Large-scale, Cross-lingual Trend Mining and Summarization of Real-time Media Streams

TrendMiner (Large-scale, Cross-lingual Trend Mining and Summarization of Real-time Media Streams) is a three-years European project funded by the European Commission through the Seventh Research Framework Program (FP7-ICT) and under Project No 287863. The project starts in November 2011 and since May 2012, is supported by the company Internet Memory Research via its platform mignify (more information)

The recent massive growth in online media and the rise of user-authored content (e.g weblogs, Twitter, Facebook) has lead to challenges of how to access and interpret these strongly multilingual data, in a timely, efficient, and affordable manner. Scientifically, streaming online media pose new challenges, due to their shorter, noisier, and more colloquial nature. Moreover, they form a temporal stream strongly grounded in events and context. Consequently, existing language technologies fall short on accuracy, scalability and portability.
The goal of this project is to deliver innovative, portable open-source real-time methods for cross-lingual mining and summarization of large-scale stream media.
TrendMiner will achieve this through an inter-disciplinary approach, combining deep linguistic methods from text processing, knowledge-based reasoning from web science, machine learning, economics, and political science. No expensive human annotated data will be required due to our use of time-series data (e.g. financial markets, political polls) as a proxy. A key novelty will be weakly supervised machine learning algorithms for automatic discovery of new trends and correlations. Scalability and affordability will be addressed through a cloud-based infrastructure for real-time text mining from stream media.
Results will be validated in two high-profile case studies: financial decision support (with analysts, traders, regulators, and economists) and political analysis and monitoring (with politicians, economists, and political journalists).
The techniques will be generic with many business applications: business intelligence, customer relations management, community support. The project will also benefit society and ordinary citizens by enabling enhanced access to government data archives, summarization of online health information, and tracking of hot societal issues.

In this project, Internet Memory contributes to the Platform for Real Time Media collection, Analysis and storage by :
- providing our scalable infrastructure to partners, with support for integration and experiment.
- designing and developing an application-aware crawler mechanism for social medias.

The TrendMiner project is headed by the Deutsches Forschungszentrum für Künstliche Intelligenz GmbH(Germany).
Beside Internet Memory, The University of Sheffield (United Kingdom), Ontotext AD (Bulgaria), University of Southampton (UK), Eurokleis S.R.L. (Italy), Sora Ogris & Hofinger GmbH (Austria) and Hardik Fintrade Pvt Ltd. (India) are involved.


For more information on TrendMiner, please visit the Project website.