17501980
Term Graph Model for Text Classification
Most existing text classification methods (and text mining methods at large) are based on representing the documents using the traditional vector space model. We argue that important information, such as the relationship among words, is lost. We propose a term graph model to represent not only the content of a document but also the relationship among the keywords. We demonstrate that the new model enables us to define new similarity functions, such as considering rank correlation based on PageRank-style algorithms, for the classification purpose. Our preliminary results show promising results of our new model.
4018890
Clustering Moving Objects for Spatio-temporal Selectivity Estimation
Many spatio-temporal applications involve managing and querying moving objects. In such an environment, predictive spatio-temporal queries become an important query class to be processed to capture the nature of moving objects. In this paper, we investigated the problem of selectivity estimation for predictive spatio-temporal queries. We propose a novel histogram technique based on a clustering paradigm. To avoid expensive computation costs, we developed linear time heuristics to construct such a histogram. Our performance study indicated that the new techniques improve the accuracy of the existing techniques by one order of magnitude.
1993887
Locating Motifs in Time-Series Data
Finding motifs in time-series is proposed to make clustering of time-series subsequences meaningful, because most existing algorithms of clustering time-series subsequences are reported meaningless in recent studies. The existing motif finding algorithms emphasize the efficiency at the expense of quality, in terms of the number of time-series subsequences in a motif and the total number of motifs found. In this paper, we formalize the problem as a continuous top-k motif balls problem in an m-dimensional space, and propose heuristic approaches that can significantly improve the quality of motifs with reasonable overhead, as shown in our experimental studies.
28636420
Efficient computation of a proximity matching in spatial databases
Abstract Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. In this paper, we investigate a proximity matching problem among clusters and features. The investigation involves proximity relationship measurement between clusters and features. We measure proximity in an average fashion to address possible non-uniform data distribution in a cluster. An efficient algorithm is proposed and evaluated to solve the problem. The algorithm applies a standard multi-step paradigm in combining with novel lower and upper proximity bounds. The algorithm is implemented in several different modes. Our experiment results not only give a comparison among them but also illustrate the efficiency of the algorithm.
2460253
Approximate processing of massive continuous quantile queries over high-speed data streams
Quantile computation has many applications including data mining and financial data analysis. It has been shown that an /spl epsi/-approximate summary can be maintained so that, given a quantile query (/spl phi/,/spl epsi/), the data item at rank /spl lceil//spl phi/N/spl rceil/ may be approximately obtained within the rank error precision /spl epsi/N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different /spl phi/ and /spl epsi/ poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.
1773095
Delay Optimization in Quorum Consensus
Abstract
 The management of replicated data in distributed database systems is a classic problem with great
practical importance. Quorum consensus is one of the popular methods, combined with eager replication, for
managing replicated data. In this paper we investigate the problems of delay-optimal quorum consensus.
Firstly, we show that the problem of minimizing the total delay (or mean delay) restricted to a ring can be
solved in a constant time in contrast to the existing approximation results. Secondly, we show that the problem
of minimizing the total delay (or mean delay) is NP-hard. Thirdly, we present an approximate algorithm with
an approximate ratio 2; and the approximate algorithm can guarantee the exact solutions for some specific
network topology, such as trees and meshes. Finally, we present an improvement on the existing algorithm
to solve the problem of minimizing the maximal delay; this reduces the time complexity from O(n3 log n) to
O(n3) where n is the number of nodes.
8597703
Evaluation and Application of Recognition Confidence in OCR
Recognition confidence plays an important role in the selection of rejection threshold and the combination of multiple classifiers. In this paper, we first present a systematic theory on classifier's confidence, which includes the definition, the concept of generalized confidence, optimal rejection theorem and the relationship between confidence value and recognition rate. Then we propose a method for the evaluation of recognition confidence. The theory and method are strongly supported by the practice in handwritten numeral recognition and off-line handwritten Chinese character recognition.
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.
2535403
Visualization for the document space
An information retrieval frame work that promotes graphical displays, and that will make documents in the computer visualizable to the searcher, is described. As examples of such graphical displays, two simulation results of using a Kohonen feature map to generate map displays for information retrieval are presented and discussed. The map displays are a mapping from a high-dimensional document space to a two-dimensional space. They show document relationships by various visual cues, such as dots, links, clusters, and areas, as well as their measurement and spatial arrangement. Using the map displays as an interface for document retrieval systems, the user is provided with richer visual information to support browsing and searching.<<ETX>>
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.
1998178
A Hierarchical Approach to Internet Distance Prediction
Internet distance prediction gives pair-wise latency information with limited measurements. Recent studies have revealed that the quality of existing prediction mechanisms from the application perspective is short of satisfactory. In this paper, we explore the root causes and remedies for this problem. Our experience with different landmark selection schemes shows that although selecting nearby landmarks can increase the prediction accuracy for short distances, it can cause the prediction accuracy for longer distances to degrade. Such uneven prediction quality significantly impacts application performance. Instead of trying to select the landmark nodes in some "intelligent" fashion, we propose a hierarchical prediction approach with straightforward landmark selection. Hierarchical prediction utilizes multiple coordinate sets at multiple distance scales, with the "right" scale being chosen for prediction each time. Experiments with Internet measurement datasets show that this hierarchical approach is extremely promising for increasing the accuracy of network distance prediction.