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  • Technology Transfer in Computing Systems

     Larriba Pey, Josep
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  • Graphalytics

     Larriba Pey, Josep
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  • Massive query expansion by exploiting graph knowledge bases for image retrieval

     Guisado Gamez, Joan; Dominguez Sal, David; Larriba Pey, Josep
    ACM International Conference on Multimedia Retrieval
    p. 33-40
    DOI: 10.1145/2578726.2578737
    Presentation's date: 2014-04-01
    Presentation of work at congresses

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    Annotation-based techniques for image retrieval suffer from sparse and short image textual descriptions. Moreover, users are often not able to describe their needs with the most appropriate keywords. This situation is a breeding ground for a vocabulary mismatch problem resulting in poor results in terms of retrieval precision. In this paper, we propose a query expansion technique for queries expressed as keywords and short natural language descriptions. We present a new massive query expansion strategy that enriches queries using a graph knowledge base by identifying the query concepts, and adding relevant synonyms and semantically related terms. We propose a topological graph enrichment technique that analyzes the network of relations among the concepts, and suggests semantically related terms by path and community detection analysis of the knowledge graph. We perform our expansions by using two versions of Wikipedia as knowledge base achieving improvements of the system's precision up to more than 27% Copyright 2014 ACM.

  • Gestió i Anàlisi de Dades Complexes

     Balcazar Navarro, Jose Luis; Morrill, Glyn Verden; Castro Rabal, Jorge; Delgado Pin, Jordi; Sierra Santibañez, Maria Josefina; Arias Vicente, Marta; Arratia Quesada, Argimiro Alejandro; Baixeries i Juvillà, Jaume; Ferrer Cancho, Ramon; Valentin Fernandez Gallart, Jose Oriol; Hernandez Fernandez, Antonio; Larriba Pey, Josep; Perez Casany, Marta; Prat Perez, Arnau; Guisado Gamez, Joan; Martinez Palau, Xavier; Gavaldà Mestre, Ricard
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  • Pla d'Actuació DAMA

     Larriba Pey, Josep
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  • Benchmarking, Applications and Technology for graph management and social analytics

     Perez Casany, Marta; Dominguez Sal, David; Martinez Bazan, Norbert; Boncz, Peter A.; Valduriez, Patrick; Angles, Renzo; Larriba Pey, Josep
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  • Query Optimization Engine for Graph Databases

     Larriba Pey, Josep
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  • A Coherent and Rich PaaS with a Common Programming Model

     Larriba Pey, Josep
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  • Producer-consumer: the programming model for future many-core processors

     Prat Perez, Arnau; Dominguez Sala, David; Larriba Pey, Josep; Troncoso, Pedro
    International Conference on Architecture of Computing Systems
    p. 110-121
    DOI: 10.1007/978-3-642-36424-2_10
    Presentation's date: 2013
    Presentation of work at congresses

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    The massive addition of cores on a chip is adding more pressure to the accesses to main memory. In order to avoid this bottleneck, we propose the use of a simple producer-consumer model, which allows for the temporary results to be transferred directly from one task to another. These data transfer operations are performed within the chip, using on-chip memory, thus avoiding costly off-chip memory accesses. We implement this model on a real many-core processor, the 48-core Intel Single-chip Cloud Computer processor using its on-chip memory facilities. We find that the Producer-Consumer model adapts to such architectures and allow to achieve good task and data parallelism. For the evaluation of the proposed platform we implement a graph-based application using the Producer- Consumer model. Our tests show that the model scales very well as it takes advantage of the on-chip memory. The execution times of our implementation are up to 9 times faster than the baseline implementation, which relies on storing the temporary results to main memory

    The massive addition of cores on a chip is adding more pressure to the accesses to main memory. In order to avoid this bottleneck, we propose the use of a simple producer-consumer model, which allows for the temporary results to be transferred directly from one task to another. These data transfer operations are performed within the chip, using on-chip memory, thus avoiding costly off-chip memory accesses. We implement this model on a real many-core processor, the 48-core Intel Single-chip Cloud Computer processor using its on-chip memory facilities. We find that the Producer-Consumer model adapts to such architectures and allow to achieve good task and data parallelism. For the evaluation of the proposed platform we implement a graph-based application using the Producer- Consumer model. Our tests show that the model scales very well as it takes advantage of the on-chip memory. The execution times of our implementation are up to 9 times faster than the baseline implementation, which relies on storing the temporary results to main memory.

