ppxscal/embedding_network huggingface dataset:
Search in the Eye of the Beholder: Using the Personal Social Dataset and Ontology-guided Input to Improve Web Search Efficiency
Authors: Juan Miguel Gomez, Ricardo Colomo Palacios, Angel Garcia Crespo, Giner Alor-Hernandez, Ruben Posada-Gomez
Venue: Proceedings of the 2007 Latin American Web Conference (2007)

Among the challenges of searching the vast information source the Web has become, improving Web search efficiency by different strategies using semantics and the user generated data from Web 2.0 applications remains a promising and interesting approach. In this paper, we present the Personal Social Dataset and Ontology-guided Input strategies and couple them together, providing a proofof- concept implementation.
Steps towards cache-resident transaction processing
Authors: Stavros Harizopoulos, Anastassia Ailamaki
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

Online transaction processing (OLTP) is a multibillion dollar industry with high-end database servers employing state-of-the-art processors to maximize performance. Unfortunately, recent studies show that CPUs are far from realizing their maximum intended throughput because of delays in the processor caches. When running OLTP, instruction-related delays in the memory subsystem account for 25 to 40% of the total execution time. In contrast to data, instruction misses cannot be overlapped with out-of-order execution, and instruction caches cannot grow as the slower access time directly affects the processor speed. The challenge is to alleviate the instruction-related delays without increasing the cache size. We propose Steps, a technique that minimizes instruction cache misses in OLTP workloads by multiplexing concurrent transactions and exploiting common code paths. One transaction paves the cache with instructions, while close followers enjoy a nearly miss-free execution. Steps yields up to 96.7% reduction in instruction cache misses for each additional concurrent transaction, and at the same time eliminates up to 64% of mispredicted branches by loading a repeating execution pattern into the CPU. This paper (a) describes the design and implementation of Steps, (b) analyzes Steps using microbenchmarks, and (c) shows Steps performance when running TPC-C on top of the Shore storage manager.
Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research
Authors: Miriam J. Metzger
Venue: Journal of the American Society for Information Science and Technology (2007)

This article summarizes much of what is known from the communication and information literacy fields about the skills that Internet users need to assess the credibility of online information. The article reviews current recommendations for credibility assessment, empirical research on how users determine the credibility of Internet information, and describes several cognitive models of online information evaluation. Based on the literature review and critique of existing models of credibility assessment, recommendations for future online credibility education and practice are provided to assist users in locating reliable information online. The article concludes by offering ideas for research and theory development on this topic in an effort to advance knowledge in the area of credibility assessment of Internet-based information. &copy; 2007 Wiley Periodicals, Inc.
Functional Similarity Analyzing of Protein Sequences with Empirical Mode Decomposition
Authors: Feng Shi, Qiujian Chen, Xiaohui Niu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

This paper applies empirical mode decomposition (EMD) to find functional similarity of proteins with low identity. The cross-correlation coefficient based on the EMD is used to measure the pair-wise similarity. We also use a segmentation technique, combined with EMD, to handle long protein sequences. The results are compared with those using the pair-wise alignment and PSI-BLAST.
CDIP: Collection-Driven, yet Individuality-Preserving Automated Blog Tagging
Authors: Jong Wook Kim, K. Selcuk Candan, Junichi Tatemura
Venue: Proceedings of the International Conference on Semantic Computing (2007)

With the success of blogs as popular information sharing media, searches on blogs have become popular. In the blogosphere, tagging is used as a means of annotating blog entries with contextually meaningful keywords, which enable users more easily locate blog content. Yet, although tags provided by bloggers are effective for organizing blog entries, in many cases, they are not always sufficient in properly capturing the semantics of the blog content. In our previous work [7], we observed that there exists large degree of content overlap (not only in the form of quotation/ commentary pairs, but also as content borrowing across media outlets) among blog entries, which makes it hard for effective, discriminating keyword searches. In this paper, we further note that these implicit or explicit quotations could be leveraged to identify the contexts in which entries occur; thus, resulting in more effective tagging. Thus, we propose CDIP (a collection-driven, yet individuality-preserving tagging system) which relies on relationships provided by quotation/reuse detection and semantic-focus analysis to automatically tag the blogs in such a way that, not-only the related blogs share tags, but also individuality of the entries is preserved for discriminating tag-based accesses.
Automated Development Environments
Authors: A. I. Wasserman
Venue: Computer (1981)

