Nicolas Travers

RoSeS: a continuous content-based query engine for RSS feeds

In this paper we present RoSeS (Really Open Simple and Efficient Syndication), a generic framework for content-based RSS feed querying and aggregation. RoSeS is based on a data-centric approach, using a combination of standard database concepts like declarative query languages, views and multiquery optimization. Users create personalized feeds by defining and composing content-based filtering and aggregation queries on collections of RSS feeds. Publishing these queries corresponds to defining views which can then be used for building new queries / feeds. This naturally reflects the publish-subscribe nature of RSS applications. The contributions presented in this paper are a declarative RSS feed aggregation language, an extensible stream algebra for building efficient continuous multi-query execution plans for RSS aggregation views, a multiquery optimization strategy for these plans and a running prototype based on a multi-threaded asynchronous execution engine.

WebContent: efficient P2P Warehousing of web data

We present the WebContent platform for managing distributed repositories of XML and semantic Web data. The platform allows integrating various data processing building blocks (crawling, translation, semantic annotation, full-text search, structured XML querying, and semantic querying), presented as Web services, into a large-scale efficient platform. Calls to various services are combined inside ActiveXML [8] documents, which are XML documents including service calls. An ActiveXML optimizer is used to: (i) efficiently distribute computations among sites; (ii) perform XQuery-specific optimizations by leveraging an algebraic XQuery optimizer; and (iii) given an XML query, chose among several distributed indices the most appropriate in order to answer the query.

TGV: a tree graph view for modeling untyped XQuery

Tree Pattern Queries [7,6] are now well admitted for modeling parts of XML Queries. Actual works only focus on a small subpart of XQuery specifications and are not well adapted for evaluation in a distributed heterogeneous environment. In this paper, we propose the TGV (Tree Graph View) model for XQuery processing. The TGV model extends the Tree Pattern representation in order to make it intuitive, has support for full untyped-XQuery queries, and for optimization and evaluation. Several types of Tree Pattern are manipulated to handle all XQuery requirements. Links between Tree Patterns are called hyperlinks in order to apply transformations on results. The TGV has been implemented in a mediator system called XLive.

RSS feeds behavior analysis, structure and vocabulary

Purpose – The purpose of this paper is to present a thorough analysis of three complementary features of real-scale really simple syndication (RSS)/Atom feeds, namely, publication activity, items characteristics and their textual vocabulary, that the authors believe are crucial for emerging Web 2.0 applications. Previous works on RSS/Atom statistical characteristics do not provide a precise and updated characterization of feeds’ behavior and content, characterization that can be used to successfully benchmark the effectiveness and efficiency of various Web syndication processing/analysis techniques. Design/methodology/approach – The authors empirical study relies on a large-scale testbed acquired over an eight-month campaign from 2010. They collected a total number of 10,794,285 items originating from 8,155 productive feeds. The authors deeply analyze feeds productivity (types and bandwidth), content (XML, text and duplicates) and textual content (vocabulary and buzz-words). Findings – The findings of the...

Content-Based Publish/Subscribe System for Web Syndication

Content syndication has become a popular way for timely delivery of frequently updated information on the Web. Today, web syndication technologies such as RSS or Atom are used in a wide variety of applications spreading from large-scale news broadcasting to medium-scale information sharing in scientific and professional communities. However, they exhibit serious limitations for dealing with information overload in Web 2.0. There is a vital need for efficient real-time filtering methods across feeds, to allow users to effectively follow personally interesting information. We investigate in this paper three indexing techniques for users’ subscriptions based on inverted lists or on an ordered trie for exact and partial matching. We present analytical models for memory requirements and matching time and we conduct a thorough experimental evaluation to exhibit the impact of critical parameters of realistic web syndication workloads.

FiND: a real-time filtering by novelty and diversity for publish/subscribe systems

Content syndication has become a popular way for timely delivery of frequently updated information on the Web. It essentially enhances traditional pull-oriented searching and browsing of web pages with push-oriented protocols. However many Web syndication applications imply a tight coupling between feed producers and consumers and do not help users to find, in all information they received, items with interesting and new content. We present the FiND Pub/Sub system which integrates an in-memory filtering process based on keyword subscriptions. Unlike existing proposals, FiND is designed for real-time notifications on item streams. This demonstration illustrates the main features of the FiND system namely (i) a scalable real-time notification process when the most important terms of the subscription are matched, (ii) a tunable filtering by novelty and diversity to reduce user flooding.

RoSeS: a continuous query processor for large-scale RSS filtering and aggregation

We present RoSeS, a running system for large-scale content-based RSS feed filtering and aggregation. The implementation of RoSeS is based on standard database concepts like declarative query languages, views and multi-query optimization. Users create personalized feeds by defining and composing content-based filtering and aggregation queries on collections of RSS feeds. These queries are translated into continuous multi-query execution plans which are optimized using a new cost-based multi-query optimization strategy.

Querying Music Notation

We consider the emerging field of music score libraries, where documents rely on a music notation markup language such as MusicXML or MEI. We propose to model as synchronized time-series the music structure that can be extracted from such documents, together with an algebra that operates in closed form and allows manipulations, restructurings, and combinations of music scores stored in a database. We formally present the model, its algebraic operators, and finally show how our approach can serve as a building block for a query and analytic language on large collections of XML-encoded music scores.

TDV-based Filter for Novelty and Diversity in a Real-time Pub/Sub System

Publish/Subscribe (Pub/Sub) systems have been designed to face the exponential growth of information published on the Web by subscribing to sources of interest which produce flows of items. However users may receive some information several times, or information that does not contain any new content, and conversely miss some information of interest hidden in all information received. Pub/Sub systems are consequently witnessing a real challenge to efficiently filter relevant information. We propose in this paper a scalable approach for filtering news (items) which match the user interests (expressed as subscriptions). Introducing for the first time Term Discrimination Value (TDV) in this context, which allows to measure how a term discrimines an item, we filter out in real-time items whose content has already been notified recently to the user, either in another item (filtering by novelty) or globally in his recent history (filtering by diversity). Our experiments illustrate the impact of our different parameters and confirm the scalability of our approach and the relevance of the results notified.

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.