7247766
Semantic and Generative Models for Lossy Text Compression
The complementary paradigms of text compression and image compression suggest that there may be potential for applying methods developed for one domain to the other. In image coding, lossy techniques yield compression factors that are vastly superior to those of the best lossless schemes, and we show that this is also the case for text. This paper investigates the resulting tradeoff between subjective quality of the transmission and its compression factor. Two different methods are described, which can be combined into an extremely effective technique that provides far better compression than the present state of the art and yet preserves a reasonable degree of perceived match between the original and received text. The major challenge for lossy text compression is the quantitative evaluation of the quality of this match.
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.
12515579
Supporting serendipitous integration in mobile computing environments
Abstract In the richly networked world of the near future, mobile computing users will be confronted with an ever-expanding array of devices and services accessible in their environments. In such a world, we cannot expect to have available to us specific applications that allow us to accomplish every conceivable combination of devices that we may wish. Instead, we believe that many of our interactions with the network will be characterized by the use of “general purpose” tools that allow us to discover, use, and integrate multiple devices around us. This paper lays out the case for why we believe that so-called “serendipitous integration” is a necessary fact that we will face in mobile computing, and explores a number of design experiments into supporting end user configuration and control of networked environments through general purpose tools. We present an iterative design approach to creating such tools and their user interfaces, discuss our observations about the challenges of designing for such a world, and then explore a number of tools that take differing design approaches to overcoming these challenges. We conclude with a set of reflections on the user experience issues that we believe are inherent in dealing with ad hoc mobile computing in richly networked environments.
7260476
Visual Explorations for the Alexandria Digital Earth Prototype
The Alexandria Digital Earth Prototype project addresses issues of access, browsing, delivery and understanding of georeferenced library items. Two visualization approaches that address these issues in different ways are under development: interfaces between some existing digital earth systems and the digital library, and spatial but nongeoreferenced information spaces. Both the abstract spatial and georeferenced projects are being evaluated for their educational potential in classroom and lectures, in labs and as tools for students to use on their own.
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.
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.
3284353
Point-Based POMDP Algorithms: Improved Analysis and Implementation
Existing complexity bounds for point-based POMDP value iteration algorithms focus either on the curse of dimensionality or the curse of history. We derive a new bound that relies on both and uses the concept of discounted reachability; our conclusions may help guide future algorithm design. We also discuss recent improvements to our (point-based) heuristic search value iteration algorithm. Our new implementation calculates tighter initial bounds, avoids solving linear programs, and makes more effective use of sparsity.