Future software development systems will build on the success of Unix and Interlisp, adding central data bases to store in-progress project information accessible through sophisticated user interfaces.
How can multi-topology routing be used for intradomain traffic engineering?
Authors: Amund Kvalbein, Olav Lysne
Venue: Proceedings of the 2007 SIGCOMM workshop on Internet network management (2007)

Multi-Topology routing allows each router in a network to maintain several valid routes to each destination. This increases the possibilities to spread traffic towards a destination over multiple paths with connectionless routing protocols like OSPF or IS-IS. In this paper, we report early ideas on how this can be utilized as a Traffic Engineering tool. We look at both offline and online approaches, and argue that a Multi-Topology based solution has advantages over previous solutions in both paradigms.
Distance String Models for Program Behavior
Authors: J. Spirn
Venue: Computer (1976)

To analyze or simulate an operating/computer system, one must construct a model of the programs executing within the system. Many recent analyses, particularly queueing models, have used mathematically convenient program models. For example, in one popular model the times between page faults are assumed to be exponentially distributed and independent. However, such a program model is inaccurate, which may cause the analysis to be unrepresentative of the real world. Simulation models of systems, on the other hand, have relied largely on traces of actual programs. Such traces are undoubtedly more accurate than simple mathematical models, but they have several drawbacks. They are expensive to generate, they may not be truly representative of typical programs, and they may contain more detail than is necessary for accurate system modeling. Moreover, it is difficult to extrapolate their behavior to other similar programs.
Microprocessor Architecture and Systems
Authors: M. J. Gonzalez
Venue: Computer (1976)

A Workshop on Microprocessor Architecture and Systems was held on May 6-7, 1976, at Northwestern University under the sponsorship of the Technical Committee on Computer Architecture and the Technical Committee on Minis and Micros of the IEEE Computer Society. No formal theme was established, and no summary positions were presented by the attendees, but the following conclusions appeared to emerge:
Rule component specification for business process deployment
Authors: Saqib Ali, Torab Torabi, Ben Soh
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

In this paper we propose an approach to treat business rules as a separate component of business model used in business process deployment. Using this approach, we can define, customise and deploy business processes that are directly dependent upon business rules. Moreover, business rules can be applied efficiently and consistently to a business process. Furthermore, we are able to incorporate these rules into another business process, where each process depends upon some specific rules, policies, procedures and standards. The approach also provides the flexibility to allow business process automation to be more customisable, flexible, efficient and reusable.
Sparseness vs Estimating Conditional Probabilities: Some Asymptotic Results
Authors: Peter L. Bartlett, Ambuj Tewari
Venue: The Journal of Machine Learning Research (2007)

One of the nice properties of kernel classifiers such as SVMs is that they often produce sparse solutions. However, the decision functions of these classifiers cannot always be used to estimate the conditional probability of the class label. We investigate the relationship between these two properties and show that these are intimately related: sparseness does not occur when the conditional probabilities can be unambiguously estimated. We consider a family of convex loss functions and derive sharp asymptotic results for the fraction of data that becomes support vectors. This enables us to characterize the exact trade-off between sparseness and the ability to estimate conditional probabilities for these loss functions.
Semantic Processing of Natural Language Queries in the OntoNL Framework
Authors: Anastasia Karanastasi, Stavros Christodoulakis
Venue: Proceedings of the International Conference on Semantic Computing (2007)

The OntoNL Framework provides an architecture and re-usable components for automating as much as possible the building of natural language interfaces to information systems. In addition to the syntactic analysis components, OntoNL has semantic analysis components which exploit domain ontologies to provide better disambiguation of the user input. We present in this paper the algorithms used for semantic processing of the natural language queries, as well as an ontology-driven semantic relatedness measure developed for this purpose. We also present extensive evaluation results with different ontologies using human subjects.
Supporting collaborative software development through the visualization of socio-technical dependencies
Authors: Cleidson R. de Souza, Stephen Quirk, Erik Trainer, David F. Redmiles
Venue: Proceedings of the 2007 international ACM conference on Supporting group work (2007)

One of the reasons large-scale software development is difficult is the number of dependencies that software engineers face. These dependencies create a need for communication and coordination that requires continuous effort by developers. Empirical studies, including our own, suggest that technical dependencies among software components create social dependencies among the software developers implementing those components. Based on this observation, we developed Ariadne, a plug-in for Eclipse. Ariadne analyzes software projects for dependencies and collects authorship information about projects relying on configuration management repositories. Ariadne can "translate" technical dependencies among components into social dependencies among developers. We have created visualizations to convey dependency information and the presence of coordination problems identified in our previous work. We believe the information conveyed in the visualizations will prove useful for software developers.
Special Feature: Prometheus or Pandora: The Influence of Automation on Society
Authors: H. A. Simon
Venue: Computer (1981)

