5659557
An Information-Theoretic Definition of Similarity
Similarity is an important and widely used concept. Previous definitions of similarity are tied to a particular application or a form of knowledge representation. We present an informationtheoretic definition of similarity that is applicable as long as there is a probabilistic model. We demonstrate how our definition can be used to measure the similarity in a number of different domains.
15110225
Efficient Parsing for Korean and English: A Parameterized Message- Passing Approach
This article presents an efficient, implemented approach to cross-linguistic parsing based on Government Binding (GB) Theory (Chomsky 1986) and followers. One of the drawbacks to alternative GB-based parsing approaches is that they generally adopt a filter-based paradigm. These approaches typically generate all possible candidate structures of the sentence that satisfy X theory, and then subsequently apply filters in order to eliminate those structures that violate GB principles. (See, for example, Abney 1989; Correa 1991; Dorr 1993; Fong 1991.) The current approach provides an alternative to filter-based designs that avoids these difficulties by applying principles to descriptions of structures without actually building the structures themselves. Our approach is similar to that of Lin (1993) in that structure-building is deferred until the descriptions satisfy all principles; however, the current approach differs in that it provides a parameterization mechanism along the lines of Dorr (1994) that allows the system to be ported to languages other than English. We focus particularly on the problem of processing head-final languages such as Korean. We are currently incorporating the parser into a machine translation (MT) system called PRINCITRAN. l In general, parsers of existing principle-based interlingual MT systems are exceedingly inefficient, since they tend to adopt the filter-based paradigm. We combine the benefits of the message-passing paradigm with the benefits of the parameterized approach to build a more efficient, but easily extensible system, that will ultimately be used for MT. The algorithm has been implemented in C++ and successfully tested on well-known, translationally divergent sentences. We present a general framework for parsing by message passing and describe our implementation of GB principles as attribute-value constraints. We then present the parameterization framework, demonstrating the feasibility of handling cross-linguistic variation within the message-passing framework. A technique for automatic precompilation of parameter settings is described. Finally, we compare the efficiency of the
9541345
Principle-Based Parsing without Overgeneration
Overgeneration is the main source of computational complexity in previous principle-based parsers. This paper presents a message passing algorithm for principle-based parsing that avoids the overgeneration problem. This algorithm has been implemented in C++ and successfully tested with example sentences from (van Riemsdijk and Williams, 1986).
183890
A Probabilistic Network of Predicates
Bayesian networks are directed acyclic graphs representing independence relationships among a set of random variables. A random variable can be regarded as a set of exhaustive and mutually exclusive propositions. We argue that there are several drawbacks resulting from the propositional nature and acyclic structure of Bayesian networks. 
 
To remedy these shortcomings, we propose a probabilistic network where nodes represent unary predicates and which may contain directed cycles. The proposed representation allows us to represent domain knowledge in a single static network even though we cannot determine the instantiations of the predicates before hand. The ability to deal with cycles also enables us to handle cyclic causal tendencies and to recognize recursive plans.
6491908
A Dependency-based Method for Evaluating Broad-Coverage Parsers
With the emergence of broad-coverage parsers, quantitative evaluation of parsers becomes increasingly more important. We propose a dependency-based method for evaluating broad-coverage parsers. The method offers several advantages over previous methods that are based on phrase boundaries The error count score. We propose here is not only more intuitively meaningful than other scores, but also more relevant to semantic interpretation. We will also present an algorithm for transforming constituency trees into dependency trees so that the evaluation method is applicable to both dependency and constituency grammars. Finally, we discuss a set of operations for modifying dependency trees that can be used lo eliminate inconsequential differences among different parse trees and allow us to selectively evaluate different aspects of a parser.
15698938
Automatic Retrieval and Clustering of Similar Words
Bootstrapping semantics from text is one of the greatest challenges in natural language learning. We first define a word similarity measure based on the distributional pattern of words. The similarity measure allows us to construct a thesaurus using a parsed corpus. We then present a new evaluation methodology for the automatically constructed thesaurus. The evaluation results show that the thesaurus is significantly closer to WordNet than Roget Thesaurus is.
