Sentence examples for machine learning information from inspiring English sources

The development of systems to retrieve relevant biomedical documents on a specific topic is a scientific effort that needs contributions mainly from areas that involve machine learning, information retrieval, information extraction and natural language processing.

In the area of machine learning, information sharing among tasks is a well-known technique [25].

Taxonomy trees are used in machine learning, information retrieval, bioinformatics, and multi-agent systems for matching as well as matchmaking in e-business, e-marketplaces, and e-learning.

Several different research fields deal with text, such as text mining, computational linguistics, machine learning, information retrieval, semantic web and crowdsourcing.

Basically, to even begin to tackle ad targeting, you need top-notch data scientists with PhDs in Machine Learning, Information Retrieval or other AI fields.

The traditional improvement process is extended to benefit extensively from machine learning, information retrieval and information extraction technologies to assist the wind tunnel engineers with difficult tasks.

Applying machine learning algorithms to information in the form of refined data presents the opportunity to both train and validate the data to accomplish different tasks.

The proposed framework combines multiple forecasting models and adaptive machine learning techniques for information processing.

Machine learning methods for information extraction became prevalent in the late 1990s and early 2000s with the introduction of Maximum Entropy Markov Models (MEMM) [3] and Conditional Random Fields (CRF) [4].

Machine learning applied to information from a disease-specific (cancer) database and the EAR can be used to predict clinical outcomes.

In conclusion, machine learning applied to information from a disease-specific (cancer) database and the EAR can be used to predict outcomes.