Abstract: Means and a computerized method for recommending items such as books and audio compact disks. For each item, a user profile includes ratings provided by users of the system. Unlike present recommendation systems, the user profiles do not include pre-computed similarity factors measuring similarity between users. Rather, when an advisee requests a recommendation, similarity measures are computed comparing the advisee to other users, and the similarity measures are associated with the other users. A subset of the users is selected, where the subset includes the users most similar to the advisee. A recommendation is made based on the ratings by the members of the selected subset.

Abstract: Means and a computerized method for recommending items such as books and audio compact disks. For each item, a user profile includes ratings provided by users of the system. Unlike present recommendation systems, the user profiles do not include pre-computed similarity factors measuring similarity between users. Rather, when an advisee requests a recommendation, similarity measures are computed comparing the advisee to other users, and the similarity measures are associated with the other users. A subset of the users is selected, where the subset includes the users most similar to the advisee. A recommendation is made based on the ratings by the members of the selected subset.

Abstract: Means and a computerized method for recommending items such as books and audio compact disks. For each item, a user profile includes ratings provided by users of the system. Unlike present recommendation systems, the user profiles do not include pre-computed similarity factors measuring similarity between users. Rather, when an advisee requests a recommendation, similarity measures are computed comparing the advisee to other users, and the similarity measures are associated with the other users. A subset of the users is selected, where the subset includes the users most similar to the advisee. A recommendation is made based on the ratings by the members of the selected subset.

Abstract: A digital data storage device physically stores blocks of identical data only once on its storage medium wherein a second or even further identical blocks are stored only as reference referring to the first block of these identical blocks. By this technique, storage of duplicate data is most effectively avoided on the lowest storage level of the disk storage device, even in cases where identical blocks are written by different operating Systems. In the preferred embodiment, the underlying storage medium (magnetic hard disk, optical disk, tape, or M-RAM) is segmented into two areas, the first area particularly comprising a relatively small block reference table and the remaining physical storage area for storing real blocks of information.

Abstract: A digital data storage device physically stores blocks of identical data only once on its storage medium wherein a second or even further identical blocks are stored only as reference referring to the first block of these identical blocks. By this technique, storage of duplicate data is most effectively avoided on the lowest storage level of the disk storage device, even in cases where identical blocks are written by different operating Systems. In the preferred embodiment, the underlying storage medium (magnetic hard disk, optical disk, tape, or M-RAM) is segmented into two areas, the first area particularly comprising a relatively small block reference table and the remaining physical storage area for storing real blocks of information.

Abstract: The present invention relates to the field of computer technology, and in particular to a method and system for compressing digital data from a row-column structured, multi-color bitmap image representation and to advantageous applications thereof for low bandwidth data communication. In order to increase the compression rate in particular of bitmaps corresponding to screen shots in web-based applications or standard desktop applications having a graphical user interface (GUI) it is proposed to reduce (210) the image representation in order to contain only a subset of colors, preferably 2, 4, 8, 16 . . . 256, before subjecting it to further compression steps (215, 260, 265) and comprising rowwise X-OR operations (215) and subsequent compressed mapping (240, 245) of the resulting pixel information into a respective compressed bit string. X-OR operations in column direction (220) are also added in order to improve the compression rate for the specific field of above said low bandwidth communications.

Abstract: The present invention relates to the field of computer technology, and in particular to a method and system for compressing digital data from a row-column structured, multi-color bitmap image representation and to advantageous applications thereof for low bandwidth data communication. In order to increase the compression rate in particular of bitmaps corresponding to screen shots in web-based applications or standard desktop applications having a graphical user interface (GUI) it is proposed to reduce (210) the image representation in order to contain only a subset of colors, preferably 2, 4, 8, 16 . . . 256, before subjecting it to further compression steps (215, 260, 265) and comprising rowwise X-OR operations (215) and subsequent compressed mapping (240, 245) of the resulting pixel information into a respective compressed bit string. X-OR operations in column direction (220) are also added in order to improve the compression rate for the specific field of above said low bandwidth communications.

Abstract: A digital data storage device physically stores blocks of identical data only once on its storage medium wherein a second or even further identical blocks are stored only as reference referring to the first block of these identical blocks. By this technique, storage of duplicate data is most effectively avoided on the lowest storage level of the disk storage device, even in cases where identical blocks are written by different operating systems. In the preferred embodiment, the underlying storage medium (magnetic hard disk, optical disk, tape, or M-RAM) is segmented into two areas, the first area particularly comprising a relatively small block reference table and the remaining physical storage area for storing real blocks of information.

Abstract: A computerized method and corresponding means for rating an item within a recommendation system. In a recommendation scheme, each of a multitude of users U and each of a multitude of items I is included in a profile P(U,I) that comprises ratings. Based on the similarity between a given user and the multitude of users in terms of the ratings, a subset of users is selected who have interest similar to those of the given user.

Abstract: A computerized method and corresponding means for rating an item within a recommendation system, that exploits additional external knowledge or the relationships between the ratable items to implicitly derive, from a first item rated explicitly by a certain user, implicit ratings for items related to the explicitly rated item. In response to a first explicit rating for a first item, the following steps are performed: determining, for the first item, a first set related items based on a predefined item relationship; storing, within the recommendation system, the first explicit rating of the first item; and storing, within the recommendation system, first implicit ratings for the first set of related items.

Abstract: A system for recommending items to a given user based on item recommendations of the given user and other users of the system, using general properties of users or items characterized by arbitrary property values as parameters of the recommendation process to improve recommendation quality.

Abstract: Means and a computerized method for recommending items such as books and audio compact disks. For each item, a user profile includes ratings provided by users of the system. Unlike present recommendation systems, the user profiles do not include pre-computed similarity factors measuring similarity between users. Rather, when an advisee requests a recommendation, similarity measures are computed comparing the advisee to other users, and the similarity measures are associated with the other users. A subset of the users is selected, where the subset includes the users most similar to the advisee. A recommendation is made based on the ratings by the members of the selected subset.

Abstract: The present invention relates to an automatic method of computerized optimization of a technical system like for instance routing systems such as a transportation routing system or a communication network. The invention teaches an optimization method of a technical system comprising new ruin- and recreate-steps operating on the state-variables of a current system state. The ruin-step destroys the current state in a “larger” extend and thus introduces increased freedom for the recreate-step to create a new state. This allows for recalculating a new state in accordance with additional constraints which also improves a quality measure of the state; i.e. every recalculated state always fulfills the additional constraints. Moreover, the recreate-step is not guided by the values of said destroyed state variables, which opens a larger space for determining a new state.

Abstract: A description is given of an electronic auction machine, which reacts to changing sales conditions with appropriately adjusted machine prices. For existing automatic vending machines restocking is based upon very vague experience figures and in particular customary fluctuations in sales are not taken into consideration. With the proposed machine, using a computer current market data are recorded (31) and using these data the current market situation is automatically assessed (32,34). A corresponding updated machine price (33,35) is then displayed.