Kontera's contextual advertising network provides online publishers and advertisers with the most technologically advanced In Text Advertising solution and Information Services.
Kontera´s contextual advertising and information services are based on patent-pending technology, which utilizes several proprietary semantic, statistical, linguistic, and yield maximization algorithms. Our advanced algorithms analyze content, extract and rank topics and keywords, and then match them to the most relevant contextual ads, content, and information from among Kontera's thousands of advertisers and content providers.
Kontera’s contextual analysis technology is based on the principles of computational linguistics and enables uncovering topics, keywords, and overall meaning in a way that mimics human intent. Kontera’s topic and keyword selection, for the purpose of creating contextual advertising or information links, uses specific statistical algorithms that examine the level of relevancy, yield maximization, and conversions in order to refine the selection decisions as part of a continuous process.
Online Contextual Advertising
Kontera's Online Contextual Advertising Program is based on sophisticated technology which enables real- time analysis of static or dynamic content - such as blogs, forums, and user reviews (no crawling or index building are required). Furthermore, our online advertising technology can handle pages that search engines cannot crawl, such as password-protected sites, form-based content, and cookie authentication.
How Kontera’s contextual analysis engine works:
Extraction: A typical analysis process begins by extracting all the relevant page content and attributes, including: text, HTML properties, location on page, URL, Title, Meta tags, custom Meta tags, etc. Every such attribute conveys a specific weight to the algorithms that analyzes the data.
Discovery: The extracted data is then scanned through the discovery process in relationship to the proprietary taxonomy and via a dynamic part-of-speech analysis to identify keyword relationships and significance.
Classification: The page and its best matching keywords are classified with their best matching topics, and both keywords and topics are scored for relevancy.
Ranking: The resulting output of keywords and topics are then ranked, based not only on keyword and topic relevancy but on other parameters as well. These parameters include: topic and keyword conversion rate and click-through rate, advertisement CTR, advertisement conversion and revenue potential.
Self-Learning Optimization: The self-learning and tuning module automatically performs yield management and optimization. This process is based on real-time analysis of user reactions to specific keywords, topics, and ads as they relate to specific web pages and topics. In Text Ad impressions are then re-distributed in order to assign more impressions to the keywords that are performing better. This self-learning stage completes the cycle of Kontera´s contextual advertising technology granting it its unique competitive edge.
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