ppxscal/embedding_network huggingface dataset:
The use of tree-based data structure in association mining
Authors: Yu Li
Venue:  (2005)

Data Mining is the process of discovering valuable information from large databases. One popular sub-field of data mining is the area of association mining that studies algorithms capable of discovering frequently co-occurring groups of items in transaction databases. Answering targeted query refers to constrain the search to those association rules that contain certain user-specified items. One recent approach proposed a mechanism that converts the database into a data structure called an itemset tree (IT-tree) that facilitates speedy processing of such queries. This dissertation addresses several research questions related to the IT-tree framework. The main goal is to improve IT-tree approach for the need of association mining. First, we extend the IT-tree to general query answering rectifying its major deficiency. The theoretical analysis and experimental results show that proposed IT-Mining algorithm is very efficient and scales roughly linear with the size of the database. It outperforms another tree-based algorithm, DepthProject, for mining long frequent itemsets with high pair-wise overlaps. Second, we propose TF-Mining algorithm to achieve significant reduction in processing time for answering targeted queries. TF-Mining runs faster than the original methods by two orders of magnitude. Third, we compare the IT-tree approach to similar tree-structure approaches, [AAP1999] and [HPY2000]. We introduce targeted query concept into these two approaches by proposing AAP-QueriedMining and FP-QueriedMining algorithms respectively. Experimental results indicate that IT-tree has distinct advantages when querying with variant minimum support while the other two are better when queried minimum support is fixed. Fourth, we explore the effect of pruning heuristics designed for further speeding up query processing. Our research show that as long as the user is interested only in itemsets with very low supports, the size of the tree and the costs of query processing can be significantly reduced at the small price of missing acceptable percentage of frequent itemsets. Finally we extend the IT-tree paradigm to another type of specialized query, item constraints. The proposed IC-Mining is very efficient and scalable with the size of the database. The performance analysis demonstrates that IC-Mining would outperform another similar approach, Direct algorithm, in very large databases.
Using Information-Theoretic Measures to Assess Association Rule Interestingness
Authors: Julien Blanchard, Fabrice Guillet, Regis Gras, Henri Briand
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

Assessing rules with interestingness measures is the cornerstone of successful applications of association rule discovery. However, there exists no information-theoretic measure which is adapted to the semantics of association rules. In this article, we present the Directed Information Ratio (DIR), a new rule interestingness measure which is based on information theory. DIR is specially designed for association rules, and in particular it differentiates two opposite rules a → b and a → \mathop b\limits^ - . Moreover, to our knowledge, DIR is the only rule interestingness measure which rejects both independence and (what we call) equilibrium, i.e. it discards both the rules whose antecedent and consequent are negatively correlated, and the rules which have more counter-examples than examples. Experimental studies show that DIR is a very filtering measure, which is useful for association rule post-processing.
Keyboard acoustic emanations revisited
Authors: Li Zhuang, Feng Zhou, J. D. Tygar
Venue: Proceedings of the 12th ACM conference on Computer and communications security (2005)

We examine the problem of keyboard acoustic emanations. We present a novel attack taking as input a 10-minute sound recording of a user typing English text using a keyboard, and then recovering up to 96% of typed characters. There is no need for a labeled training recording. Moreover the recognizer bootstrapped this way can even recognize random text such as passwords: In our experiments, 90% of 5-character random passwords using only letters can be generated in fewer than 20 attempts by an adversary; 80% of 10-character passwords can be generated in fewer than 75 attempts. Our attack uses the statistical constraints of the underlying content, English language, to reconstruct text from sound recordings without any labeled training data. The attack uses a combination of standard machine learning and speech recognition techniques, including cepstrum features, Hidden Markov Models, linear classification, and feedback-based incremental learning.
Hybrid Custom Instruction and Co-Processor Synthesis Methodology for Extensible Processors
Authors: Fei Sun, Srivaths Ravi, Anand Raghunathan, Niraj K. Jha
Venue: Proceedings of the 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design (2006)

