also have the desirable property of being able to construct robust grammars from positive instances alone. Unfortunately, the “zero-frequency” problem entails assigning a small probability to all possible word patterns, thus ungrammatical n-grams become as probable as unseen grammatical ones. Further, such grammars are unable to take advantage of inherent lexical properties that should allow infrequent words to inherit the syntactic properties of the class to which they belong.
35525617
Eye movements and pupil dilation during event perception
Human observers segment ongoing activities into events that are reliable across observers [Newtson and Engquist 1976]. Segments can be small ("fine") or large ("coarse") with clusters of fine-grained segments relating hierarchically to coarse segments. Segmentation behaviour occurs even without instruction indicated by neural activity in the Medial Temporal complex (MT+)and Frontal Eye Field (FEF). Similar activation is observed during active segmentation [Zacks et al. 2001]. These two brain regions are known to be active during the processing of visual motion (MT+) and guiding saccadic eye movements (FEF). This, along with behavioural evidence [Zacks 2004], indicates that visual motion may play an important role in identifying events.
10464813
Building Semantic Tools for Concept-based Learning Spaces: Knowledge Bases of Strongly-Structured Models for Scientific Concepts in Advanced Digital Libraries
Applying conventional principles of knowledge organization, representation, and other semantic tools, we have constructed a model for scientific concepts and employed knowledge bases and visualization tools to represent knowledge concerning scientific concepts. Strongly-structured models, such as the integration of a taxonomy (or thesaurus) with metadata (or attribute-value pairs) and domain-specific markup languages, as well as specialized models for learning scientific concepts, focus on such attributes as objective representations, operational semantics, use, and interrelationships of concepts. All of these play important roles in constructing representations of knowledge in most domains of science. Instructional activities for undergraduate teaching and learning are greatly facilitated with the use of such integrated semantic tools.
9064289
Automatic Pattern Embedding in Protein Structure Models
This article describes an implementation of a set of rules for automatically embedding a minimal functional sequence pattern in a structural hidden Markov model. The final product is a library of wide ranging fold models with encoded information about the functional families.
2795329
User interfaces when and where they are needed: an infrastructure for recombinant computing
Users in ubiquitous computing environments need to be able to make serendipitous use of resources that they did not anticipate and of which they have no prior knowledge. The Speakeasy recombinant computing framework is designed to support such ad hoc use of resources on a network. In addition to other facilities, the framework provides an infrastructure through which device and service user interfaces can be made available to users on multiple platforms. The framework enables UIs to be provided for connections involving multiple entities, allows these UIs to be delivered asynchronously, and allows them to be injected by any party participating in a connection.
17905377
FLANNEL: adding computation to electronic mail during transmission
In this paper, we describe FLANNEL, an architecture for adding computational capabilities to email. FLANNEL allows email to be modified by an application while in transit between sender and receiver. This modification is done without modification to the endpoints---mail clients---at either end. This paper also describes interaction techniques that we have developed to allow senders of email to quickly and easily select computations to be performed by FLANNEL. Through, our experience, we explain the properties that applications must have in order to be successful in the context of FLANNEL.