CONTENT SELECTION FOR MOBILE DEVICE

• US 20170024815A1
• Filed: 03/04/2015
• Published: 01/26/2017
• Est. Priority Date: 03/13/2014
• Status: Active Grant

• Current Assignee: Op-Palvelut Oy (OP Financial Group)
• Original Assignee: Op-Palvelut Oy (OP Financial Group)
• Inventors: JOMPPANEN, Tuomas, JUNTUNEN, Jussi
• Granted Patent: US 10,565,650 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/109 Time management, e.g. calendars, reminders, meetings or time accounting
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

Content selection for a mobile device. An apparatus obtains classified weekly consumption data of a consumer, calculates for each consumption class a relative daily value for each day of the week, calculates for each consumption class a content relevance probability in a selected day of the week on the basis of a relative daily value of the selected day of the week affected by a relative daily value of at least one day following the selected day of the week, controls a content selection for the consumer on the selected day of the week on the basis of the calculated content relevance probabilities for the selected day, and transmits the selected content to a mobile device of the consumer on the selected day.

Claims

1-12. -12. (canceled)

13. An apparatus comprising

one or more processors, and

one or more memories including computer program code,

the one or more memories and the computer program code configured to, with the one or more processors, cause the apparatus at least to:

obtain classified weekly consumption data of a consumer, the classified weekly consumption data comprising daily consumption classes for each day of the week;

calculate for each consumption class a relative daily value for each day of the week such that the relative daily value is the sum of the payments in the consumption class during the day in proportion to the sum of the payments in all consumption classes during said day;

calculate for each consumption class a content relevance probability in a selected day of the week on the basis of a relative daily value of the selected day of the week affected by a relative daily value of at least one day following the selected day of the week;

control a content selection for the consumer on the selected day of the week on the basis of the calculated content relevance probabilities for the selected day; and

transmit the selected content to a mobile device of the consumer on the selected day.

14. The apparatus of claim 13, wherein the classified weekly consumption data is based on payments of trades of various commodities during at least one week.

15. The apparatus of claim 13, wherein the classified weekly consumption data is based on payments of trades of various commodities during a fortnight, four weeks, eight weeks, twelve weeks, one month, two months, three months, six months, or one year.

16. The apparatus of claim 13, wherein each daily consumption class includes payments of trades of commodities belonging to the daily consumption class.

17. The apparatus of claim 13, wherein the at least one day following the selected day of the week comprises at least one of the following:

two days, three days, four days, five days, six days.

18. The apparatus of claim 13, wherein the selected day and the at least one day following the selected day of the week comprises at least one of the following combinations:

Monday as the selected day, and Tuesday as the at least one day following the selected day of the week;

Monday as the selected day, and Tuesday and Wednesday as the at least one day following the selected day of the week;

Monday as the selected day, and Tuesday, Wednesday and Thursday as the at least one day following the selected day of the week;

Tuesday as the selected day, and Wednesday as the at least one day following the selected day of the week;

Tuesday as the selected day, and Wednesday and Thursday as the at least one day following the selected day of the week;

Wednesday as the selected day, and Thursday as the at least one day following the selected day of the week;

Friday as the selected day, and Saturday as the at least one day following the selected day of the week;

Friday as the selected day, and Saturday and Sunday as the at least one day following the selected day of the week;

Saturday as the selected day, and Sunday as the at least one day following the selected day of the week;

Sunday as the selected day, and Monday as the at least one day following the selected day of the week;

Sunday as the selected day, and Monday and Tuesday as the at least one day following the selected day of the week;

Sunday as the selected day, and Monday, Tuesday and Wednesday as the at least one day following the selected day of the week;

Sunday as the selected day, and Monday, Tuesday, Wednesday and Thursday as the at least one day following the selected day of the week.

19. The apparatus of claim 13, wherein the one or more memories and the computer program code are further configured to, with the one or more processors, cause the apparatus further to:

calculate for each consumption class the content relevance probability in the selected day of the week on the basis of the relative daily value of the selected day of the week affected by the relative daily value of the at least one day following the selected day of the week such that the relative daily value of the selected day of the week is multiplied by a first weighting coefficient and summed up with the relative daily value of the at least one following day of the week multiplied by at least one further weighting coefficient.

20. The apparatus of claim 13, wherein the one or more memories and the computer program code are further configured to, with the one or more processors, cause the apparatus further to:

control the content selection for the consumer on the selected day of the week on the basis of the calculated content relevance probabilities for the selected day such that each content item of the content is classified to at least one consumption class, and a content item classified to a consumption class with a higher content relevance probability is favoured over a content item classified to a consumption class with a lower content relevance probability than the higher content relevance probability.

21. The apparatus of claim 20, wherein the one or more memories and the computer program code are further configured to, with the one or more processors, cause the apparatus further to:

control the content selection for the consumer on the selected day of the week on the basis of the calculated content relevance probabilities for the selected day such that demographic information of the consumer further influences the content selection such that the content item matching the demographic information of the consumer is favoured in the content selection.

22. The apparatus of claim 20, wherein the one or more memories and the computer program code are further configured to, with the one or more processors, cause the apparatus further to:

obtain brand loyalty ranking information of the consumer; and

control the content selection for the consumer on the selected day of the week on the basis of the calculated content relevance probabilities for the selected day such that each content item of the content is classified to at least one brand, and the brand loyalty ranking information of the consumer further influences the content selection such that the content item with a higher brand loyalty rank is favoured over a content item with a lower brand loyalty rank than the higher brand loyalty rank.

23. The apparatus of claim 20, wherein the one or more memories and the computer program code are further configured to, with the one or more processors, cause the apparatus further to:

divide the selected day into parts;

control the content selection for the consumer on the selected day of the week on the basis of the calculated content relevance probabilities for the selected day such that each content item of the content is classified to at least one part of the day, and each selected content item is assigned for at least one part of the selected day; and

transmit the selected content to the mobile device of the consumer on the selected day such that each selected content item is transmitted during the at least one assigned part of the selected day.

24. A non-transitory computer readable storage medium comprising computer program code which, when loaded into an apparatus causes the apparatus at least to:

obtain classified weekly consumption data of a consumer, the classified weekly consumption data comprising daily consumption classes for each day of the week;

calculate for each consumption class a relative daily value for each day of the week such that the relative daily value is the sum of the payments in the consumption class during the day in proportion to the sum of the payments in all consumption classes during said day;

calculate for each consumption class a content relevance probability in a selected day of the week on the basis of a relative daily value of the selected day of the week affected by a relative daily value of at least one day following the selected day of the week;

control a content selection for the consumer on the selected day of the week on the basis of the calculated content relevance probabilities for the selected day; and

transmit the selected content to a mobile device of the consumer on the selected day.