Transforming a Business Model Based on Data Matching Solutions (Round 6)
HungaryProject type: largeCM Investment Ltd
Major Hungarian news site 24.hu will reinvent its business model by building two connected technological capabilities. A new automatic tagging solution will be developed and implemented to improve archive utilisation, content recommendation and advertising features. This technology utilises machine learning and natural language processing to provide an objective and efficient tagging of all content. In parallel, a single sign-on solution will be launched. This will empower users to control their topic preferences, personalise front pages, newsletters and app features. Combining these technological deliverables can provide basis to rationalise cost base and create new revenue streams.
As there is currently no off-the-shelf NLP solution is available for the Hungarian language, the common practice is to use manual tagging for content rather than automated one. This creates subjective tags, tag-overlaps, non-relevant tag groups and mainly word-based tags, rather than relevant topics/themes organised in a structured manner. Moreover, 24.hu is constrained by cookie-data for personalisation as no sign-on solution is deployed. Machine learning-based automatic tagging will improve accuracy, recommendation relevance and archive utilisation. Single sign-on on the 24.hu satellite network can add personalisation skills and unlock better targeting capabilities.
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