شماره ركورد كنفرانس :
3297
عنوان مقاله :
Imapct of machine learning on improvement of user experience in museums
عنوان به زبان ديگر :
Imapct of machine learning on improvement of user experience in museums
پديدآورندگان :
Majd Mahshid Computer engineering and IT Amirkabir University of Technology Tehran , Safabakhsh Reza Computer engineering and IT Amirkabir University of Technology Tehran
كليدواژه :
museum data analysis , automatic guide , museum experience , computer vision , machine learning application , Keywords-component
عنوان كنفرانس :
نوزدهمين سمپوزيوم بين المللي هوش مصنوعي و پردازش سيگنال
چكيده لاتين :
Utilizing new technologies is the key to improve user
experience in museums. Natural and unobtrusive methods like
those offered by machine learning approaches are more desired
by users. So far, the research on machine learning applications in
museums is mostly limited to art authentication, guiding
and virtual reality. Yet, machine learning has powerful methods
to extract information from any type of data and therefore there
are other interesting applications which can have a significant
effect on museum experience. The current work is an attempt to
find an abstract and yet elaborate view into the existing machine
learning applications in museums in general and automatic guide
methods in particular. To do so, applications are grouped into
different categories and for each category the usefulness of
applying machine learning along with the existing methods, if
any, are presented. Furthermore, a precise explanation on new
directions accompanied by examples is provided. We expect this
paper to be of interest to the machine learning researchers since
it provides a guideline to proper directions of research in this
realm.