Stream Cube: An Architecture for Multi-Dimensional Analysis of Data Streams
Distributed and Parallel Databases
OLAP over imprecise data with domain constraints
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Supporting OLAP operations over imperfectly integrated taxonomies
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Graph OLAP: Towards Online Analytical Processing on Graphs
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Text Cube: Computing IR Measures for Multidimensional Text Database Analysis
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
BaseX & DeepFS joint storage for filesystem and database
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
XQuery Full Text Implementation in BaseX
XSym '09 Proceedings of the 6th International XML Database Symposium on Database and XML Technologies
Using twitter to recommend real-time topical news
Proceedings of the third ACM conference on Recommender systems
Short and tweet: experiments on recommending content from information streams
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
TwitterMonitor: trend detection over the twitter stream
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Streaming first story detection with application to Twitter
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Discovering users' topics of interest on twitter: a first look
AND '10 Proceedings of the fourth workshop on Analytics for noisy unstructured text data
Journal of the American Society for Information Science and Technology
Tweets from Justin Bieber's heart: the dynamics of the location field in user profiles
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Towards an on-line analysis of tweets processing
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
Towards an advanced system for real-time event detection in high-volume data streams
Proceedings of the 5th Ph.D. workshop on Information and knowledge
Discovering dynamic classification hierarchies in OLAP dimensions
ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems
A text cube approach to human, social and cultural behavior in the twitter stream
SBP'13 Proceedings of the 6th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction
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Social networks are platforms where millions of users interact frequently and share variety of digital content with each other. Users express their feelings and opinions on every topic of interest. These opinions carry import value for personal, academic and commercial applications, but the volume and the speed at which these are produced make it a challenging task for researchers and the underlying technologies to provide useful insights to such data. We attempt to extend the established OLAP(On-line Analytical Processing) technology to allow multidimensional analysis of social media data by integrating text and opinion mining methods into the data warehousing system and by exploiting various knowledge discovery techniques to deal with semi-structured and unstructured data from social media. The capabilities of OLAP are extended by semantic enrichment of the underlying dataset to discover new measures and dimensions for building data cubes and by supporting up-to-date analysis of the evolving as well as the historical social media data. The benefits of such an analysis platform are demonstrated by building a data warehouse for a social network of Twitter, dynamically enriching the underlying dataset and enabling multidimensional analysis.