Even though computer technology may challenge one of man's last and most cherished illusions that he alone is capable of thought it can also show him how to live in harmony with nature.
CT-MRI automatic surface-based registration schemes combining global and local optimization techniques
Authors: George K. Matsopoulos, Konstantinos K. Delibasis, Nicolaos A. Mouravliansky, Pantelis A. Asvestas, Konstantina S. Nikita, Vassilios E. Kouloulias, Nikolaos K. Uzunoglu
Venue: Technology and Health Care (2003)

Medical image registration is commonly required in order to combine the complementary information provided by different medical imaging modalities. In this paper, a new automatic registration scheme is proposed to register 3-D CT-MR head images and is currently tested on a clinical environment. The proposed scheme, after the preprocessing and the outer surface extraction of the data, is based on the use the rigid transformation method, in conjunction with a combination of global and local optimization techniques. Analytically, the paper exploits the optimization efficiency of three widely used optimization techniques, in obtaining the parameters of the rigid transformation model: the Downhill Simplex Method, the Genetic Algorithms and the Simulated Annealing. These optimization techniques are further combined by the sequential application of the Powell optimization method in order to refine the registration and increase its accuracy. A comparative study involving these optimization techniques in conjunction with the rigid transformation, and two other methods, the ICP and the manual methods, is also presented, for a sufficient number of clinical CT-MR brain images. Finally, quantitative and qualitative results are also presented to validate the performance of these automatic surface-based registration schemes, in terms of consistency and accuracy. Throughout of this study, the automatic registration scheme comprising of the rigid transformation in conjunction with the Simulated Annealing method sequentially combined with the Powell method has been performed superior regarding all the other compared registration schemes.
Packing vertices and edges in random regular graphs
Authors: Mihalis Beis, William Duckworth, Michele Zito
Venue: Random Structures Algorithms (2008)

In this paper we consider the problem of finding large collections of vertices and edges satisfying particular separation properties in random regular graphs of degree r, for each fixed r &ge; 3. We prove both constructive lower bounds and combinatorial upper bounds on the maximal sizes of these sets. The lower bounds are proved by analyzing a class of algorithms that return feasible solutions for the given problems. The analysis uses the differential equation method proposed by Wormald [Lectures on Approximation and Randomized Algorithms, PWN, Wassaw, 1999, pp. 239&ndash;298]. The upper bounds are proved by direct combinatorial means. &copy; 2007 Wiley Periodicals, Inc. Random Struct. Alg., 2008
A New Cost-Effective Technique for QoS Support in Clusters
Authors: Alejandro Martinez, Francisco J. Alfaro, José L. Sanchez, Francisco . J. Quiles, José Duato
Venue: IEEE Transactions on Parallel and Distributed Systems (2007)

Virtual channels (VCs) are a popular solution for the provision of quality of service (QoS). Current interconnect standards propose 16 or even more VCs for this purpose. However, most implementations do not offer so many VCs because it is too expensive in terms of silicon area. Therefore, a reduction of the number of VCs necessary to support QoS can be very helpful in the switch design and implementation.In this paper, we show that this number of VCs can be reduced if the system is considered as a whole rather than each element being taken separately. The scheduling decisions made at network interfaces can be easily reused at switches without significantly altering the global behavior. In this way, we obtain a noticeable reduction of silicon area, component count, and, thus, power consumption, and we can provide similar performance to a more complex architecture. We also show that this is a scalable technique, suitable for the foreseen demands of traffic.
The "active" gatekeeper in collaborative information seeking activities
Authors: Patricia Ruma Spence, Madhu C. Reddy
Venue: Proceedings of the 2007 international ACM conference on Supporting group work (2007)

Multidisciplinary team members often must work together to find needed information. To identify when team members collaborate, why they collaborate, and how they collaborate during information seeking activities, we conducted a field study of a multidisciplinary patient care team. We found that the unit secretary, a non-clinical team member, had characteristics of various types of gatekeepers identified in previous studies. However, unlike those gatekeepers, the unit secretary also played a particularly active role during information seeking activities. Most medical information systems design focus on supporting collaboration amongst clinical staff. Our study highlights the importance of also supporting non-clinical team members.
Built-In Speed Grading with a Process-Tolerant ADPLL
Authors: Hsuan-Jung Hsu, Chun-Chieh Tu, Shi-Yu Huang
Venue: Proceedings of the 16th Asian Test Symposium (2007)