Classical hardware/software partitioning techniques, recent advances in application-specific instruction set architecture (ISA) design tools, etc., provide avenues to address the individual problems of co-processor generation and custom instruction addition for extensible processors. However, we argue that there is a need for hybrid synthesis techniques by demonstrating that a combination of custom instructions and co-processors is often the better solution in many applications. We propose a systematic methodology that builds on basic observations and trade-offs associated with co-processors and custom instructions: co-processors are good for performing coarse-grained tasks that require minimal intervention or support from the processor, while custom instructions are efficient solutions for fine-grained tasks that are best integrated into a processor's pipeline. We have developed a hierarchical synthesis flow that incorporates a muti-objective evolutionary algorithm in order to handle diverse design dimensions such as area, performance. We have implemented the proposed methodology in the context of a commercial extensible processor based platform (XtensaTM from Tensilica). Our design flow incorporates a commercial behavioral synthesis tool and an automatic custom instruction generation engine. Our experiments with several applications show that simultaneous custom instruction and co-processor synthesis can achieve significantly better area/performance trade-offs than using only one of them.
Learning basic block scheduling heuristics from optimal data
Authors: Tyrel Russell, Abid M. Malik, Michael Chase, Peter van Beek
Venue: Proceedings of the 2005 conference of the Centre for Advanced Studies on Collaborative research (2005)

Instruction scheduling is an important step for improving the performance of object code produced by a compiler. The basic block instruction scheduling problem is to find a minimum length schedule for a basic block-a straight-line sequence of code with a single entry point and a single exit point-subject to precedence, latency, and resource constraints. Solving the problem exactly is known to be difficult, and most compilers use a greedy list scheduling algorithm coupled with a heuristic. The heuristic is usually hand-crafted, a potentially time-consuming process. In contrast, we present a study on automatically learning good heuristics using techniques from machine learning. In our study, a recently proposed optimal basic block scheduler was used to generate the machine learning training data. A decision tree learning algorithm was then used to induce a simple heuristic from the training data. The automatically constructed decision tree heuristic was compared against a popular criticalpath heuristic on the SPEC 2000 benchmarks. On this benchmark suite, the decision tree heuristic reduced the number of basic blocks that were not optimally scheduled by up to 55% compared to the critical-path heuristic, and gave improved performance guarantees in terms of the worst-case factor from optimality.
Text Locating Competition Results
Authors: Simon M. Lucas
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

This paper describes the results of the ICDAR 2005 competition for locating text in camera captured scenes. For this we used the same data as the ICDAR 2003 competition, which has been kept private until now. This allows a direct comparison with the 2003 entries. The main result is that the leading 2005 entry has improved significantly on the leading 2003 entry, with an increase in average f-score from 0.5 to 0.62, where the f-score is the same adapted information retrieval measure used for the 2003 competition. The paper also discusses the web-based deployment and evaluation of text locating systems, and one of the leading entries has now been deployed in this way. This mode of usage could lead to more complete and more immediate knowledge of the strengths and weaknesses of each newly developed system.
SmartTiles: Mobility and Wireless Programmability in Children's Construction and Crafts
Authors: Nwanua Elumeze, Michael Eisenberg
Venue: Proceedings of the IEEE International Workshop on Wireless and Mobile Technologies in Education (2005)

This paper presents a working prototype of a mobile, programmable set of construction kit elements for children. SmartTiles are small, lightweight, independently programmable tile objects that can be combined to cover various sorts of planar surfaces; each touch-sensitive tile contains its own computer and LED, and communicates with its neighboring tiles when placed on an appropriate background material. Collectively, the tiles enact usercustomizable cellular automaton programs and thus display complex and fascinating dynamical patterns of light. In this paper, we discuss the implementation of SmartTiles and explore their potential use as an instance of mobile computation for children. We also discuss the way in which the tiles can be programmed wirelessly via a PDA interface, and discuss the implications of this sort of programming for educational computing more generally.
Detection of eating and drinking arm gestures using inertial body-worn sensors
Authors: Oliver Amft, Holger Junker, Gerhard Troster
Venue: Proceedings of the Ninth IEEE International Symposium on Wearable Computers (2005)

We propose a two-stage recognition system for detecting arm gestures related to human meal intake. Information retrieved from such a system can be used for automatic dietary monitoring in the domain of behavioural medicine. We demonstrate that arm gestures can be clustered and detected using inertial sensors. To validate our method, experimental results including 384 gestures from two subjects are presented. Using isolated discrimination based on HMMs an accuracy of 94% can be achieved. When spotting the gestures in continous movement data, an accuracy of up to 87% is reached.
Recognition of Printed and Handwritten Tamil Characters Using Fuzzy Approach
Authors: R. M. Suresh, L. Ganesan
Venue: Proceedings of the Sixth International Conference on Computational Intelligence and Multimedia Applications (2005)

