Engine Scoring & Predictive Analytics to Boost Search Accuracy

With Big Data, it is possible to harvest user event data, such as search and click logs, for the purpose of computing user-based search accuracy metrics. Learn about the algorithms and processes for computing these metrics which are vital for comparing search engine accuracy before a deployment.

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With Big Data, it is possible to harvest user event data, such as search and click logs, for the purpose of computing user-based search accuracy metrics. Learn about the algorithms and processes for computing these metrics which are vital for comparing search engine accuracy before a deployment.

Paul Nelson

Paul was an early pioneer in the field of text retrieval and has worked on search engines for over 25 years. He was the architect and inventor of RetrievalWare, a ground-breaking natural-language based statistical text search engine which he started in 1989 and grew to $50 million in annual sales worldwide. RetrievalWare is now owned by Microsoft Corporation. During his many years in the industry, Paul has been involved in hundreds of text search installations of all shapes and sizes. This includes enterprise search for dozens of fortune 500 corporations as well as large government installations for the National Archives and Records Administration (NARA) and the Government Printing Office (GPO). Paul is the Chief Architect at Search Technologies where he provides architectural oversight for clients’ projects and conducts design, technology research and training.