  • GraphGen: a tool for automatic generation of multipartite graphs from arbitrary data

     Álvarez Garcia, Sandra; Baeza Yates, Ricardo; Brisaboa, Nieves R.; Larriba Pey, Josep; Pedreira, Oscar
    Latin American Web Congress
    p. 87-94
    DOI: 10.1109/LA-WEB.2012.15
    Presentation's date: 2012-10
    Presentation of work at congresses

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  • Linked Data Benchmark Council

     Perez Casany, Marta; Martinez Bazan, Norbert; Escale Claveras, Francesc; Ferrer Sumsi, Miquel; Prat Perez, Arnau; Dominguez Sal, David; Pau Fernandez, Raquel; Larriba Pey, Josep
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  • Shaping communities out of triangles

     Prat Perez, Arnau; Dominguez Sal, David; Brunat Blay, Josep Maria; Larriba Pey, Josep
    ACM International Conference on Information and Knowledge Management
    p. 1677-1681
    Presentation's date: 2012
    Presentation of work at congresses

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    Community detection has arisen as one of the most relevant topics in the field of graph data mining due to its importance in many fields such as biology, social networks or network traffic analysis. The metrics proposed to shape communi- ties are generic and follow two approaches: maximizing the internal density of such communities or reducing the connec - tivity of the internal vertices with those outside the commu - nity. However, these metrics take the edges as a set and do not consider the internal layout of the edges in the commu- nity. We define a set of properties oriented to social network s that ensure that communities are cohesive, structured and well defined. Then, we propose the Weighted Community Clustering ( W CC ), which is a community metric based on triangles. We proof that analyzing communities by trian- gles gives communities that fulfill the listed set of propert ies, in contrast to previous metrics. Finally, we experimentall y show that WCC correctly captures the concept of commu- nity in social networks using real and syntethic datasets, a nd compare statistically some of the most relevant community detection algorithms in the state of the art.

  • Efficient graph management based on bitmap indices

     Martinez Bazan, Norbert; Muntés Mulero, Víctor; Gómez Villamor, S.; Dominguez Sala, David; Aguila Lorente, Miguel Angel; Larriba Pey, Josep
    International Database Engineering and Applications Symposium
    p. 110-119
    DOI: 10.1145/2351476.2351489
    Presentation's date: 2012
    Presentation of work at congresses

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    The increasing amount of graph like data from social networks, science and the web has grown an interest in analyzing the relationships between different entities. New specialized solutions in the form of graph databases, which are generic and able to adapt to any schema as an alternative to RDBMS, have appeared to manage attributed multigraphs efficiently. In this paper, we describe the internals of DEX graph database, which is based on a representation of the graph and its attributes as maps and bitmap structures that can be loaded and unloaded efficiently from memory. We also present the internal operations used in DEX to manipulate these structures. We show that by using these structures, DEX scales to graphs with billions of vertices and edges with very limited memory requirements. Finally, we compare our graph-oriented approach to other approaches showing that our system is better suited for out-of-core typical graph-like operations.