The theory of fuzzy set provides an approximate but effective means of describing the behavior of ill-defined systems. Patterns of human origin like handwritten characters are to some extent found to be fuzzy in nature. It is decided to use fuzzy conceptual approach effectively in this paper. In fact, in this paper, we attempt to use the fuzzy concept on handwritten Numerals and Tamil characters to classify them as one among the prototype characters using a feature called distance from the frame and a suitable membership function. The unknown and prototype characters are preprocessed and considered for recognition. The algorithm is tested for about 250 samples for numerals and seven chosen Tamil characters and the success rate obtained varies from 76% to 94%.
A BLAST Service Built on Data Indexed Overlay Network
Authors: Chen Wang, Bassam A. Alqaralleh, Bing Bing Zhou, Michael Till, Albert Y. Zomaya
Venue: Proceedings of the First International Conference on e-Science and Grid Computing (2005)

Most of bioinformatics data distributed on the Internet is organized in an unstructured manner, which makes it hard to construct applications that need to integrate them. In this paper, we proposed an XML schema based data indexing mechanism to integrate sequence databases stored in a DHT overlay network. The construction of large-scale distributed applications therefore can be greatly simplified with the support of structured distributed data. We present a system that can seamlessly integrate sequence databases and computing resources together to provide BLAST query services based on the data indexing mechanism. Our experiments show that, with a data centric scheduling algorithm to improve the processor utilization, the BLAST service can achieve scalable high throughput.
New high-dimensional access methods based on superimposed space-partitioning schemes
Authors: Ratko Orlandic
Venue:  (2005)

Contemporary scientific and engineering applications increasingly rely on advanced database technology to store their data and search them on multi-attribute ranges. With the rapid increase in the volume and dimensionality of data, new multi-dimensional access methods are required to support these applications. This dissertation presents the results of a systematic research conducted to identify and pursue key factors of good retrieval performance in high-dimensional spaces. In the dissertation, the desirable properties of high-dimensional access methods are formulated as two design principles. The research shows that these properties depend on the space partitioning strategy underlying the access method, and that the existing partitioning schemes do not exhibit these properties. Based on this, a new partitioning strategy for high-dimensional spaces, called &Gamma;, is proposed. The static &Gamma; partitioning is used to impose desirable behavior on existing partitioning strategies. The idea of superimposed partitioning leads to a family of new access methods organized around the two design principles. The significant performance improvements over several popular access methods observed in the course of thorough experimental studies demonstrate the viability of the proposed access methods and the validity of the underlying approach. The emergence of advanced data-intensive analytical computing has also created the demand for efficient indexing of partially specified (incomplete) multi-dimensional data. The dissertation introduces new techniques for indexing incomplete data, which exploit key aspects of superimposed space partitioning. Effectively challenging conventional wisdom, this investigation has shown that multi-dimensional retrieval can be efficient, scalable, and effective even on incomplete data.
Two-level additive Schwarz preconditioners for C0 interior penalty methods
Authors: Susanne C. Brenner, Kening Wang
Venue: Numerische Mathematik (2005)

We study two-level additive Schwarz preconditioners that can be used in the iterative solution of the discrete problems resulting from C0 interior penalty methods for fourth order elliptic boundary value problems. We show that the condition number of the preconditioned system is bounded by C(1+(H3/&#x03b4;3)), where H is the typical diameter of a subdomain, &#x03b4; measures the overlap among the subdomains and the positive constant C is independent of the mesh sizes and the number of subdomains.
Visual Correlation of Host Processes and Network Traffic
Authors: Glenn A. Fink, Paul Muessig, Chris North
Venue: Proceedings of the IEEE Workshops on Visualization for Computer Security (2005)

Anomalous communication patterns are one of the leading indicators of computer system intrusions according to the system administrators we have interviewed. But a major problem is being able to correlate across the host/network boundary to see how network connections are related to running processes on a host. This paper introduces Portall, a visualization tool that gives system administrators a view of the communicating processes on the monitored machine correlated with the network activity in which the processes participate. Portall is a prototype of part of the Network Eye framework we have introduced in an earlier paper [1]. We discuss the Portall visualization, the supporting infrastructure it requires, and a formative usability study we conducted to obtain administrators' reactions to the tool.
Digital Government Research in Academia
Authors: Lois Delcambre, Genevieve Giuliano
Venue: Computer (2005)

Digital government projects are bringing together researchers from the technical and social sciences to participate in interdisciplinary and multidisciplinary collaborations that have the potential for making a broad and significant impact.
diorama table
Authors: Keiko Takahashi, Shinji Sasada
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

