40938143
Automating the analysis of voting systems
Voting is a well-known technique to combine the decisions of peer experts. It is used in fault tolerant applications to mask errors from one or more experts using n-modular redundancy (NMR) and n-version programming. Voting strategies include: majority, weighted voting, plurality; instance runoff voting, threshold voting, and the more general weighted k-out-of-n systems. Before selecting a voting schema for a particular application, we have to understand the various tradeoffs and parameters and how they impact the correctness, reliability, and confidence in the final decision made by a voting system. In this paper, we propose an enumerated simulation approach to automate the behavior analysis of voting schemas with application to majority and plurality voting. We conduct synthetic studies using a simulator that we develop to analyze results from each expert, apply a voting mechanism, and analyze the voting results. The simulator builds a decision tree and uses a depth-first traversal algorithm to obtain the system reliability among other factors. We define and study the following behaviors: 1) the probability of reaching a consensus, "Pc"; 2) reliability of the voting system, "R"; 3) certainly index, "T"; and 4) the confidence index, "C". The parameters controlling the analysis are the number of participating experts, the number of possible output symbols that can be produced by an expert, the probability distribution of each expert's output, and the voting schema. The paper presents an enumerated simulation approach for analyzing voting systems which can be used when the use of theoretical models are challenged by dependencies between experts or uncommon probability distributions of the expert's output.
5163377
Handwritten numeral recognition using MFNN based multiexpert combination strategy
A novel unconstrained numeral recognition system using an MFNN (multilayered feedforward neural net)-based multi-expert combination strategy is proposed. Taking advantage of every method's confidence value as well as its output label, this strategy can improve the system's performance significantly with as few as two experts. Another novel feature of the system is that the multi-expert combination problem is converted into a new classification problem, and then the MFNNs are used to handle the combination adaptively. The proposed system has achieved promising results on the NIST database.
15560852
Performance analysis of pattern classifier combination by plurality voting
Plurality voting is widely used in pattern recognition. However, there is little theoretical analysis of plurality voting. In this paper, we attempt to explore the rationale behind plurality voting. The recognition/error/rejection rates of plurality voting are compared with those of majority voting under different conditions. It is demonstrated that plurality voting is more efficient in achieving the tradeoff between rejection rate and error rate. We also discuss some practical problems when applying plurality voting to real-world applications.
2250003
ICDAR 2003 robust reading competitions: entries, results, and future directions
Abstract.This paper describes the robust reading competitions for ICDAR 2003. With the rapid growth in research over the last few years on recognizing text in natural scenes, there is an urgent need to establish some common benchmark datasets and gain a clear understanding of the current state of the art. We use the term ‘robust reading’ to refer to text images that are beyond the capabilities of current commercial OCR packages. We chose to break down the robust reading problem into three subproblems and run competitions for each stage, and also a competition for the best overall system. The subproblems we chose were text locating, character recognition and word recognition. By breaking down the problem in this way, we hoped to gain a better understanding of the state of the art in each of the subproblems. Furthermore, our methodology involved storing detailed results of applying each algorithm to each image in the datasets, allowing researchers to study in depth the strengths and weaknesses of each algorithm. The text-locating contest was the only one to have any entries. We give a brief description of each entry and present the results of this contest, showing cases where the leading entries succeed and fail. We also describe an algorithm for combining the outputs of the individual text locators and show how the combination scheme improves on any of the individual systems.
26474180
Adaptive confidence transform based classifier combination for Chinese character recognition
Abstract Classifier combination is an effective way to improve recognition performance. However, in Chinese character recognition the extremely large number of categories results in several difficulties for the combination. In order to overcome these difficulties a novel combination method is presented in this paper. It consists of three main components: adaptive confidence transform (ACT), consensus theoretic combination and reliability based speedup scheme. ACT, which can estimate a posteriori probabilities from raw measurement values, is the focus of this paper. Experimental results show a significant reduction of error rates in both printed (PCCR) and handwritten Chinese character recognition (HCCR).
8341476
Active document layout synthesis
Document layout analysis has been researched for many years. However, there is little work on the reverse of document layout analysis: document layout synthesis, whose goal is to generate logically correct and aesthetically appealing layout given the text/image contents and the flexible layout template. This paper introduces a new automatic document layout synthesis method, which can actively pursue the optimal text block height-width tradeoff simultaneously with the block position adjustment. The key idea is to use a cluster of linear functions to approximate the nonlinear height-width curve. Then two-pass simplex algorithm is used to solve the layout synthesis problem. This method has a wide range of applications, such as variable data printing (VDP), automatic table formatting, and automating document layout ground truth generation.
6238577
Labeling Scheme and Structural Joins for Graph-Structured XML Data
When XML documents are modeled as graphs, many challenging research issues arise. In particular, query processing for graph-structured XML data brings new challenges because traditional structural join methods cannot be directly applied. In this paper, we propose a labeling scheme for graph-structured XML data. With this labeling scheme, the reachability relationship of two nodes can be judged efficiently without accessing other nodes. Based on this labeling scheme, we design efficient structural join algorithms to evaluate reachability queries. Experiments show that our algorithms have high efficiency and good scalability.