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    Hybrid tables for speeding-up data accesses in hybrid database management systems  Open access

     Guisado Gamez, Joan; Wolski, Antoni; Zuzarte, Calisto; Larriba Pey, Josep; Muntés Mulero, Víctor
    Jornadas de Ingeniería del Software y Bases de Datos
    Presentation's date: 2011-09-06
    Presentation of work at congresses

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  • Memory-, bandwidth-, and power-aware multi-core for a graph database workload

     Trancoso, Pedro; Martinez Bazan, Norbert; Larriba Pey, Josep
    International Conference on Architecture of Computing Systems
    p. 171-182
    DOI: 10.1007/978-3-642-19137-4_15
    Presentation's date: 2011-02-24
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    Processors have evolved to the now de-facto standard multicore architecture. The continuous advances in technology allow for increased component density, thus resulting in a larger number of cores on the chip. This, in turn, places pressure on the off-chip and pin bandwidth. Large Last-Level Caches (LLC), which are shared among all cores, have been used as a way to control the out-of-chip requests. In this work we focus on analyzing the memory behavior of a modern demanding application, a graph-based database workload, which is representative of future workloads. We analyze the performance of this application for different cache configurations in terms of: memory access time, bandwidth requirements, and power consumption. The experimental results show that the bandwidth requirements reduce as the number of clusters reduces and the LLC per cluster increases. This configuration is also the most power efficient. If on the other hand, memory latency is the dominant factor, assuming bandwidth is not a limitation, then the best configuration is the one with more clusters and smaller LLCs.

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    Hybrid in-memory and on-disk tables for speeding-up table accesses  Open access

     Guisado Gamez, Joan; Wolski, Antoni; Zuzarte, Calisto; Larriba Pey, Josep; Muntés Mulero, Víctor
    International Conference on Database and Expert Systems Applications
    p. 231-240
    Presentation's date: 2010-08-30
    Presentation of work at congresses

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    Main memory database management systems have become essential for response-time-bounded applications, such as those in telecommunications systems or Internet, where users frequently access a table in order to get information or check whether an element exists, and require the response to be as fast as possible. Continuous data growth is making it unafordable to keep entire relations in memory and some commercial applications provide two different engines to handle data in-memory and on-disk separately. However, these systems assign each table to one of these engines, forcing large relations to be kept on secondary storage. In this paper we present TwinS|a hybrid database management system that allows managing hybrid tables, i.e. tables partially managed by both engines. Our objective is twofold: first, to allow large tables that do not fit in the memory to partially benefit from in-memory management techniques and, second, to provide a way to discard unnecessary accesses to both memory and disk. Overall, we show that we can reduce response time when accessing a large table in the database. All our experiments have been run on a dual-engine DBMS: IBM-SolidDB .

  • Analysis and Optimization of Question Answering Systems  Open access

     Dominguez Sala, David
    Department of Computer Architecture, Universitat Politècnica de Catalunya
    Theses

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  • PROCESADO DE ALTO RENDIMIENTO DE GRANDES CONJUNTOS DE DATOS REPRESENTADOS COMO GRAFOS

     Dominguez Sala, David; Martinez Bazan, Norbert; Gomez Villamor, Sergio; Perez Casany, Marta; Larriba Pey, Josep
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  • Creixement centre DAMA-UPC

     Larriba Pey, Josep
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  • Desemantization for numerical microdata anonymization

     Pont Tuset, Jordi; Nin Guerrero, Jordi; Medrano Gracia, Pau; Larriba Pey, Josep; Muntés Mulero, Víctor
    Date of publication: 2010
    Book chapter

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    The design of cryptographic and security protocols for new scenarios and applications can be computationally expensive. Examples of these can be sensor or mobile ad-hoc networks where thousands of nodes can be involved. In such cases, the aid of an automated tool generating protocols for a predefined problem can be of great utility. This work uses the genetic algorithms (GA) techniques for the automatic design of security networked protocols. When using GA for optimizing protocols two aspects are critical: the genome definition and the evaluation function. We discuss how security protocols can be represented as binary strings and can be interpreted as security protocols; moreover we define several basic criteria for evaluating security protocols. Finally, we present the software we developed for generating secure communications protocols and show some examples and obtained results.