"diorama table " is an interactive table installation. People place physical objects on the table and projected elements such as trains, cars, houses, and trees appear and are interacted with physical objects.
Multiway Decision Tree Induction Using Projection and Merging (MPEG)
Authors: Yasser El-Sonbaty, Amgad Neematallah
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

Decision trees are one of the most popular and commonly used classification models. Many algorithms have been designed to build decision trees in the last twenty years. These algorithms are categorized into two groups according to the type of the trees they build, binary and multiway trees. In this paper, a new algorithm, MPEG, is designed to build multiway trees. MPEG uses DBMS indices and optimized query to access the dataset it works on, hence it has few memory requirements and no restrictions on sizes of datasets. Projection of examples over attribute values, merging of generated partitions using class values, applying GINI index to select among different attributes and finally post pruning using EBP method, are the basic steps of MPEG. The trees built by MPEG have the advantages of binary trees as being accurate, small in size and the advantages of multiway trees as being compact and easy to be comprehended by humans.
QoS Routing: Challenges and Solution Approaches
Authors: Ariel Orda
Venue: Proceedings of the Second International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks (2005)

Broadband integrated services networks are expected to support multiple and diverse applications with various Quality of Service (QoS) requirements. Accordingly, a major issue in the design of broadband architectures is how to provide the resources in order to meet the requirements of each connection, and, moreover, how to meet this goal in a networkwide efficient manner. QoS routing is, undoubtedly, one of the major building blocks in such architectures. However, QoS routing poses several major algorithmic challenges. One complication is the inherent intractability of many fundamental QoS routing problems. A second challenge is the need to provide scalable solutions, which can cope with the growing sizes of networks. An additional complication lies in the typical uncertainty regarding the precise state of the network. All these become ever more challenging when addressing multicast connections. Moreover, a successful QoS routing scheme should smoothly integrate with other QoS-enabling mechanisms, most notably schedulers. Finally, the practical deployment of QoS routing requires to successfully integrate it within standard routing protocols. These major challenges call for novel algorithmic approaches and solution schemes, which are the subject of this talk. We shall overview some typical problems and solution approaches, focusing on three representative models. The first is a "basic" model, where each network element can offer a certain degree of QoS at a certain "cost". In the second, "extended" model, each network element may offer various degrees of QoS, at different "costs". Finally, in the "coupled" model, the tasks of routing and scheduling are tackled together, hence providing a more precise assessment of the actual consumption of resources. We shall consider the support of bottleneck and additive QoS requirements, both for unicast as well as multicast connections, also in the presence of network failures. We shall focus on solution schemes that provide proven performance guarantees within efficient (polynomial) time complexity for general network topologies. We shall overview several approaches for improving scalability, with a particular focus on precomputation schemes. We shall indicate how this algorithmic framework can address problems of special practical interest, such as the need to cope with state uncertainty.
Relevance for browsing, relevance for searching
Authors: David Bodoff
Venue: Journal of the American Society for Information Science and Technology (2006)

The concept of relevance has received a great deal of theoretical attention. Separately, the relationship between focused search and browsing has also received extensive theoretical attention. This article aims to integrate these two literatures with a model and an empirical study that relate relevance in focused searching to relevance in browsing. Some factors affect both kinds of relevance in the same direction; others affect them in different ways. In our empirical study, we find that the latter factors dominate, so that there is actually a negative correlation between the probability of a document's relevance to a browsing user and its probability of relevance to a focused searcher. &copy; 2006 Wiley Periodicals, Inc.
Supporting Software Release Planning Decisions for Evolving Systems
Authors: Omolade Saliu, Guenther Ruhe
Venue: Proceedings of the 29th Annual IEEE/NASA on Software Engineering Workshop (2005)

Large-scale software systems constantly change during system evolution for feature enhancement. Most of the features originate from diverse stakeholders that require their needs to be met despite resource and risk constraints. In such large systems, the number of features requested during the different releases of the system typically exceeds the available resources. Release planning involves decision making about what new features or changes to implement during which release of the software. Existing release planning techniques are not targeted at evolving systems; in this case, knowledge about existing software product is core to making meaningful release decisions. In this paper, we describe ten key technical and nontechnical aspects impacting release planning. Based on these aspects, we evaluate seven existing release planning methods. We have also proposed a new release planning framework that considers the effect of existing system characteristics on release planning decisions. Initial realization of this framework focuses on historical defect data to characterize the health of system components. This proposed approach extends the existing solution method called EVOLVE by (i) the proactive analysis of the risk involved in integrating new features into existing components of the system and (ii) identifying the importance of estimating the integration effort for each feature based on system characteristics. An illustrative example is also presented.