Novelty detection is the
mechanism by which an
intelligent organism
An organism is any life, living thing that functions as an individual. Such a definition raises more problems than it solves, not least because the concept of an individual is also difficult. Many criteria, few of them widely accepted, have be ...
is able to identify an incoming
sensory pattern as being hitherto unknown. If the pattern is sufficiently
salient or associated with a high positive or strong negative
utility
In economics, utility is a measure of a certain person's satisfaction from a certain state of the world. Over time, the term has been used with at least two meanings.
* In a normative context, utility refers to a goal or objective that we wish ...
, it will be given computational resources for effective future processing.
The principle is long known in
neurophysiology
Neurophysiology is a branch of physiology and neuroscience concerned with the functions of the nervous system and their mechanisms. The term ''neurophysiology'' originates from the Greek word ''νεῦρον'' ("nerve") and ''physiology'' (whic ...
, with roots in the
orienting response research by
E. N. Sokolov in the 1950s. The reverse phenomenon is
habituation
Habituation is a form of non-associative learning in which an organism’s non-reinforced response to an inconsequential stimulus decreases after repeated or prolonged presentations of that stimulus. For example, organisms may habituate to re ...
, i.e., the phenomenon that known patterns yield a less marked response. Early neural modeling attempts were by Yehuda Salu.
An increasing body of knowledge has been collected concerning the corresponding mechanisms in the brain. In technology, the principle became important for
radar detection methods during the Cold War, where unusual aircraft-reflection patterns could indicate an attack by a new type of aircraft. Today, the phenomenon plays an important role in
machine learning
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of Computational statistics, statistical algorithms that can learn from data and generalise to unseen data, and thus perform Task ( ...
and
data science
Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processing, scientific visualization, algorithms and systems to extract or extrapolate knowledge from potentially noisy, stru ...
, where the corresponding methods are known as
anomaly detection or outlier detection. An extensive methodological overview is given by Markou and Singh.
See also
*
Change detection
*
Outlier
In statistics, an outlier is a data point that differs significantly from other observations. An outlier may be due to a variability in the measurement, an indication of novel data, or it may be the result of experimental error; the latter are ...
*
Reward system
The reward system (the mesocorticolimbic circuit) is a group of neural structures responsible for incentive salience (i.e., "wanting"; desire or craving for a reward and motivation), associative learning (primarily positive reinforcement and c ...
References
{{Reflist, 30em
Neurophysiology
Experimental psychology
Machine learning
Data mining
Statistical outliers