use case: Improving video recom­men­da­tions

How do I create better sugges­tions based on viewing behavior without a compre­hensive user profile? 

the challenge

Improving video recom­men­da­tions

Every video platform aims to offer its users the best and most individual customer experience in order to stand out from the multitude of competitors. They want to increase the time spent on the site and the rate of inter­action with adver­tise­ments. These goals can only be achieved with an accurate and reliable recom­men­dation system that goes beyond video titles or video descrip­tions. Can DeepVA help me to provide better recom­men­da­tions?

DeepVA Deep Explorer Better video recommendations

the solution

Deep Explorer

The DeepVA Deep Explorer enriches a media archive with demographic and factual knowledge and enables a recom­men­dation system via an extensive AI-based analysis of the visual material. This happens with regard to relation­ships and similar­ities between assets, which in terms of its quality clearly goes beyond the pure inter­action of the user via time or frequency. The combi­nation of user data and metadata from the latest AI technology makes this system so precise and reliable.

The system can be used on-premise or in the cloud. If it is to be part of a workflow, integration is required. Via our RESTful API, it can be easily integrated in any existing system or workflow. Data protection require­ments usually play a major role in this decision and should be considered. 

What results can be obtained?

Better products for users: provide context and details

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faster data acqui­sition

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COST REDUCTION

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faster labelling

Improving video recom­men­da­tions

Function overview

Knowledge Graph

Recog­nizes the relation­ships between people or objects, repre­sents them visually, and thus helps to stay one step ahead of the compe­tition.

Fabian Linder

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