Speed grading has becoming more and more important for nanometer technologies to support activities like process monitoring or performance diagnosis. In this work, we analyze the feasibility of providing such a capability through on-chip circuitry. This Built-In Speed Grading (BISG) methodology uses an All-Digital Phase-Locked Loop (ADPLL) as the programmable clock generator to provide various clock signals within a specific frequency range. The maximum operating speed of a circuit can thus be easily tracked down using a binary search process with multiple runs of built-in self-test. To accommodate larger process variation, we further explore a so-called binary-neighborhood-linear frequency-locking scheme for the underlying ADPLL, and thereby resulting in a higher accuracy. Experimental results show that only 2289 gates are adequate to provide this valuable infrastructure that may find numerous applications in IC testing and diagnostics.
A New Approach for Fuzzy Fertilization Forecast Based on Support Vector Learning Mechanism
Authors: Miao Li, Dezhou Fang, Jian Zhang, Qiang Zhang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

This paper presents a support vector machine (SVM) algorithm to generate fertilization fuzzy rules so as to realize the prediction method. That SVM is equivalent to the fuzzy rule-based modeling (FRM) is important to many practical and complicated situations where one unable to determine the number of rules in advance, such as knowledge acquisition form samples. Agricultural fertilizer commonly used orthogonal experiment whose balanced scattered data makes the regression curve fitting method ineffective. This paper presents training data set for SVM learning, and takes advantage of membership to extract fuzzy IF-THEN rules. Rule activated by the threshold value and credibility controls the prediction process. The approach not only avoids the error caused by regression method, and the fuzzy rules also increase the linguistic interpretability of the generated rules, and improve the capability of knowledge acquisition greatly. The performance of the proposed approach is compared to the linear regression method by orthogonal experiment. Index Terms: fuzzy rules extraction, orthogonal experiment, SVM, fuzzy sets division
Weighted kNNModel-Nased Data Reduction and Classification
Authors: Xuming Huang, Gongde Guo, Daniel Neagu, Tianqiang Huang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

A weighted kNNModel-based data reduction and classification algorithm, called wkNNModel, is proposed in this paper which aims to find some more meaningful representatives to replace the original dataset for further classification. Each representative is formed by an instance and its weighted neighbourhood satisfies a predefined threshold. Compared to kNNModel the proposed method, as an alterative to other kNN algorithms, further alleviates the effect of abnormal data, i.e. noisy or boundary disturbance data, to data reduction and classification, thus contributing to the improvement of data reduction rate.
A Stock Pattern Recognition Algorithm Based on Neural Networks
Authors: Xinyu Guo, Xun Liang, Xiang Li
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

Recent studies show that stock patterns might implicate useful information for stock price forecasting. The patterns underlying the price time series can not be discovered exhaustively by the pure man power in a limited time, thus the computer algorithm for stock price pattern recognition becomes more and more popular. Currently, there are mainly two kinds of stock price pattern recognition algorithms: the algorithm based on rule-matching and the algorithm based on template-matching. However, both of the two algorithms highly require the participation of domain experts, as well as their lacks of the learning ability. To solve these problems, the paper proposes a stock price pattern recognition approach based upon the artificial neural network. The experiment shows that the neural network can effectively learn the characteristics of the patterns, and accurately recognize the patterns.
A new video segmentation method of moving objects based on blob-level knowledge
Authors: Enrique J. Carmona, Javier Martínez-Cantos, José Mira
Venue: Pattern Recognition Letters (2008)

Variants of the background subtraction method are broadly used for the detection of moving objects in video sequences in different applications. In this work we propose a new approach to the background subtraction method which operates in the colour space and manages the colour information in the segmentation process to detect and eliminate noise. This new method is combined with blob-level knowledge associated with different types of blobs that may appear in the foreground. The idea is to process each pixel differently according to the category to which it belongs: real moving objects, shadows, ghosts, reflections, fluctuation or background noise. Thus, the foreground resulting from processing each image frame is refined selectively, applying at each instant the appropriate operator according to the type of noise blob we wish to eliminate. The approach proposed is adaptive, because it allows both the background model and threshold model to be updated. On the one hand, the results obtained confirm the robustness of the method proposed in a wide range of different sequences and, on the other hand, these results underline the importance of handling three colour components in the segmentation process rather than just the one grey-level component.