18266651
A similarity-based soft clustering algorithm for documents
Document clustering is an important tool for applications such as Web search engines. Clustering documents enables the user to have a good overall view of the information contained in the documents that he has. However, existing algorithms suffer from various aspects, hard clustering algorithms (where each document belongs to exactly one cluster) cannot detect the multiple themes of a document, while soft clustering algorithms (where each document can belong to multiple clusters) are usually inefficient. We propose SISC (similarity-based soft clustering), an efficient soft clustering algorithm based on a given similarity measure. SISC requires only a similarity measure for clustering and uses randomization to help make the clustering efficient. Comparison with existing hard clustering algorithms like K-means and its variants shows that SISC is both effective and efficient.
18594508
An index structure for efficient reverse nearest neighbor queries
The Reverse Nearest Neighbor (RNN) problem is to find all points in a given data set whose nearest neighbor is a given query point. Just like the Nearest Neighbor (NN) queries, the RNN queries appear in many practical situations such as marketing and resource management. Thus, efficient methods for the RNN queries in databases are required. The paper introduces a new index structure, the Rdnn-tree, that answers both RNN and NN queries efficiently. A single index structure is employed for a dynamic database, in contrast to the use of multiple indexes in previous work. This leads to significant savings in dynamically maintaining the index structure. The Rdnn-tree outperforms existing methods in various aspects. Experiments on both synthetic and real world data show that our index structure outperforms previous methods by a significant margin (more than 90% in terms of number of leaf nodes accessed) in RNN queries. It also shows improvement in NN queries over standard techniques. Furthermore, performance in insertion and deletion is significantly enhanced by the ability to combine multiple queries (NN and RNN) in one traversal of the tree. These facts make our index structure extremely preferable in both static and dynamic cases.
17442336
Ordinal association rules for error identification in data sets
A new extension of the Boolean association rules, ordinal association rules, that incorporates ordinal relationships among data items, is introduced. One use for ordinal rules is to identify possible errors in data. A method that finds these rules and identifies potential errors in data is proposed.
46019766
A Study on Textual Entailment
In this paper we study a graph-based approach to the task of textual entailment between a text and hypothesis. The approach takes into account the full lexico-syntactic context of both the text and hypothesis and relies heavily on the concept of subsumption. It starts with mapping the text and hypothesis into graph structures where nodes represent concepts and edges represent lexico-syntactic relations among concepts. Based on a subsumption score between the text-graph and hypothesis-graph an entailment decision is then made. The impact of synonymy on entailment is quantified and discussed. An important advantage of our solution is the ability to customize it so that high-confidence results are obtained
15536346
An Index Structure for Data Mining and Clustering
Abstract. In this paper we present an index structure, called MetricMap, that takes a set of objects and a distance metric and then maps those objects to a k-dimensional space in such a way that the distances among objects are approximately preserved. The index structure is a useful tool for clustering and visualization in data-intensive applications, because it replaces expensive distance calculations by sum-of-square calculations. This can make clustering in large databases with expensive distance metrics practical. We compare the index structure with another data mining index structure, FastMap, recently proposed by Faloutsos and Lin, according to two criteria: relative error and clustering accuracy. For relative error, we show that (i) FastMap gives a lower relative error than MetricMap for Euclidean distances, (ii) MetricMap gives a lower relative error than FastMap for non-Euclidean distances (i.e., general distance metrics), and (iii) combining the two reduces the error yet further. A similar result is obtained when comparing the accuracy of clustering. These results hold for different data sizes. The main qualitative conclusion is that these two index structures capture complementary information about distance metrics and therefore can be used together to great benefit. The net effect is that multi-day computations can be done in minutes.
7539391
Compressed-domain video indexing techniques using DCT and motion vector information in MPEG video
Development of various multimedia applications hinges on the availability of fast and efficient storage, browsing, indexing, and retrieval techniques. Given that video is typically stored efficiently in a compressed format, if we can analyze the compressed representation directly, we can avoid the costly overhead of decompressing and operating at the pixel level. Compressed domain parsing of video has been presented in earlier work where a video clip is divided into shots, subshots, and scenes. In this paper, we describe key frame selection, feature extraction, and indexing and retrieval techniques that are directly applicable to MPEG compressed video. We develop a frame-type independent representation of the various types of frames present in an MPEG video in which al frames can be considered equivalent. Features are derived from the available DCT, macroblock, and motion vector information and mapped to a low-dimensional space where they can be accessed with standard database techniques. The spatial information is used as primary index while the temporal information is used to enhance the robustness of the system during the retrieval process. The techniques presented enable fast archiving, indexing, and retrieval of video. Our operational prototype typically takes a fraction of a second to retrieve similar video scenes from our database, with over 95% success.
7844991
Jitter control in time-triggered systems
The paper addresses the jitter control issue in time-triggered real-time systems where tasks are activated according to time. Our model is based on the temporal distance constrained task model (DCTS). However, many real-time systems have tasks that do not fit the simple assumptions of the DCTS model because tasks may occasionally access shared resources, and certain tasks may arrive irregularly. We address the issues that cause jitters in DCTS. We first review the algorithm developed for DCTS and present an extension for an optimal algorithm. Three jitter issues are then discussed: sharing resources between tasks, handling tasks that have fixed and unchangeable periods, and handling tasks that arrive aperiodically. We present solutions that can prevent jitters, as well as other solutions that may result in minor jitters.
1566772
A General Resource Management Framework for Real-Time Operating Systems
In RED-Linux kernel, a General Scheduling Framework (GSF) has been implemented. Under GSF, different scheduling algorithms can be easily implemented. However GSF only addresses the scheduling of CPU. Other system resources are not considered. In this paper we propose a general resource management framework for various OS resources. When user applications request and consume system resources, they may use uniform APIs although each type of OS resource has its own properties and means to be controlled. In the resource management framework, we also allow the inter-relationship between different types of resources to be defined and managed.
4707602
An initial strategy for comparing proteins at the domain architecture level
MOTIVATION
Ideally, only proteins that exhibit highly similar domain architectures should be compared with one another as homologues or be classified into a single family. By combining three different indices, the Jaccard index, the Goodman-Kruskal gamma function and the domain duplicate index, into a single similarity measure, we propose a method for comparing proteins based on their domain architectures.