22202534
Subspace-based active user identification for a collision-free slotted ad hoc network
We propose a novel spreading code scheme, transmitter-receiver-based code, for wireless ad hoc networks. The design facilitates collision resolution using multiuser detection at each node, and is more bandwidth efficient than creating orthogonal channels in time or frequency. A subspace-based receiver structure is introduced, which identifies users of interest, or "active" users, with minimal prior information on the spreading code ensemble. A subspace-based blind multiuser detector can then be implemented to suppress multiaccess interference. The performance of the proposed active user identifier is studied by investigating its false alarm rate P/sub f/ and miss rate P/sub m/. Tradeoffs between P/sub f/ and P/sub m/ are discussed, and a graphical method to determine the threshold value d/sub th/ of the decision statistic used in discriminating between active and inactive channels is introduced.
15442120
Digital City Shanghai: Concepts, Foundations, and Current State
The fastest developing city in China is Shanghai; its annual growth rate (GDP) exceeded 11.9% average in every year from 1992 and GDP per person in 2003 reached 4909 USD. Economists, industries and the government have been considering how to keep Shanghai developing in a sustainable manner. In 1994, the Shanghai Municipal Government put forward the concept of information harbor and set the goal of establishing a series of information infrastructures in the following five years. The Shanghai city informatization project started in 1999, and by the end of 2001 it had spread across Shanghai. At the same time, some applications based on Internet technologies were designed and developed. In the beginning of 2002, based on the current information infrastructures and systems, Shanghai Municipal Government announced the Digital City Shanghai strategy. This chapter will introduce the background of the Digital City Shanghai project, the current state of the information infrastructure in Shanghai, and the concept of system design & user interface. The Digital City Shanghai project will be described in four parts: Spatial Data Infrastructure, City Informatization, Shanghai City Grid, and Shanghai Logistics Information Platform. We will also introduce some research projects. In addition to the strategy, we describe and discuss social perspective and problems.
14056340
An efficient Monte Carlo approach to assessing statistical significance in genomic studies
MOTIVATION
Multiple hypothesis testing is a common problem in genome research, particularly in microarray experiments and genomewide association studies. Failure to account for the effects of multiple comparisons would result in an abundance of false positive results. The Bonferroni correction and Holm's step-down procedure are overly conservative, whereas the permutation test is time-consuming and is restricted to simple problems.


RESULTS
We developed an efficient Monte Carlo approach to approximating the joint distribution of the test statistics along the genome. We then used the Monte Carlo distribution to evaluate the commonly used criteria for error control, such as familywise error rates and positive false discovery rates. This approach is applicable to any data structures and test statistics. Applications to simulated and real data demonstrate that the proposed approach provides accurate error control, and can be substantially more powerful than the Bonferroni and Holm methods, especially when the test statistics are highly correlated.
12969098
An approach to evaluate policy similarity
Recent collaborative applications and enterprises very often need to efficiently integrate their access control policies. An important step in policy integration is to analyze the similarity of policies. Existing approaches to policy similarity analysis are mainly based on logical reasoning and boolean function comparison. Such approaches are computationally expensive and do not scale well for large heterogeneous distributed environments (like Grid computing systems). In this paper, we propose a policy similarity measure as a filter phase for policy similarity analysis. This measure provides a lightweight approach to pre-compile a large amount of policies and only return the most similar policies for further evaluation. In the paper we formally define the measure, by taking into account both the case of categorical attributes and numeric attributes. Detailed algorithms are presented for the similarly computation. Results of our case study demonstrates the efficiency and practical value of our approach.
12904695
Computer-aided kidney segmentation on abdominal CT images
In this paper, an effective model-based approach for computer-aided kidney segmentation of abdominal CT images with anatomic structure consideration is presented. This automatic segmentation system is expected to assist physicians in both clinical diagnosis and educational training. The proposed method is a coarse to fine segmentation approach divided into two stages. First, the candidate kidney region is extracted according to the statistical geometric location of kidney within the abdomen. This approach is applicable to images of different sizes by using the relative distance of the kidney region to the spine. The second stage identifies the kidney by a series of image processing operations. The main elements of the proposed system are: 1) the location of the spine is used as the landmark for coordinate references; 2) elliptic candidate kidney region extraction with progressive positioning on the consecutive CT images; 3) novel directional model for a more reliable kidney region seed point identification; and 4) adaptive region growing controlled by the properties of image homogeneity. In addition, in order to provide different views for the physicians, we have implemented a visualization tool that will automatically show the renal contour through the method of second-order neighborhood edge detection. We considered segmentation of kidney regions from CT scans that contain pathologies in clinical practice. The results of a series of tests on 358 images from 30 patients indicate an average correlation coefficient of up to 88% between automatic and manual segmentation