Cms topss efficient dissemination of rss documents
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CMS-ToPSS: Efficient Dissemination of RSS Documents. Milenko Petrovic Haifeng Liu Hans-Arno Jacobsen University of Toronto. Information Dissemination. Easy to use web publishing tools (blog, wiki) are fueling the increase in the number of web publishers

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CMS-ToPSS: Efficient Dissemination of RSS Documents

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Cms topss efficient dissemination of rss documents

CMS-ToPSS: Efficient Dissemination of RSS Documents

Milenko Petrovic Haifeng Liu Hans-Arno Jacobsen

University of Toronto

VLDB2005


Information dissemination

Information Dissemination

  • Easy to use web publishing tools (blog, wiki) are fueling the increase in the number of web publishers

  • RSS frequently used to disseminate update to interested users

    • CNN.com, Yahoo! News, Amazon.com, MSN search (beta)

Problem:Polling based architecture

RSSreaders

RSSpublishers

RSSaggregator

VLDB05


Solution

Solution!

Current rss dissemination architecture

G-ToPSS rss dissemination architecture

VLDB05


Interaction model publish subscribe

MatchingRSS feeds

MatchingRSS feeds

Interaction Model: Publish/Subscribe

Publisher

Publisher

RSS feeds

Broker

Queries over all RSS

Subscriber

Subscriber

VLDB05


Research challenges

Research challenges

  • Need a subscription (query) language suitable for filtering of rss documents

  • Need an efficient matching algorithm based on graph representation

    • Structurally matching

    • Constraint matching

  • Scalability to a large number of subscriptions and high publishing rate

  • VLDB05


    Cms topss system architecture

    CMS-ToPSS System Architecture

    VLDB05


    Subscription scalability

    Subscription Scalability

    VLDB05


    Memory scalability

    Memory Scalability

    VLDB05


    Matching semantics

    Matching Semantics

    PAPER17

    Publication

    ?y(?y <= Publication)

    AUTHOR

    CONFERENCE

    AUTHOR

    CONFERENCE

    “Arno Jacobsen”

    SIGMOD

    SIGMOD

    “Arno Jacobsen”

    YEAR

    “2001”

    YEAR

    LOCATION

    “California”

    ?z(?z > 2000)

    Subscription

    VLDB05


    Data model rss documents

    Data Model (RSS Documents)

    • Publications are represented as directed graphs with node and edge labels

    • Node labels are typed

      • Literal value

      • Class

    • Edge labels are typed

      • Class

    • Classes can be related using multiple inheritance ontology

    VLDB05


    Query language gql

    Query Language (GQL)

    • Queries are represented as directed graph patternswith node and edge labels

    • Node labels are variables

    • Variables can be constrained by

      • Classes

      • Class instances and literal values

    • Edge labels are class instances

    • Mapping (matching) semantics

      • Pattern graph maps to data graph if the topology (structure) of the two graphs matches and all variable constraints are satisfied

    VLDB05


    Conclusion and future work

    Conclusion and Future Work

    • Proposed a prototype for graph-based metadata filtering

    • G-ToPSS supports high matching rate for an expressive subscription language

    • Extend G-ToPSS with full RDF language features

    • Optimize constraint processing during matching

    VLDB05


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