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Semantic Search on Heterogeneous Wiki Systems - Short
Semantic Search on Heterogeneous Wiki Systems - Short
Semantic Search on Heterogeneous Wiki Systems - Short
Semantic Search on Heterogeneous Wiki Systems - Short
Semantic Search on Heterogeneous Wiki Systems - Short
Semantic Search on Heterogeneous Wiki Systems - Short
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Semantic Search on Heterogeneous Wiki Systems - Short

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@ NUI Galway - Research Day …

@ NUI Galway - Research Day
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Published in: Technology, Education
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  • 1. Semantic Search on Heterogeneous Wiki Systems Fabrizio Orlandi, Alexandre Passant USS, Unit Social Software NUI Galway – Research Day 15-04-2010
  • 2. Background <ul><li>Social software allows people to connect, communicate or collaborate on the Web. Popular systems are discussion forums , blogs , wikis and online social networks </li></ul><ul><li>A wiki is a website that allows the easy and collaborative creation of any number of interlinked web pages via a web browser </li></ul><ul><li>Wikis are widely used both on the Web </li></ul><ul><li>( e.g. Wikipedia ) </li></ul><ul><li>and in the workplace </li></ul><ul><li>( e.g. project management or customer relationships) </li></ul><ul><li>By utilising Semantic Web technologies in social software systems, we can create new methods for connecting people to other people and also to the information that they have created </li></ul>
  • 3. Motivations <ul><li>All wikis share a wide common knowledge , but they have different structures and implementations, platform dependent </li></ul><ul><li>They act as isolated systems , where information from one system cannot be easily integrated with information from another one </li></ul><ul><li>Several semantic models implemented within specific semantic wiki platforms </li></ul><ul><li>But they are all specific to wikis and not open to other social websites </li></ul><ul><li>We propose a new approach based on Linked Data principles to solve such issues and to enable semantic search across heterogeneous wiki systems </li></ul>
  • 4. Our Contribution <ul><li>We developed a system to enable semantic search across heterogeneous wikis in a unified way using Semantic Web technologies </li></ul><ul><li>I ) We designed a common semantic model , based on the SIOC ontology, for representing wiki structure and contributions in RDF - Resource Description Framework - encompassing previous models in the area </li></ul><ul><li>II ) We extracted semantic data from wikis developing data exporters for popular wiki systems, translating wiki information in RDF annotations (based on our model) in real-time </li></ul><ul><li>III )We built an efficient application with a user-friendly interface enabling semantic searching and browsing capabilities on the top of different interlinked wikis </li></ul>
  • 5. Results <ul><li>In total we collected more that 3000 wiki articles and 700 users from 5 different wiki sites </li></ul><ul><li>The system is capable to answer queries like: </li></ul><ul><li>“ What are the co-authors of user X and on which articles they collaborate?” </li></ul><ul><li>“ What are the topics and the wiki sites the user X contributed most in the past six months?” </li></ul><ul><li>The presented application allows for advanced and fast querying processes and hidden knowledge discovery </li></ul><ul><li>By applying Semantic Web technologies to wikis we show potentialities that cannot be obtained using the traditional Web 2.0 instruments </li></ul>
  • 6. Conclusions and Future Work <ul><li>We showed an overall benefit on applying Semantic Web technologies to wikis, enabling end-users to access the information generated by this process in a simple and transparent way </li></ul><ul><li>The presented work goes exactly in the direction of creating a collective knowledge system on the Web in accordance to the Linking Open Data project </li></ul><ul><li>Future work: </li></ul><ul><ul><li>To develop this system as a stable online web service </li></ul></ul><ul><ul><li>To provide more details about the content of wiki articles </li></ul></ul><ul><ul><li>To add to the system architecture a real-time search functionality </li></ul></ul>

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