RoSeS A continuous content based query engine for RSS feeds

Description

Niveau: Supérieur, Doctorat, Bac+8
RoSeS : A continuous content-based query engine for RSS feeds Jordi Creus1, Bernd Amann1, Nicolas Travers2, and Dan Vodislav3 1 LIP6, CNRS – Universite Pierre et Marie Curie, Paris, France 2 Cedric/CNAM – Conservatoire National des Arts et Metiers, Paris, France 3 ETIS, CNRS – University of Cergy-Pontoise, Cergy, France Abstract. In this article we present RoSeS (Really Open Simple and Efficient Syndication), a generic framework for content-based RSS feed querying and ag- gregation. RoSeS is based on a data-centric approach, using a combination of 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. Pub- lishing 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 article are a declara- tive RSS feed aggregation language, an extensible stream algebra for building efficient continuous multi-query execution plans for RSS aggregation views, a multi-query optimization strategy for these plans and a running prototype based on a multi-threaded asynchronous execution engine. 1 Introduction In its origins the Web was a collection of semi-structured (HTML) documents con- nected by hypertext links.

• rss feeds


• main feed


• prototype based


• query plan


• rss aggregation


• language


• aggregating rss streams


• rss views


• roses


• interfaces like

Sujets

• Google
• Agence nationale de la recherche
• France 2
• Prototype-based programming
• Query plan
• Language

Informations

• Publié par: profil-zyak-2012
• Nombre de lectures: 16
• Langue: English
• Poids de l'ouvrage: 2 Mo

Extrait

RoSeS:Acontinuouscontent-basedqueryenginefor RSSfeeds JordiCreus 1 ,BerndAmann 1 ,NicolasTravers 2 ,andDanVodislav 3 1 LIP6,CNRS–Universite ´ PierreetMarieCurie,Paris,France 2 Cedric/CNAM–ConservatoireNationaldesArtsetMe´tiers,Paris,France 3 ETIS,CNRS–UniversityofCergy-Pontoise,Cergy,France Abstract.Inthisarticlewepresent RoSeS (ReallyOpenSimpleandEfficient Syndication),agenericframeworkforcontent-basedRSSfeedqueryingandag- gregation. RoSeS isbasedonadata-centricapproach,usingacombinationof standarddatabaseconceptslikedeclarativequerylanguages,viewsandmulti- queryoptimization.Userscreatepersonalizedfeedsbydefiningandcomposing content-basedfilteringandaggregationqueriesoncollectionsofRSSfeeds.Pub- lishingthesequeriescorrespondstodefiningviewswhichcanthenbeusedfor buildingnewqueries/feeds.Thisnaturallyreflectsthepublish-subscribenature ofRSSapplications.Thecontributionspresentedinthisarticleareadeclara- tiveRSSfeedaggregationlanguage,anextensiblestreamalgebraforbuilding efficientcontinuousmulti-queryexecutionplansforRSSaggregationviews,a multi-queryoptimizationstrategyfortheseplansandarunningprototypebased onamulti-threadedasynchronousexecutionengine. 1Introduction InitsoriginstheWebwasacollectionofsemi-structured(HTML)documentscon- nectedbyhypertextlinks.Thisvisionhasbeenvalidformanyyearsandthemaineffort forfacilitatingaccesstoandpublishingwebinformationwasinvestedinthedevelop- mentofexpressiveandscalablesearchenginesforretrievingpagesrelevanttouser queries.Morerecently,newwebcontentpublishingandsharingapplicationsthatcom- binemodernsoftwareinfrastructures(AJAX,webservices)andhardwaretechnologies (handheldmobileuserdevices)appearedonthescene.Thewebcontentspublishedby theseapplicationsisgenerallyevolvingveryrapidlyintimeandcanbestbecharac- terizedbyastreamofinformationentities.GoogleNews,FacebookandTwitterare amongthemostpopularexamplesofsuchapplications,butthelistofwebapplications generatingmanydifferentkindsofinformationstreamsisincreasingeveryday. InourworkweareinterestedinRSSandATOMasstandardformatsforpublish- inginformationstreams.Bothformatscanbeconsideredasthecontinuouscounterpart ofstaticHTMLdocumentsforencodingsemi-structureddatastreamsinformofdy- namicallyevolvingdocumentscalledfeeds.Theybothuseverysimilardatamodels TheauthorsacknowledgethesupportoftheFrenchAgenceNationaledelaRecherche(ANR), undergrantROSES(ANR-07-MDCO-011)“ReallyOpen,SimpleandEfficientSyndication”