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Semantic Web and Web Mining: Networking with Industry and Academia

Semantic Web and Web Mining: Networking with Industry and Academia. İsmail Hakkı Toroslu IST EVENT 2006. WWW: Related Subjects. Browsers and Search: browsers that are richer and more interactive improved search tools to explore and access complex and unstructured information on the Web.

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Semantic Web and Web Mining: Networking with Industry and Academia

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  1. Semantic Web and Web Mining:Networking with Industry and Academia İsmail Hakkı Toroslu IST EVENT 2006

  2. WWW: Related Subjects • Browsers and Search: • browsers that are richer and more interactive • improved search tools to explore and access complex and unstructured information on the Web

  3. WWW: Related Subjects • XML: • language of the Web • basis for many Web-based applications Used for • data exchange • to publish data from database systems (provides input to content generators). • Web Services: intra- and inter-enterprise application integration (e-commerce)

  4. WWW: Related Subjects • Semantic Web: to extend the current human-readable web by encoding the semantics of web-resources in a machine-interpretable form Used for • to automatically integrate data from different sources • to perform actions on behalf of the user • to search for information based on its meaning rather than its syntactic form.

  5. WWW: Related Subjects • Web Mining: to develop techniques to derive knowledge from data published in web-accessible formats Due to heterogeneity and lack of structure in web data automated discovery of targeted or unexpected knowledge becomes hard Related fields: data mining, machine learning, natural language processing, statistics, databases, information retrieval

  6. Issues: Browsers and Search • Search engine design and architecture • Basic search engine infrastructure: crawling, indexing, and query processing • Personalized search: location, context, activity-aware search • Query languages for Web data • Search interfaces: natural language interfaces, summarization, post processing tools, feedback • Search-motivated characterizations of the web • Meta-search and ranking

  7. Issues: XML and Web Services • Service contract and metadata • Orchestration, choreography, composition of services • Using formal methods on Web Services • Large scale XML data integration • XML query processing and data management • Web Engineering: tools and technologies for Web Services development, deployment, management Software methodologies for Service-Oriented Systems

  8. Issues: Semantic Web • Ontologies, ontology representation languages • Semantic annotation and metadata • Semantic integration and interoperability • Semantic search and retrieval • Semantic web services • Semantic web mining • Ontology learning

  9. Issues: Web Mining • Classification and clustering of web data • Web content mining • Web link structure mining • Web usage mining (log and web traffic analysis) • Building user profiles and providing recommendations • Change detection and monitoring methods for web data • Entity and relationship extraction and disambiguation • Privacy issues in web mining • Data integration and data cleaning • Integrating linguistic and domain knowledge in web mining

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