  • DEX: ANÁLISIS DE DATOS

     Baleta Ferrer, Pedro; Coll Jimenez, Damaris; Trench Ribes, Nuria; Pau Fernandez, Raquel; Ventura Simon, Robert; Tomas Ozalla, Miguel; Guisado Gamez, Joan; Prat Perez, Arnau; Martinez Palau, Xavier; Larriba Pey, Josep
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    Cache-aware load balancing vs. cooperative caching for distributed search engines  Open access

     Dominguez Sala, David; Perez Casany, Marta; Larriba Pey, Josep
    IEEE International Conference on High Performance Computing and Communications
    p. 415-423
    Presentation's date: 2009-06-26
    Presentation of work at congresses

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    In this paper we study the performance of a distributed search engine from a data caching point of view. We compare and combine two different approaches to achieve better hit rates: (a) send the queries to the node which currently has the related data in its local memory (cache-aware load balancing), and (b) send the cached contents to the node where a query is being currently processed (cooperative caching). Furthermore, we study the best scheduling points in the query computation in which they can be reassigned to another node, and how this reassignation should be performed. Our analysis is guided by statistical tools on a real question answering system for several query distributions, which are typically found in query logs.

  • Proposta XViB Call 5 ICT

     Larriba Pey, Josep
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  • CONTINUACIÓN DE LA CREACIÓN DE UN SISTEMA DE ANALISIS DE LA INVESTIGACIÓN EN ESPAÑA, TIN2007-30380

     Dominguez Sala, David; Martinez Bazan, Norbert; Pau Fernandez, Raquel; Muntés Mulero, Víctor; Gomez Villamor, Sergio; Larriba Pey, Josep
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  • 9th Business Ideas Competition of the Department of Innovation, Universities and Industry of the Generalitat de Catalunya

     Muntés Mulero, Víctor; Larriba Pey, Josep; Martinez Bazan, Norbert; Baleta Ferrer, Pedro
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  • Improving microaggregation for complex record anonymization

     Pont Tuset, Jordi; Nin Guerrero, Jordi; Medrano Gracia, Pau; Larriba Pey, Josep; Muntés Mulero, Víctor
    International Conference on Modeling Decisions for Artificial Intelligence
    p. 215-226
    DOI: 10.1007/978-3-540-88269-5_20
    Presentation's date: 2008-10-31
    Presentation of work at congresses

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    Microaggregation is one of the most commonly employed microdata protection methods. This method builds clusters of at least k original records and replaces the records in each cluster with the centroid of the cluster. Usually, when records are complex, i.e., the number of attributes of the data set is large, this data set is split into smaller blocks of attributes and microaggregation is applied to each block, successively and independently. In this way, the information loss when collapsing several values to the centroid of their group is reduced, at the cost of losing the k-anonymity property when at least two attributes of different blocks are known by the intruder. In this work, we present a new microaggregation method called One dimension microaggregation (Mic1D − κ). This method gathers all the values of the data set into a single sorted vector, independently of the attribute they belong to. Then, it microaggregates all the mixed values together. Our experiments show that, using real data, our proposal obtains lower disclosure risk than previous approaches whereas the information loss is preserved.

  • Parallelizing record linkage for disclosure risk assessment

     Guisado Gamez, Joan; Prat Perez, Arnau; Nin Guerrero, Jordi; Muntés Mulero, Víctor; Larriba Pey, Josep
    Privacy in Statistical Databases
    p. 190-202
    DOI: 10.1007/978-3-540-87471-3_16
    Presentation's date: 2008-09-25
    Presentation of work at congresses

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  • Load Balancing for Question Answering

     Dominguez Sala, David; Aguilar Saborit, Josep; Surdeanu, Mihai; Larriba Pey, Josep
    Date: 2008-06
    Report

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  • On the use of Evolutive Summary Counters in Distributed Retrieval Systems

     Dominguez Sala, David; Aguilar Saborit, Josep; Surdeanu, Mihai; Larriba Pey, Josep
    Date: 2008-03
    Report

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  • ONN the use of neural networks for data privacy

     Pont Tuset, Jordi; Medrano Gracia, Pau; Nin Guerrero, Jordi; Larriba Pey, Josep; Muntés Mulero, Víctor
    International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM)
    p. 634-645
    DOI: 10.1007/978-3-540-77566-9_55
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  • Premi BDigital Global d'Innovació Digital

