METHOD AND ARRANGEMENT FOR RANKING OF LIVE WEB APPLICATIONS

• US 20100100512A1
• Filed: 10/16/2009
• Published: 04/22/2010
• Est. Priority Date: 10/17/2008
• Status: Abandoned Application

• Current Assignee: Telefonaktiebolaget LM Ericsson
• Original Assignee: Telefonaktiebolaget LM Ericsson
• Inventors: Lundkvist, Karl-Johan, Brodin, Per-Erik
• Application Number:
  US12/580,484
• Publication Number:
  US 20100100512A1
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: H04N 21/41407 embedded in a portable device, e.g. video client on a mobile phone, PDA, laptop constructional details of equipment or arrangements specially adapted for portable computer application G06F1/1626; arrangements specially adapted for mobile receivers in broadcast systems H04H20/57
• CPC Class Codes: H04N 21/4143 embedded in a Personal Computer [PC]
• CPC Class Codes: H04N 21/466 Learning process for intelligent management, e.g. learning user preferences for recommending movies services using the results of monitoring in broadcast systems H04H60/61
• CPC Class Codes: H04N 21/4663 involving probabilistic networks, e.g. Bayesian networks
• CPC Class Codes: H04N 21/6125 involving transmission via Internet transmission by internet of broadcast information H04H60/82
• CPC Class Codes: H04N 21/812 involving advertisement data advertising per se G06Q30/02

Abstract

A method of ranking a plurality of live web applications of a communication device is disclosed. The method comprises receiving at least one data stream, each having a content and associated with a corresponding one of the plurality of live web applications, and evaluating the content of the at least one data stream using machine-learning algorithms. The method further comprises updating each of the corresponding live web applications based on the at least one data stream and determining for each of the corresponding live web applications whether any user reaction occurs with the corresponding live web application in association with the updating of the corresponding live web application. The method comprises ranking the plurality of live web applications relative to each other based at least on the evaluation of the content of the at least one data stream and the determinations of whether any user reaction occurred. Corresponding computer program product, arrangement and communication device are also disclosed.

Claims

1. A method of ranking a plurality of live web applications of a communication device, comprising the steps of:

receiving at least one data stream, each having a content and associated with a corresponding one of the plurality of live web applications;

evaluating the content of the at least one data stream using machine-learning algorithms;

updating each of the corresponding live web applications based on the at least one data stream;

determining for each of the corresponding live web applications whether any user reaction occurs with the corresponding live web application in association with the updating of the corresponding live web application; and

ranking the plurality of live web applications relative to each other based at least on the evaluation of the content of the at least one data stream and the determinations of whether any user reaction occurred.

2. The method of claim 1, wherein the step of receiving at least one data stream comprises receiving a plurality of data streams, the step of evaluating the content of the at least one data stream comprises evaluating the content of the plurality of data streams, and the step of ranking the plurality of live web applications relative to each other is further based on the evaluation of the content of the plurality of data streams.

3. The method of claim 1, wherein the step of receiving at least one data stream comprises receiving a plurality of data streams, and further comprising the step of:

updating the ranking of the plurality of live web applications for each of the received plurality of data streams.

4. The method of claim 1, further comprising the step of using a profile ranking as an initial ranking prior to the reception of a first data stream.

5. The method of claim 1, wherein the ranking of the plurality of live web applications relative to each other is also based on a time indication.

6. The method of claim 1, wherein the ranking of the plurality of live web applications relative to each other is also based on a geographical location indication.

7. The method of claim 1, further comprising the step of:

displaying at least one of the plurality of live web applications on a user interface of the communication device based on the ranking of the plurality of live web applications relative to each other.

8. The method of claim 1, wherein the live web applications are web widgets.

9. The method of claim 1, wherein the machine-learning algorithms comprise statistical processing.

10. The method of claim 9, wherein the step of evaluating the content of the at least one data stream using statistical processing further comprises the steps of:

normalizing the content;

excluding certain content items from the content; and

analyzing the content using a naï

ve Bayes classifier.

11. The method of claim 1, wherein the content of the at least one data stream comprises at least one of:

textual information; and

one or more images.

12. A computer program product embodied on a computer readable medium, having thereon a computer program comprising program instructions, the computer program being loadable into a data-processing unit and adapted to cause the data-processing unit to execute method steps according to claim 1 when the computer program is run by the data-processing unit.

13. An arrangement for ranking a plurality of live web applications comprising:

a receiver adapted to receive at least one data stream, each data stream having a content and associated with a corresponding one of the plurality of live web applications;

a live web application runtime unit adapted to update each of the corresponding live web applications based on the at least one data stream; and

a ranking unit adapted to;

determine for each of the corresponding live web applications whether any user re-action occurs with the corresponding live web application in association with the updating of the corresponding live web application;

evaluate the content of the at least one data stream using machine-learning algorithms; and

rank the plurality of live web applications relative to each other based at least on the evaluation of the content of the at least one data stream and the determinations of whether any user reaction occurred.

14. The arrangement of claim 13, wherein the receiver is adapted to receive a plurality of data streams, and the ranking unit is adapted to evaluate the content of the plurality of data streams and rank the plurality of live web applications relative to each other further based on the evaluation of the content of the plurality of data streams.

15. The arrangement of claim 13, wherein

the receiver is adapted to receive a plurality of data streams;

and

the ranking unit is further adapted to update the ranking of the plurality of live web applications for each of the received plurality of data streams.

16. The arrangement of claim 13, wherein the ranking unit is further adapted to use a profile ranking as an initial ranking prior to the reception of a first data stream.

17. The arrangement of claim 13, wherein the ranking unit is further adapted to base the ranking of the plurality of live web applications relative to each other on a time indication.

18. The arrangement of claim 13, wherein the ranking unit is further adapted to base the ranking of the plurality of live web applications relative to each other on a geographical location indication.

19. The arrangement of claim 13, wherein the live web applications are web widgets.

20. The arrangement of claim 13, wherein the ranking unit comprises an analyzing unit adapted to evaluate the content of the at least one data stream using machine-learning algorithms.

21. The arrangement of claim 20, wherein the analyzing unit comprises:

a stemmer;

a stop-list; and

a naï

ve Bayes classifier.

22. The arrangement of claim 13, wherein the machine-learning algorithms comprise statistical processing.

23. The arrangement of claim 13, wherein the content of the at least one data stream comprises at least one of:

textual information; and

one or more images.

24. The arrangement of claim 13 as implemented in a communication device.

25. The communication device according to claim 24, further comprising a user interface for displaying at least one of the plurality of live web applications based on the ranking of the plurality of live web applications relative to each other.

26. The communication device according to claim 24, wherein the communication device is a mobile terminal, a telephone, a smartphone, a personal digital assistant, a stationary computer, a laptop, a workstation, a Set-Top Box, or a wristwatch.