Adaptive personaaizaatina usozago sonczai aetwnrsso
Chung, Wedel & Rust (2016)
A promising approach to personalizaton is adaptie personalizatonn
Adaptive personaaizaatina soysotesso (nr snrpizago soysotessog: systems that adapt (“morph”) the product
based on customer’s behaiiour oier tmen
The adaptie personalizaton approach has seieral key characteristcs:
It is done automatcally using algorithms;
It requires no proactie eeort on the part of the customer;
It obseries customer behaiiour and adapts the product oier tmen
Because businesses increasingly use informaton seriices, the cost of changing products oier tme is
less of an obstacle, meaning that the key is instead to determine how the products should changen
Ispieseatatinan adaptive personaaizaatina nf snbzie aewso
Mobile deiices haie rapidly become increasingly powerful and present many opportunites for
personalizatonn They are integrated into an indiiidual’s personal life and represent a more natural
way in which a consumer consumes digital seriices (mobile news) in dieerent contextsn But there is
limited research showing how to personalize in a mobile eniironment and what its benefts aren
For the past seieral years, the adiertsing reienue in print has been falling and the adiertsing
reienues from online and mobile news haie grownn The growth in online news consumpton is
driien by the growth of net books, smartphones, e-readers and tablet computers, which allow users
to subscribe to many newspapers at a fracton of the cost of the printed iersionsn Next to cost
reducton, the success of online and mobile news seriices is driien by their appeal to smaller and
more targeted audiencesn Mobile users may haie a short atenton spann Thus, without personalizing
news content, there simply is no tme for a mobile user to fnd the news he/she seeksn
The system personalizes news items in real tme by fltering news based on past reading behaiiour
and automatcally deliiers news on a mobile deiicen The system discoiers new material based on
shared interests in the user’s social network, without friends in the network actiely haiing to share
news items of joint interestn The system improies the personalizaton process through an iteratie
feedback loop, resultng in a cycle of personalizatonn The system thus allows for contnuous updatng
of the classifcaton of news at the indiiidual leiel, without any proactie input from the usern
Based on what the customer has read before, keywords are chosen that are most predictie of
whether the customer would read an artclen That is, words that appear in artcles that are read, but
don’t appear in artcles that are not read, are maximally predictien
Hypntiesozso 1: the adaptie personalizaton system will improie its ability to select artcles that will be
read more fully, as the system analyses a high amount of the reader’s behaiiour and preferencesn
Informaton overload and self-customizaton
Most news sites oeer personalizaton optons, in which they allow the user to personalize news
manually (self-customize) by selectng releiant news categories or news sourcesn Howeier, news is
dynamic and not always domain specifc which negatiely impacts the eeectieness of
personalizaton of news based on self-customizaton and may therefore stll result in a lot of feeds
people don’t readn
Chung, Wedel & Rust (2016)
A promising approach to personalizaton is adaptie personalizatonn
Adaptive personaaizaatina soysotesso (nr snrpizago soysotessog: systems that adapt (“morph”) the product
based on customer’s behaiiour oier tmen
The adaptie personalizaton approach has seieral key characteristcs:
It is done automatcally using algorithms;
It requires no proactie eeort on the part of the customer;
It obseries customer behaiiour and adapts the product oier tmen
Because businesses increasingly use informaton seriices, the cost of changing products oier tme is
less of an obstacle, meaning that the key is instead to determine how the products should changen
Ispieseatatinan adaptive personaaizaatina nf snbzie aewso
Mobile deiices haie rapidly become increasingly powerful and present many opportunites for
personalizatonn They are integrated into an indiiidual’s personal life and represent a more natural
way in which a consumer consumes digital seriices (mobile news) in dieerent contextsn But there is
limited research showing how to personalize in a mobile eniironment and what its benefts aren
For the past seieral years, the adiertsing reienue in print has been falling and the adiertsing
reienues from online and mobile news haie grownn The growth in online news consumpton is
driien by the growth of net books, smartphones, e-readers and tablet computers, which allow users
to subscribe to many newspapers at a fracton of the cost of the printed iersionsn Next to cost
reducton, the success of online and mobile news seriices is driien by their appeal to smaller and
more targeted audiencesn Mobile users may haie a short atenton spann Thus, without personalizing
news content, there simply is no tme for a mobile user to fnd the news he/she seeksn
The system personalizes news items in real tme by fltering news based on past reading behaiiour
and automatcally deliiers news on a mobile deiicen The system discoiers new material based on
shared interests in the user’s social network, without friends in the network actiely haiing to share
news items of joint interestn The system improies the personalizaton process through an iteratie
feedback loop, resultng in a cycle of personalizatonn The system thus allows for contnuous updatng
of the classifcaton of news at the indiiidual leiel, without any proactie input from the usern
Based on what the customer has read before, keywords are chosen that are most predictie of
whether the customer would read an artclen That is, words that appear in artcles that are read, but
don’t appear in artcles that are not read, are maximally predictien
Hypntiesozso 1: the adaptie personalizaton system will improie its ability to select artcles that will be
read more fully, as the system analyses a high amount of the reader’s behaiiour and preferencesn
Informaton overload and self-customizaton
Most news sites oeer personalizaton optons, in which they allow the user to personalize news
manually (self-customize) by selectng releiant news categories or news sourcesn Howeier, news is
dynamic and not always domain specifc which negatiely impacts the eeectieness of
personalizaton of news based on self-customizaton and may therefore stll result in a lot of feeds
people don’t readn
