Marko Grobelnik Jozef Stefan Institute ( Ljubljana, Slovenia
Dealing with data Natural Language Processing Semantic Web Information Retrieval Machine Learning / Data Mining Databases Interoperability Storing / querying Text Model discovery Search Social Network Analysis Community
Integration of three key scientific paradigms ◦ Top-down approaches – model driven (Semantic Web, KRR, Traditional NLP) ◦ Bottom-up approaches – data driven (Machine Learning, Data Mining, Social Network Analysis, Information Retrieval, Modern NLP) ◦ Collaborative approaches – community driven (Web2.0, Social Computing) …integration of ideas from different paradigms opens possibilities to solve problems which were not easy solvable before
Scalability Dynamicity Context Quality Usage Research areas (such as IR, KDD, ML, NLP, SemWeb, …) are sub- cubes within the data cube
Can we learn from listed technologies?
Can we learn from listed technologies?
One possible conclusion: ◦ Future lies in uncovered parts of the data cube ◦ …note that items on data cube are changing Upcoming technology trends combine existing “healthy” technologies as building blocks