Download Multi-Relational Data Mining

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
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)
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.
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
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
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
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
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