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).
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.
8724659
Estimating device availability in pervasive peer-to-peer environment
In pervasive computing environments, devices often communicate in a peer-to-peer manner, either for passing messages or collaboratively running applications. For any particular device, information about the availability of other devices can lead to more efficient communication and better execution of distributed tasks. For example, a device can distribute computation tasks to reliable devices and temporarily avoid unreliable ones. Since there usually is not a central server to coordinate or monitor the communication in such environment, a key technical challenge is for each individual device to predict the availability of other devices. In this paper, we describe some methods for predicting the availability of other devices using historic availability data of those devices obtained in routine usage. In this scheme, each device separately maintains data about the past communication with the other devices, and predicts current and future availability using the statistics of those data. These methods do not require any centralized monitoring or extra probing, and thus have very low computation cost. These characteristics make them suitable for small devices in a peer-to-peer environment.
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.
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.
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.
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.
18316669
On Linear-Spline Based Histograms
Approximation is a very effective paradigm to speed up query processing in large databases. One popular approximation mechanism is data size reduction. There are three reduction techniques: sampling, histograms, and wavelets. Histogram techniques are supported by many commercial database systems, and have been shown very effective for approximately processing aggregation queries. In this paper, we will investigate the optimal models for building histograms based on linear spline techniques. We will firstly propose several novel models. Secondly, we will present efficient algorithms to achieve these proposed optimal models. Our experiment results showed that our new techniques can greatly improve the approximation accuracy comparing to the existing techniques.
503545
Privacy-preserving clustering with distributed EM mixture modeling
Privacy and security considerations can prevent sharing of data, derailing data mining projects. Distributed knowledge discovery can alleviate this problem. We present a technique that uses EM mixture modeling to perform clustering on distributed data. This method controls data sharing, preventing disclosure of individual data items or any results that can be traced to an individual site.
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.
783838
Practical Indexing XML Document for Twig Query
Answering structural queries of XML with index is an important approach of efficient XML query processing. Among existing structural indexes for XML data, F&B index is the smallest index that can answer all branching queries. However, an F&B index for less regular XML data often contains a large number of index nodes, and hence a large amount of main memory. If the F&B index cannot be accommodated in the available memory, its performance will degrade significantly. This issue has practically limited wider application of the F&B index. 
 
In this paper, we propose a disk organization method for the F&B index which shift part of the leave nodes in the F&B index to the disk and organize them judiciously on the disk. Our method is based on the observation that the majority of the nodes in a F&B index is often the leaf nodes, yet their access frequencies are not high. 
 
We select some leaves to output to disk. With the support of reasonable storage structure in main memory and in disk, we design efficient query processing method). We further optimize the design of the F&B index based on the query workload. Experimental results verified the effectiveness of our proposed approach.