RESULTS
Evaluation of the method using the eukaryotic orthologous groups of proteins (KOGs) database indicated that it allows the automatic and efficient comparison of multiple-domain proteins, which are usually refractory to classic approaches based on sequence similarity measures. As a case study, the PDZ and LRR_1 domains are used to demonstrate how proteins containing promiscuous domains can be clearly compared using our method. For the convenience of users, a web server was set up where three different query interfaces were implemented to compare different domain architectures or proteins with domain(s), and to identify the relationships among domain architectures within a given KOG from the Clusters of Orthologous Groups of Proteins database.


CONCLUSION
The approach we propose is suitable for estimating the similarity of domain architectures of proteins, especially those of multidomain proteins.


AVAILABILITY
http://cmb.bnu.edu.cn/pdart/.
206624023
A Class of Rate-Based Real-Time Scheduling Algorithms
This paper investigates a class of rate-based real-time scheduling algorithms based on the idea of general processor sharing (GPS). We extend the GPS framework of Parekh and Gallager (1993) for periodic and sporadic process scheduling and show the optimality of GPS-based scheduling. In particular, we propose the earliest-completion-time GPS (EGPS) scheduling algorithm to simulate the GPS algorithm with much lower run-time overheads. The schedulability of each process is enforced by a guaranteed CPU service rate, independent of the demands of other processes. We provide a theoretical foundation to assign proper CPU service rates to processes to satisfy their individual stringent response time requirements. We also propose a GPS-based scheduling mechanism for jitter control. Finally, the performance of the proposed algorithms is studied using a generic avionics platform example and simulation experiments on jitter control and mixed soft and hard real-time process scheduling.
13951248
A survey on evaluating and realizing IS/IT benefits in Taiwanese b2bec companies
A number of issues have emerged from the analysis of the data collected via a survey conducted in Taiwanese B2BEC companies. The results show relatively high usage of IS/IT investment evaluation and benefits realization methodologies, and yet, these methodologies were generally not used effectively within the responding organizations. Most of these organizations were not yet mature in terms of their IT. However, there was a clear association between level of IT maturity and both wide and effective use of methodologies for IS/IT investment evaluation and benefits management.