1. A method of providing a media recommendation for a user, comprising:
calculating a domain knowledge-based recommendation score for the user for a media item;
calculating a correlation-based recommendation score for the user for the media item;
deriving a user recommendation score for the media item from the domain knowledge-based recommendation score and the correlation-based recommendation score.
2. The method of providing a media recommendation for a user of claim 1, further comprising selecting one or more media items with the highest user recommendation scores not previously rated by the user to recommend to the user.
3. The method of providing a media recommendation for a user of claim 1, wherein calculating a correlation-based recommendation score comprises deriving the correlation-based recommendation score from at least one of items with similar user score ratings and users with similar item score ratings.
4. The method of providing a media recommendation for a user of claim 1, wherein calculating a domain knowledge-based recommendation score comprises deriving the domain knowledge-based recommendation score from other user indications of media that the other users would recommend to someone who enjoyed a specific media item.
5. The method of providing a media recommendation for a user of claim 1, wherein deriving a user recommendation score from the domain knowledge-based recommendation score and the correlation-based recommendation score further comprises at least one of multiplying, averaging, or adding the domain knowledge-based recommendation score and the correlation-based recommendation score.
6. The method of providing a media recommendation for a user of claim 1, wherein calculating a correlation-based recommendation score comprises employing an optimized correlation-based recommendation algorithm based on correlation between users in a plurality of media item characteristics.
7. A media recommendation engine, comprising:
a domain knowledge-based scoring module operable to calculate a domain knowledge-based recommendation score for a user;
a correlation-based scoring module operable to calculate a correlation-based recommendation score for the user; and
a user recommendation scoring module operable to derive a user recommendation score for the user regarding a media item from the domain knowledge-based recommendation score and the correlation-based recommendation score.
8. The media recommendation engine of claim 7, further comprising a media recommendation module operable to select one or more media items with the highest user recommendation scores not previously rated by the user to recommend to the user.
9. The media recommendation engine of claim 7, wherein calculating a domain knowledge-based recommendation score comprises deriving the domain knowledge-based recommendation score from domain knowledge media pair information derived using one or more intermediate media items, consistent with an example embodiment of the invention.
10. The media recommendation engine of claim 7, wherein calculating a domain knowledge-based recommendation score comprises deriving the domain knowledge-based recommendation score from other user indications of media that the other users would recommend to someone who enjoyed a specific media item.
11. The media recommendation engine of claim 7, wherein deriving a user recommendation score from the domain knowledge-based recommendation score and the correlation-based recommendation score further comprises at least one of multiplying, averaging, or adding the domain knowledge-based recommendation score and the correlation-based recommendation score.
12. The media recommendation engine of claim 7, wherein calculating a correlation-based recommendation score comprises employing an optimized correlation-based recommendation algorithm based on correlation between users in a plurality of media item characteristics.
13. A computerized system, comprising:
a domain knowledge-based scoring module operable to calculate a domain knowledge-based recommendation score for a user;
a correlation-based scoring module operable to calculate a correlation-based recommendation score for the user;
a user recommendation scoring module operable to derive a user recommendation score for the user regarding a media item from the domain knowledge-based recommendation score and the correlation-based recommendation score; and
a media recommendation module operable to select one or more media items with the highest user recommendation scores to recommend to the user.
14. The computerized system of claim 7, wherein calculating a domain knowledge-based recommendation score comprises deriving the domain knowledge-based recommendation score from other user indications of media that the other users would recommend to someone who enjoyed a specific media item.
15. The computerized system of claim 7, wherein calculating a correlation-based recommendation score comprises employing an optimized correlation-based recommendation algorithm based on correlation between at least one of media items and users in a plurality of media item characteristics.
16. The computerized system of claim 7, wherein deriving a user recommendation score from the domain knowledge-based recommendation score and the correlation-based recommendation score further comprises at least one of multiplying, averaging, or adding the domain knowledge-based recommendation score and the correlation-based recommendation score.
17. A machine-readable medium with instructions stored thereon, the instructions when executed operable to cause a computerized system to:
calculate a domain knowledge-based recommendation score for a user;
calculate a correlation-based recommendation score for the user;
derive a user recommendation score for the user regarding a media item from the domain knowledge-based recommendation score and the correlation-based recommendation score; and
select one or more media items with the highest user recommendation scores to recommend to the user.
18. The machine-readable medium of claim 7, wherein calculating a domain knowledge-based recommendation score comprises deriving the domain knowledge-based recommendation score from other user indications of media that the other users would recommend to someone who enjoyed a specific media item.
19. The machine-readable medium of claim 7, wherein calculating a correlation-based recommendation score comprises employing an optimized correlation-based recommendation algorithm based on correlation between at least one of media items and users in a plurality of media item characteristics.
20. The machine-readable medium of claim 7, wherein deriving a user recommendation score from the domain knowledge-based recommendation score and the correlation-based recommendation score further comprises at least one of multiplying, averaging, or adding the domain knowledge-based recommendation score and the correlation-based recommendation score.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A printer comprising:
a print head including an ink propelling mechanism;
an ink tank configured to supply ink to the print head;
an ink circulation route including the print head and the ink tank therein;
an ink circulator adapted to circulate ink through the ink circulation route;
a first temperature sensor adapted to measure a temperature of ink flowing in a route between the print head and the ink tank in the ink circulation route;
a heater disposed in a vicinity of the ink tank to heat ink; and
a controller configured to work with a received print job, operating for temperatures of ink as measures at the first temperature sensor lower than a first prescribed reference, to heat ink by the heater without starting printing, and for temperatures of ink as measures at the first temperature sensor kept equal to or higher than the first reference for a prescribed time interval, to start printing,
wherein the prescribed time interval is defined based on: a distance between the first temperature sensor and the print head; a cross-sectional area of the route between the print head and the ink tank; and an ink circulation amount per unit time in the route between the print head and the ink tank.
2. The printer according to claim 1, wherein
the print head further includes an ink chamber to store ink for propelling therein, and
the prescribed time interval is defined further based on a volume of the ink chamber.
3. The printer according to claim 1, wherein
the controller is adapted to work with a started printing, operating for a temperature of ink as a measure at the first temperature sensor lower than the first reference, to complete a print being made on a sheet, to stop the printing.
4. The printer according to claim 3, wherein
the controller is adapted to work with the stopped printing, operating for temperatures of ink as measures at the first temperature sensor kept equal to or higher than the first reference for the prescribed time interval, to restart printing.
5. The printer according to claim 3, wherein
the distance between the first temperature sensor and the print head is set longer than that for ink to travel in the route during a printing time necessitated for one sheet.
6. The printer according to claim 1, further comprising;
a second temperature sensor adapted to measure a temperature of ink in the ink head, wherein
the controller is adapted to operate for a temperature of ink as a measure at the second temperature sensor lower than a second prescribed reference, not to start printing.