7595419
Efficient Computation of k-Medians over Data Streams Under Memory Constraints
In this paper, we study the problem of efficiently computing k-medians over high-dimensional and high speed data streams. The focus of this paper is on the issue of minimizing CPU time to handle high speed data streams on top of the requirements of high accuracy and small memory. Our work is motivated by the following observation: the existing algorithms have similar approximation behaviors in practice, even though they make noticeably different worst case theoretical guarantees. The underlying reason is that in order to achieve high approximation level with the smallest possible memory, they need rather complex techniques to maintain a sketch, along time dimension, by using some existing off-line clustering algorithms. Those clustering algorithms cannot guarantee the optimal clustering result over data segments in a data stream but accumulate errors over segments, which makes most algorithms behave the same in terms of approximation level, in practice. We propose a new grid-based approach which divides the entire data set into cells (not along time dimension). We can achieve high approximation level based on a novel concept called (1−∊)-dominant. We further extend the method to the data stream context, by leveraging a density-based heuristic and frequent item mining techniques over data streams. We only need to apply an existing clustering once to computing k-medians, on demand, which reduces CPU time significantly. We conducted extensive experimental studies, and show that our approaches outperform other well-known approaches.
16928019
Map Displays for Information Retrieval
The focus of this article is to develop a map display for to stack in the dark, without knowing what stacks that information retrieval. Through an examination of relawe have walked through. We can get a few books each tionships among visual displays, information retrieval, time and walk out of the library to see if the book we and browsing, advantages of visual displays for informaare searching for is among them. If not, we have to walk tion retrieval are characterized as (1) the ability to conin again, based on our knowledge and our previous experivey a large amount of information in a limited space, (2) the potential to reveal semantic relationships of terms ence, to a location where we hope the book would be. In and documents, and (3) the facilitation of browsing and this situation, success in finding a book greatly depends perceptual inferences on retrieval interfaces. These adon whether we can walk to the right place in the dark (to vantages are further demonstrated through a map disgenerate a good query), and whether we know how to play generated by a neural network’s self-organizing aladjust our locations until we get to the right place (to gorithm. The map display detects complex relationships among given documents, and reveals the relationships modify queries interactively) . through a spatial arrangement of terms abstracted from Can we turn on the light for such a library? Can we the documents. The map display also provides interdevelop some visible cues in our retrieval systems so that active tools to allow the user to interact with the underlywe can use our perception for information seeking in ing information. Examples of the map displays show that the digital environment? Answers to these questions may such map displays can be used both as an overview tool and an access or exploration tool, and the map displays reside in the recent advance of information technology. will likely increase the amount of information that the ‘‘Information processing has been evolving from numeriuser is willing to browse. cal computation to character handling, and now to visual information processing’’ (Kunii, 1989). As a result, visualization will become ‘‘the second computer revolution’’ Introduction (Friedhoff & Benzon, 1989). Computers are expected to be used to reveal associations and properties of electronic The world in which we live is a visual world. We look, information to allow people to use their visual capabilities we see, and we find things. Even for written information, for information seeking (Veith, 1988). we expect to see it on tangible media stored in visible locations. We have developed a whole set of perception This article discusses using some mapping techniques and association techniques to get what we need from the to create visual displays for textual information stored in environment. However, when we search information by the computer. The focus of the article is on the developcomputer, all the things, information, media, locations, ment of a map display for information retrieval. The map as well as their relationships, become invisible; all the display attempts to show both contents and semantic clues for visual perceptions and associations disappear. structures of a document space by mapping major conWe heavily rely on our competence to generate queries cepts and documents of a document space to a two-dimenand the computer’s ability to match the queries with inforsional map. It preserves, as faithfully as possible, documation stored in the computer. At best, when interaction ment semantic relationships and reveals these relationis involved, we can modify queries based on the retrieved ships through various visual components of the display. results of a previous query. This is like searching books By communicating a spatial metaphor to the user and in a library without light. We can walk around from stack making information in a document space graphically visible, the map display provides a visual guide to help the user perceive contents and structures of the document Received May 26, 1995; revised December 18, 1995; accepted Decemspace. ber 18, 1995. In the following, relationships among information retrieval, browsing, and visual displays are discussed first, q 1997 John Wiley & Sons, Inc.
32681772
Visual MeSH
Visual MeSH is a graphical interface developed to interact with real world databases such as the National Library of Medicine’s MetaThesaurus and MEDLINE. Visual MeSH makes it easy for the user to browse complex relationships through visual representation of thesaurus structures. It helps the user to select controlled vocabulary terms for online searching in the click-andchoose environment.
7052862
Impact of the Inaccuracy of Distance Prediction Algorithms on Internet Applications - an Analytical and Comparative Study
Distance prediction algorithms use O(N) round trip time (RTT) measurements to predict the N2 RTTs among N nodes. Distance prediction can be applied to improve the performance of a wide variety of Internet applications: for instance, to guide the selection of a download server from multiple replicas, or to guide the construction of overlay networks or multicast trees. Although the accuracy of existing prediction algorithms has been extensively compared using the relative prediction error metric, their impact on applications has not been systematically studied. In this paper, we consider distance prediction algorithms from an application's perspective to answer the following questions: (1) Are existing prediction algorithms adequate for the applications? (2) Is there a significant performance difference between the different prediction algorithms, and which is the best from the application perspective? (3) How does the prediction error propagate to affect the user perceived application performance? (4) How can we address the fundamental limitation (i.e., inaccuracy) of distance prediction algorithms? We systematically experiment with three types of representative applications (overlay multicast, server selection, and overlay construction), three distance prediction algorithms (GNP, IDES, and the triangulated heuristic), and three real-world distance datasets (King, PlanetLab, and AMP). We find that, although using prediction can improve the performance of these applications, the achieved performance can be dramatically worse than the optimal case where the real distances are known. We formulate statistical models to explain this performance gap. In addition, we explore various techniques to improve the prediction accuracy and the performance of prediction-based applications. We find that selectively conducting a small number of measurements based on prediction-based screening is most effective.