Camelia Constantin

Watermill: An Optimized Fingerprinting System for Databases under Constraints

This paper presents a walermarking/fingerprinting system for relational databases. It features a built-in declarative language to specify usability constraints that watermarked data sets must comply with. For a subset of these constraints, namely, weight-independent constraints, we propose a novel watermarking strategy that consists of translating them into an integer linear program. We show two watermarking strategies: an exhaustive one based on integer linear programming constraint solving and a scalable pairing heuristic. Fingerprinting applications, for which several distinct watermarks need to be computed, benefit from the reduced computation time of our method that precomputes the watermarks only once. Moreover, we show that our method enables practical collusion-secure fingerprinting since the precomputed watermarks are based on binary alterations located at exactly the same positions. The paper includes an in-depth analysis of false-hit and false-miss occurrence probabilities for the detection algorithm. Experiments performed on our open source software WATERMILL assess the watermark robustness against common attacks and show that our method outperforms the existing ones concerning the watermark embedding speed.

RecLand: A Recommender System for Social Networks

Social networks have become an important information source. Due to their unprecedented success, these systems have to face an exponentially increasing amount of user generated content. As a consequence, finding relevant users or data matching specific interests is a challenging. We present RecLand, a recommender system that takes advantage of the social graph topology and of the existing contextual information to recommend users. The graphical interface of RecLand shows recommendations that match the topical interests of users and allows to tune the parameters to adapt the recommendations to their needs.

A link-based ranking model for services

The number of services on the web is growing every day and finding useful and efficient ranking methods for services has become an important issue in modern web applications In this paper we present a link-based importance model and efficient algorithms for distributed services collaborating through service calls We adapt the PageRank algorithm and define a service importance that reflects its activity and its contribution to the quality of other services.

AS-Index: A Structure For String Search Using n-grams and Algebraic Signatures

We present the AS-Index, a new index structure for exact string search in disk resident databases. AS-Index relies on a classical inverted file structure, whose main innovation is a probabilistic search based on the properties of algebraic signatures used for both n-grams hashing and pattern search. Specifically, the properties of our signatures allow to carry out a search by inspecting only two of the posting lists. The algorithm thus enjoys the unique feature of requiring a constant number of disk accesses, independently from both the pattern size and the database size. We conduct extensive experiments on large datasets to evaluate our index behavior. They confirm that it steadily provides a search performance proportional to the two disk accesses necessary to obtain the posting lists. This makes our structure a choice of interest for the class of applications that require very fast lookups in large textual databases. We describe the index structure, our use of algebraic signatures, and the search algorithm. We discuss the operational trade-offs based on the parameters that affect the behavior of our structure, and present the theoretical and experimental performance analysis. We next compare the AS-Index with the state-of-the-art alternatives and show that 1) its construction time matches that of its competitors, due to the similarity of structures, 2) as for search time, it constantly outperforms the standard approach, thanks to the economical access to data complemented by signature calculations, which is at the core of our search method.

A Block-Based Edge Partitioning for Random Walks Algorithms over Large Social Graphs

Recent resultsi¾?[5, 9, 23] prove that edge partitioning approaches also known as vertex-cut outperform vertex partitioningedge-cut approaches for computations on large and skewed graphs like social networks. These vertex-cut approaches generally avoid unbalanced computation due to the power-law degree distribution problem. However, these methods, like evenly random assigningi¾?[23] or greedy assignment strategyi¾?[9], are generic and do not consider any computation pattern for specific graph algorithm. We propose in this paper a vertex-cut partitioning dedicated to random walks algorithms which takes advantage of graph topological properties. It relies on a blocks approach which captures local communities. Our split and merge algorithms allow to achieve load balancing of the workers and to maintain it dynamically. Our experiments illustrate the benefit of our partitioning since it significantly reduce the communication cost when performing random walks-based algorithms compared with existing approaches.

A desktop interface over distributed document repositories

The demonstration is devoted to the desktop-level interactions offered by Cador, a content-based document management system currently under development. Cador provides a rule-based language to query and manipulate large collections of documents distributed in repositories. The language is able to define the content of Virtual File Systems (VFS) as views over the document collections. This feature allows users to combine their familiar interface and desktop-based softwares with the powerful search and transformation tools provided by the underlying system. The demonstration shows how VFS views can be created on-demand to present a desktop-based virtual document organization and how standard desktop interactions can be captured and interpreted in terms of document management operations: creation, updates, annotation, derivation of new content thanks to transformation rules, sharing between users, etc. The example application is the management of a large bibliographic database: users can, with a few clicks, organize their bibliographic references, import new references, share them with a group of co-authors and automatically maintain a ready-to-use Bibtex file.

Collaborative cache based on path scores

Large-scale distributed data integration systems have to deal with important query processing costs which are essentially due to the high communication overload between data peers. Caching techniques can drastically reduce processing and communication cost.We propose a new distributed caching strategy that reduces redundant caching decisions of individual peers. We estimate cache redundancy by a distributed algorithmwithout additionalmessages. Our simulation experiments show that considering redundancy scores can drastically reduce distributed query execution costs.

Un modèle de classement de services par contribution et utilité

Service-oriented architectures (SOA) have become essential for building web applications due to the development of open standards which are compatible with the existing web technologies. The number of services on the web is growing every day and application developers are oftenly faced with the problem of choosing among the available services. We present a ranking model based on importance scores that reflects for each service its activity and its contribution to the quality of other services. We also present a distributed algorithm for computing these scores based on the existing connections between services. Our model and algorithms were validated by simulations.

SGVCut: A Vertex-Cut Partitioning Tool for Random Walks-based Computations over Social Network graphs

Several distributed frameworks have recently emerged to perform computations on large-scale graphs. However some recent studies have highlighted that vertex-partitioning approaches, e.g. Giraph, failed to achieve workload-balanced partitioning for skewed graphs, typically having a heavy-tail degree distribution. While edge-partitioning approaches such as PowerGraph and GraphX provide beter balancing and performances for graph computation, they supply a generic framework, independent from the computation. This demonstration presents SGVCut to display our edge partitions designed for random walks-based computation, which is the foundation of many graph algorithms, on skewed graphs. The demonstration scenario introduces SGVCut interface and illustrates the benefits of our approach compare to other partitioning strategies for different settings and algorithms.

Finding Users of Interest in Micro-blogging Systems

Micro-blogging systems have become a prime source of information. However, due to their unprecedented success, they have to face an exponentially increasing amount of user-generated content. As a consequence finding users who publish quality content that matches precise interest is a real challenge for the average user. This paper presents a new recommendation score which takes advantage both of the social graph topology and of the existing contextual information to recommend users to follow according to user interest. Then we introduce a landmark-based algorithm which allows to scale. The experimental results and the user studies that we conducted confirm the relevance of this recommendation score against concurrent approaches as well as the scalability of the landmark-based algorithm.