Abstract: According to an embodiment of the invention, an approach is provided for estimating how a particular user would rate a particular item from a plurality of items. The approach is applicable to any type of items, including rental items such as movies, music and games, and the invention is not limited to any particular type of item. One or more items from the plurality of items that have ratings similar to the particular item are identified. One or more other users are identified that have given ratings to the one or more items that are substantially similar to ratings given by the particular user to the one or more items. An estimation is made of how the particular user would rate the particular item based upon ratings for the particular item given by the one or more other users.

Abstract: According to an embodiment of the invention, an approach is provided for estimating how a particular user would rate a particular item from a plurality of items. The approach is applicable to any type of items, including rental items such as movies, music and games, and the invention is not limited to any particular type of item. One or more items from the plurality of items that have ratings similar to the particular item are identified. One or more other users are identified that have given ratings to the one or more items that are substantially similar to ratings given by the particular user to the one or more items. An estimation is made of how the particular user would rate the particular item based upon ratings for the particular item given by the one or more other users.

Abstract: According to another embodiment of the invention, an approach is provided for estimating how a particular user would rate a particular item from a plurality of items. The approach is applicable to any type of items, including rental items such as movies, music and games, and the invention is not limited to any particular type of item. One or more items from the plurality of items that have ratings similar to the particular item are identified. Then, one or more other users are identified that have given ratings to the one or more items that are substantially similar to ratings given by the particular user to the one or more items. Finally, an estimation is made of how the particular user would rate the particular item based upon ratings for the particular item given by the one or more other users.

Abstract: An “inventory free” approach for managing rental items across a plurality of distribution locations includes sending at least some rental items that are not needed by two or more distribution locations to a designated distribution location. Rental items sent to the designated distribution location may be permanently stored at the designated distribution location, returned to the distribution location from which they were sent, or sent to other distribution locations, depending upon where the rental items are needed. In situations where particular rental items are not currently needed by customers at a distribution location, but there is a high likelihood that the particular rental items will be needed by the customers within a specified time, the particular rental items may be maintained at the distribution location as “float” and not sent to the designated distribution location. The float is re-processed as returned rental items prior to being again rented to customers.

Abstract: According to another embodiment of the invention, an approach is provided for estimating how a user would rate an item that the user has not yet rated. The approach is applicable to any type of items, including rental items such as movies and games, and the invention is not limited to any particular type of item. The approach is applicable to a wide variety of contexts and is ideally suited for automatically selecting rental items to be recommended for rental. One or more items that have been rated by the user are identified. Then, one or more other users are identified that have rated the one or more items and given ratings to the one or more items that are substantially similar to ratings given by user to the one or more items. Finally, an estimation is made how the user would rate the item that the user has not yet rated based upon how the one or more other users rated the item.

Abstract: According to a computer-implemented approach for renting items to customers, customers specify what items to rent using item selection criteria separate from deciding when to receive the specified items. According to the approach, customers provide item selection criteria to a provider provides the items indicated by the item selection criteria to customer over a delivery channel. The provider may be either centralized or distributed depending upon the requirements of a particular application. A “Max Out” approach allows up to a specified number of items to be rented simultaneously to customers. A “Max Turns” approach allows up to a specified number of item exchanges to occur during a specified period of time. The “Max Out” and “Max Turns” approaches may be used together or separately with a variety of subscription methodologies.

Abstract: According to a computer-implemented approach for renting items to customers, customers specify what items to rent using item selection criteria separate from deciding when to receive the specified items. According to the approach, customers provide item selection criteria to a provider provides the items indicated by the item selection criteria to customer over a delivery channel. The provider may be either centralized or distributed depending upon the requirements of a particular application. A “Max Out” approach allows up to a specified number of items to be rented simultaneously to customers. A “Max Turns” approach allows up to a specified number of item exchanges to occur during a specified period of time. The “Max Out” and “Max Turns” approaches may be used together or separately with a variety of subscription methodologies.