1394805
Using Syntactic Dependency as Local Context to Resolve Word Sense Ambiguity
Most previous corpus-based algorithms disambiguate a word with a classifier trained from previous usages of the same word. Separate classifiers have to be trained for different words. We present an algorithm that uses the same knowledge sources to disambiguate different words. The algorithm does not require a sense-tagged corpus and exploits the fact that two different words are likely to have similar meanings if they occur in identical local contexts.
6409436
Word-for-Word Glossing with Contextually Similar Words
Many corpus-based machine translation systems require parallel corpora. In this paper, we present a word-for-word glossing algorithm that requires only a source language corpus. To gloss a word, we first identify its similar words that occurred in the same context in a large corpus. We then determine the gloss by maximizing the similarity between the set of contextually similar words and the different translations of the word in a bilingual thesaurus.
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.
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.
8110502
Data Management in RFID Applications
Nowadays, RFID applications have attracted a great deal of interest due to their increasing adoptions in supply chain management, logistics and security. They have posed many new challenges to existing underlying database technologies, such as the requirements of supporting big volume data, preserving data transition path and handling new types of queries. In this paper, we propose an efficient method to manage RFID data.We explore and take advantage of the containment relationships in the relational tables in order to support special queries in the RFID applications. The experimental evaluation conducted on an existing RDBMS demonstrates the efficiency of our method.
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.
1196662
A Nearest-Neighbor Method for Resolving PP-Attachment Ambiguity
We present a nearest-neighbor algorithm for resolving prepositional phrase attachment ambiguities. Its performance is significantly higher than previous corpus-based methods for PP-attachment that do not rely on manually constructed knowledge bases. We will also show that the PP-attachment task provides a way to evaluate methods for computing distributional word similarities. Our experiments indicate that the cosine of pointwise mutual information vector is a significantly better similarity measure than several other commonly used similarity measures.
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.
5467372
Organizing and Searching the World Wide Web of Facts - Step One: The One-Million Fact Extraction Challenge
Due to the inherent difficulty of processing noisy text, the potential of the Web as a decentralized repository of human knowledge remains largely untapped during Web search. The access to billions of binary relations among named entities would enable new search paradigms and alternative methods for presenting the search results. A first concrete step towards building large searchable repositories of factual knowledge is to derive such knowledge automatically at large scale from textual documents. Generalized contextual extraction patterns allow for fast iterative progression towards extracting one million facts of a given type (e.g., Person-BornIn-Year) from 100 million Web documents of arbitrary quality. The extraction starts from as few as 10 seed facts, requires no additional input knowledge or annotated text, and emphasizes scale and coverage by avoiding the use of syntactic parsers, named entity recognizers, gazetteers, and similar text processing tools and resources.