     Larriba Pey, Josep; Martinez Bazan, Norbert; Gomez Villamor, Sergio; Pons, M; Rodríguez, A; Erola, P
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  • Semantic blocking for record linkage

     Nin Guerrero, Jordi; Muntés Mulero, Víctor; Martinez Bazan, Norbert; Larriba Pey, Josep
    International Conference of the Catalan Association for Artificial Intelligence
    p. 141-149
    Presentation's date: 2007-10-25
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  • DEX: High Performance Exploration on Large Graphs for Information Retrieval

     Martinez Bazan, Norbert; Muntés Mulero, Víctor; Gomez Villamor, Sergio; Nin, J; Sánchez, Marcelo; Larriba Pey, Josep
    Date: 2007-08
    Report

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  • Genetic optimization for large join queries

     Muntés Mulero, Víctor
    Department of Computer Architecture, Universitat Politècnica de Catalunya
    Theses

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  • L'assignatura Programació Conscient de l'Arquitectura

     Fernandez Jimenez, Agustin; Jimenez Gonzalez, Daniel; Larriba Pey, Josep; Morancho Llena, Enrique; Ramirez Bellido, Alejandro
    Jornades de Docència del Departament d'Arquitectura de Computadors. 10 Anys de Jornades
    p. 1-10
    Presentation of work at congresses

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  • A Multi-layer Collaborative Cache for Question Answering

     Dominguez Sala, David; Larriba Pey, Josep; Surdeanu, Mihai
    Euro-Par
    p. 295-306
    Presentation of work at congresses

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    Parameter determination of ONN (Ordered Neural Networks)  Open access

     Pont Tuset, Jordi; Medrano Gracia, Pau; Nin Guerrero, Jordi; Larriba Pey, Josep; Muntés Mulero, Víctor
    Date: 2007
    Report

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    The need for data privacy motivates the development of new methods that allow to protect data minimizing the disclosure risk without losing information. In this paper, we propose a new protection method for numerical data called Ordered Neural Networks (ONN) method. ONN presents a new way to protect data based on the use of Artificial Neural Networks (ANN). ONN combines the use of ANN with a new strategy for preprocessing data consisting in the vectorization, sorting and partitioning of all the values in the attributes to be protected in the data set. We also present an statistical analysis that allows to understand the most important parameters affecting the quality of our method, and we show that it is possible to find a good configuration for these parameters. Finally, we compare our method to the best methods presented in the literature, using data provided by the US Census Bureau. Our experiments show that ONN outperforms the previous methods proposed in the literature, proving that the use of ANNs in these situations is convenient to protect the data efficiently without losing the statistical properties of the set.

    Postprint (author’s final draft)

  • COMPLEMENTÀRIA AL PROJECTE EUROPEU SEMEDIA

     Larriba Pey, Josep
    Competitive project

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    Increasing polynomial regression complexity for data anonymization  Open access

     Nin Guerrero, Jordi; Pont Tuset, Jordi; Medrano Gracia, Pau; Larriba Pey, Josep; Muntés Mulero, Víctor
    International Conference on Intelligent Pervasive Computing
    p. 29-34
    DOI: 10.1109/IPC.2007.103
    Presentation's date: 2007
    Presentation of work at congresses

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    Pervasive computing and the increasing networking needs usually demand from publishing data without revealing sensible information. Among several data protection methods proposed in the literature, those based on linear regression are widely used for numerical data. However, no attempts have been made to study the effect of using more complex polynomial regression methods. In this paper, we present PoROP-k, a family of anonymizing methods able to protect a data set using polynomial regressions. We show that PoROP-k not only reduces the loss of information, but it also obtains a better level of protection compared to previous proposals based on linear regressions.

  • Improving Quality and Convergence of Genetic Query Optimizers

     Muntés Mulero, Víctor; Lafon Gracia, Nestor; Aguilar Saborit, Josep; Larriba Pey, Josep
    12th International Conference on Database Systems for Advanced Applications DASFAA 2007
    p. 6-17
    Presentation of work at congresses

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