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INTRODUCTION TO AI-BASED SEARCH ENGINE MODELING ©2021 rewco Inc. 8 + CREATING A SEARCH ENGINE MODEL: TRAINING DATA To build a model, you need to train it. Our approach has been to reverse the process used by the search engine that we’re modeling. Search engines evaluate page and site features against their algorithms and produce a SERP.
31 lip 2024 · Guide to building a vector-based search engine with pre-trained transformers, from loading models to accelerating search.
1 maj 2012 · This paper presents Moogle, a model search engine that uses metamodeling information to create richer search indexes and to allow more complex queries to be performed.
27 gru 2021 · In the previous work, we presented MAR, a search engine for models which has been designed to support a query-by-example mechanism with fast response times and improved precision over simple...
26 cze 2014 · In this paper, we present a learning based search engine that uses supervised machine learning techniques like selection based and review based algorithms to construct a ranking model.
In this paper we present MAR, a search engine for models. MAR is generic in the sense that it can index any type of model if its meta-model is known. MAR uses a query-by-example approach, that is, it uses example models as queries.
Given a dataset, an attribute of that dataset to predict, and a space of possible model configurations to consider, the goal of model search is to find a supervised learning model that will provide good predictions for the attribute of interest on unseen data—that is, a model with low generalization error.
