Papers.

Retos en la interacción de la recuperación de información y el procesamiento del lenguaje natural

QueryBag: Using Different Sources For Querying Large Music Collections

Programming Scala - Scalability = Functional Programming + Objects

Proceedings of the Second ACM International Conference on Web Search and Data Mining

Proceedings of the 2009 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2009)

Privacy-as-a-Service: Models, Algorithms, and Results on the Facebook Platform

Parallel Higher-Order Finite Element Method for Accurate Field Computations in Wakefield and PIC Simulations

Over the past years, SLAC's Advanced Computations Department (ACD), under SciDAC sponsorship, has developed a suite of 3D (2D) parallel higher-order finite element (FE) codes, T3P (T2P) and Pic3P (Pic2P), aimed at accurate, large-scale simulation of wakefields and particle-field interactions in radio-frequency (RF) cavities of complex shape. The codes are built on the FE infrastructure that supports SLAC's frequency domain codes, Omega3P and S3P, to utilize conformal tetrahedral (triangular)meshes, higher-order basis functions and quadratic geometry approximation. For time integration, they adopt an unconditionally stable implicit scheme. Pic3P (Pic2P) extends T3P (T2P) to treat charged-particle dynamics self-consistently using the PIC (particle-in-cell) approach, the first such implementation on a conformal, unstructured grid using Whitney basis functions. Examples from applications to the International Linear Collider (ILC), Positron Electron Project-II (PEP-II), Linac Coherent Light Source (LCLS) and other accelerators will be presented to compare the accuracy and computational efficiency of these codes versus their counterparts using structured grids.

Parallel 3D Finite Element Particle-in-Cell Simulations with Pic3P

SLAC's Advanced Computations Department (ACD) has developed the parallel 3D Finite Element electromagnetic Particle-In-Cell code Pic3P. Designed for simulations of beam-cavity interactions dominated by space charge effects, Pic3P solves the complete set of Maxwell-Lorentz equations self-consistently and includes space-charge, retardation and boundary effects from first principles. Higher-order Finite Element methods with adaptive refinement on conformal unstructured meshes lead to highly efficient use of computational resources. Massively parallel processing with dynamic load balancing enables large-scale modeling of photoinjectors with unprecedented accuracy, aiding the design and operation of next-generation accelerator facilities. Applications include the LCLS RF gun and the BNL polarized SRF gun.

On the Value of Commitment Flexibility in Dynamic Task Allocation via Second-Price Auctions

On Multiple Kernel Learning with Multiple Labels

Next Generation Web Search.

Nested Named Entity Recognition

Light gluinos in hiding: Reconstructing R-parity violating decays at the Tevatron

Keynote Talk: Mining the Web 2.0 for Improved Image Search (the talk was given by Roelof van Zwol, the proceedings list Ricardo A. Baeza-Yates as the only author).

Joint Parsing and Named Entity Recognition

IEEE International Workshop on Advances in Music Information Research (AdMIRe-2009)

Human-competitive tagging using automatic keyphrase extraction

Human-competitive automatic topic indexing

How Feasible and Robust is the Automatic Extraction of Gene Regulation Events? A Cross-Method Evaluation under Lab and Real-Life Conditions.

Hierarchical Bayesian Domain Adaptation

Global Privacy and Security Law

Friends, Foes, and Fringe: Norms and Structure in Political Discussion Networks

FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs

Experiences with the Learning Resource Exchange for schools in Europe

ENERGY SAVINGS USING VARIABLE FREQUENCY DRIVES ON CENTRIFUGAL PUMPING APPLICATIONS

Declarative Languages to Declarative Processing in Computer Games

Content Analysis in Web 2.0

Cognitive Foundry v. 3.0 (OSS)

The Cognitive Foundry is a unified collection of tools designed for research and applications that use cognitive modeling, machine learning, or pattern recognition. The software library contains design patterns, interface definitions, and default implementations of reusable software components and algorithms designed to support a wide variety of research and development needs. The library contains three main software packages: the Common package that contains basic utilities and linear algebraic methods, the Cognitive Framework package that contains tools to assist in implementing and analyzing theories of cognition, and the Machine Learning package that provides general algorithms and methods for populating Cognitive Framework components from domain-relevant data.

Capabilities for Uniqueness and Borrowing

An important application of unique object references is safe and efficient message passing in concurrent object-oriented programming. However, to prevent the ill effects of aliasing, practical systems often severely restrict the shape of messages passed by reference. Moreover, the problematic interplay between destructive reads--often used to implement unique references--and temporary aliasing through "borrowed" references is exacerbated in a concurrent setting, increasing the potential for unpredictable run-time errors. This paper introduces a new approach to uniqueness. The idea is to use capabilities for enforcing both at-most-once consumption of unique references, and a flexible notion of uniqueness. The main novelty of our approach is a model of uniqueness and borrowing based on simple, unstructured capabilities. The advantages are: first, it provides simple foundations for uniqueness and borrowing. Second, it can be formalized using a relatively simple type system, for which we provide a complete soundness proof. Third, it avoids common problems involving borrowing and destructive reads, since unique references subsume borrowed references. We have implemented our type system as an extension to Scala. Practical experience suggests that our system allows type checking real-world actor-based concurrent programs with only a small number of additional type annotations.

AspectJ in Action: Enterprise AOP with Spring Applications (2nd edition)

Approximated Calculation for the Generalized Information Criteria based on Cross Validations

Analyzing Social Media Networks: Learning by Doing with NodeXL

An Intrinsic Stopping Criterion for Committee-Based Active Learning.

AdMIRe: International Workshop on Advances in Music Information Research 2009

Above the Clouds: A Berkeley View of Cloud Computing

Provided certain obstacles are overcome, we believe Cloud Computing has the potential to transform a large part of the IT industry, making software even more attractive as a service and shaping the way IT hardware is designed and purchased. Developers with innovative ideas for new interactive Internet services no longer require the large capital outlays in hardware to deploy their service or the human expense to operate it. They need not be concerned about over-provisioning for a service whose popularity does not meet their predictions, thus wasting costly resources, or under-provisioning for one that becomes wildly popular, thus missing potential customers and revenue. Moreover, companies with large batch-oriented tasks can get their results as quickly as their programs can scale, since using 1000 servers for one hour costs no more than using one server for 1000 hours. This elasticity of resources, without paying a premium for large scale, is unprecedented in the history of IT. The economies of scale of very large-scale datacenters combined with "pay-as-you-go" resource usage has heralded the rise of Cloud Computing. It is now attractive to deploy an innovative new Internet service on a third party's Internet Datacenter rather than your own infrastructure, and to gracefully scale its resources as it grows or declines in popularity and revenue. Expanding and shrinking daily in response to normal diurnal patterns could lower costs even further. Cloud Computing transfers the ri

A Common Substrate for Cluster Computing

A Best Practice Model for Cloud Middleware Systems

Abstract. Cloud computing is the latest trend in computing where the intention is to facilitate cheap, utility type computing resources in a service-oriented manner. However, the cloud landscape is still maturing and there are heterogeneities between the clouds, ranging from the ap-plication development paradigms to their service interfaces,and scaling approaches. These differences hinder the adoption of cloud by major en-terprises. We believe that a cloud middleware can solve most of these issues to allow cross-cloud inter-operation. Our proposed system is Al-tocumulus, a cloud middleware that homogenizes the clouds. In order to provide the best use of the cloud resources and make that use predictable and repeatable, Altocumulus is based on the concept of cloud best prac-tices. In this paper we briefly describe the Altocumulus middleware and detail the cloud best practice model it encapsulates. We also present ex-amples based on real world deployments as evidence to the applicability of our middleware. 1

15 Years of Language Resource Creation and Sharing: a Progress Report on LDC Activities

Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies

The Quest For Musical Genres: Do The Experts And The Wisdom Of Crowds Agree?

Healthcare Risk Modeling for Medicaid Patients - The Impact of Sampling on the Prediction of High-Cost Patients

Distilling Digital Traces: Computational Social Science Approaches to Studying the Internet

Yahoo!: towards a distributed search engine

CD-PAN : a protocol for peer-to-peer content distribution in a weakly connected and heterogeneous personal area network

This paper presents CD-PAN, a mechanism to automatically distribute content objects to weakly connected heterogeneous content devices in a personal area network without a global namespace. The content devices under consideration range from cell phones to personal computers, each of which is capable of downloading content objects on its own. The proposed mechanism alleviates the need to manually synchronize content that is downloaded to each of these content devices. A simulation study shows that CD-PAN outperforms other prefetching schemes in all our workload experiments. The performance improvement tended to increase with increase in popularity distribution skew, temporal locality and frequency of content creation/updates. The performance of CD-PAN increases when pair-wise communication capabilities are higher, and also adapts well to increasing power and metadata constraints.

Web Mining or The Wisdom of the Crowds

Studying the History of Ideas Using Topic Models

How can the development of ideas in a scientific field be studied over time? We apply unsupervised topic modeling to the ACL Anthology to analyze historical trends in the field of Computational Linguistics from 1978 to 2006. We induce topic clusters using Latent Dirichlet Allocation, and examine the strength of each topic over time. Our methods find trends in the field including the rise of probabilistic methods starting in 1988, a steady increase in applications, and a sharp decline of research in semantics and understanding between 1978 and 2001, possibly rising again after 2001. We also introduce a model of the diversity of ideas, topic entropy, using it to show that COLING is a more diverse conference than ACL, but that both conferences as well as EMNLP are becoming broader over time. Finally, we apply Jensen-Shannon divergence of topic distributions to show that all three conferences are converging in the topics they cover.

On Projecting Discretized Electromagnetic Fields with Unstructured Grids

A new method for projecting discretized electromagnetic fields on one unstructured grid to another grid is presented in this paper. Two examples are used for studying the errors of different projection methods. The analysis shows that the new method is very effective on balancing both the error of the electric field and that of the magnetic field (or curl of the electric field).

Yucca Mountain licensing support network archive assistant.

This report describes the Licensing Support Network (LSN) Assistant--a set of tools for categorizing e-mail messages and documents, and investigating and correcting existing archives of categorized e-mail messages and documents. The two main tools in the LSN Assistant are the LSN Archive Assistant (LSNAA) tool for recategorizing manually labeled e-mail messages and documents and the LSN Realtime Assistant (LSNRA) tool for categorizing new e-mail messages and documents. This report focuses on the LSNAA tool. There are two main components of the LSNAA tool. The first is the Sandia Categorization Framework, which is responsible for providing categorizations for documents in an archive and storing them in an appropriate Categorization Database. The second is the actual user interface, which primarily interacts with the Categorization Database, providing a way for finding and correcting categorizations errors in the database. A procedure for applying the LSNAA tool and an example use case of the LSNAA tool applied to a set of e-mail messages are provided. Performance results of the categorization model designed for this example use case are presented.

Main-memory scan sharing for multi-core CPUs

The Case of Predicates (Revisited): Predicate Instrumental in Russian and Its Restrictions