Abstract: A process, system and computer software are provided to facilitate at least one recommendation to one or more users and/or one or more applications using multidimensional data. In particular, a multidimensional space is defined, wherein each dimension is capable of providing variable information. At least one dimension corresponds to user profiles. The multidimensional space is filled with multidimensional data corresponding to dimensions of the multidimensional space. Then, information from the multidimensional space is retrieved. Further, the recommendation is generated based on the retrieved information. In addition, it is possible to generate a recommendation-specific query. This can be performed by generating the recommendation-specific query to access a multidimensional cube and retrieve data stored therein. Then, the recommendation can be issued based on the data retrieved from the multidimensional cube.

Abstract: In one embodiment, a method includes accessing multidimensional data corresponding to a multidimensional space having at least three dimensions. Each dimension has a number of attributes characterizing the dimension, and each attribute is capable of providing variable information. The method includes retrieving data corresponding to each of at least three dimensions of the multidimensional space and generating for a user a recommendation based on the data retrieved from each dimension.

Abstract: A process, system and computer software are provided to facilitate at least one recommendation to one or more users and/or one or more applications using multidimensional data. In particular, a multidimensional space is defined, wherein each dimension is capable of providing variable information. At least one dimension corresponds to user profiles. The multidimensional space is filled with multidimensional data corresponding to dimensions of the multidimensional space. Then, information from the multidimensional space is retrieved. Further, the recommendation is generated based on the retrieved information. In addition, it is possible to generate a recommendation-specific query. This can be performed by generating the recommendation-specific query to access a multidimensional cube and retrieve data stored therein. Then, the recommendation can be issued based on the data retrieved from the multidimensional cube.

Abstract: A process, system and computer software are provided to facilitate at least one recommendation to one or more users and/or one or more applications using multidimensional data. In particular, a multidimensional space is defined, wherein each dimension is capable of providing variable information. At least one dimension corresponds to user profiles. The multidimensional space is filled with multidimensional data corresponding to dimensions of the multidimensional space. Then, information from the multidimensional space is retrieved. Further, the recommendation is generated based on the retrieved information. In addition, it is possible to generate a recommendation-specific query. This can be performed by generating the recommendation-specific query to access a multidimensional cube and retrieve data stored therein. Then, the recommendation can be issued based on the data retrieved from the multidimensional cube.

Abstract: A user specifies one or more monitoring/probing rules on a client station. These rules specify user instructions for monitoring and probing conditions, events, and data on monitored sites on the Internet. The client station transfers the rules to the monitoring site, which also processes and interprets the rules. When the monitoring site processes these rules, it results in (1) allocation of space and (2) creation or initialization of agent programs, which will effect periodic monitoring of Internet sites and send data back to the monitoring site. If the retrieved information at the monitoring site satisfies the user-specified conditions, the monitoring site will conduct further exploration to gather more information that may help determine the causes of these conditions. The results of such a probe may be obtained from the monitoring site or the Internet, and are communicated by the monitoring site to the client station.

Abstract: A process, system and computer software are provided to facilitate at least one recommendation to one or more users and/or one or more applications using multidimensional data. In particular, a multidimensional space is defined, wherein each dimension is capable of providing variable information. At least one dimension corresponds to user profiles. The multidimensional space is filled with multidimensional data corresponding to dimensions of the multidimensional space. Then, information from the multidimensional space is retrieved. Further, the recommendation is generated based on the retrieved information. In addition, it is possible to generate a recommendation-specific query. This can be performed by generating the recommendation-specific query to access a multidimensional cube and retrieve data stored therein. Then, the recommendation can be issued based on the data retrieved from the multidimensional cube.

Abstract: A process, system and computer software are provided to facilitate at least one recommendation to one or more users and/or one or more applications using multidimensional data. In particular, a multidimensional space is defined, wherein each dimension is capable of providing variable information. At least one dimension corresponds to user profiles. The multidimensional space is filled with multidimensional data corresponding to dimensions of the multidimensional space. Then, information from the multidimensional space is retrieved. Further, the recommendation is generated based on the retrieved information. In addition, it is possible to generate a recommendation-specific query. This can be performed by generating the recommendation-specific query to access a multidimensional cube and retrieve data stored therein. Then, the recommendation can be issued based on the data retrieved from the multidimensional cube.

Abstract: A process, system and computer software are provided to facilitate at least one recommendation to one or more users and/or one or more applications using multidimensional data. In particular, a multidimensional space is defined, wherein each dimension is capable of providing variable information. At least one dimension corresponds to user profiles. The multidimensional space is filled with multidimensional data corresponding to dimensions of the multidimensional space. Then, information from the multidimensional space is retrieved. Further, the recommendation is generated based on the retrieved information. In addition, it is possible to generate a recommendation-specific query. This can be performed by generating the recommendation-specific query to access a multidimensional cube and retrieve data stored therein. Then, the recommendation can be issued based on the data retrieved from the multidimensional cube.

Abstract: A process, system and computer software are provided to facilitate at least one recommendation to one or more users and/or one or more applications using multidimensional data. In particular, a multidimensional space is defined, wherein each dimension is capable of providing variable information. At least one dimension corresponds to user profiles. The multidimensional space is filled with multidimensional data corresponding to dimensions of the multidimensional space. Then, information from the multidimensional space is retrieved. Further, the recommendation is generated based on the retrieved information. In addition, it is possible to generate a recommendation-specific query. This can be performed by generating the recommendation-specific query to access a multidimensional cube and retrieve data stored therein. Then, the recommendation can be issued based on the data retrieved from the multidimensional cube.

Abstract: A process, system and computer software are provided to facilitate at least one recommendation to one or more users and/or one or more applications using multidimensional data. In particular, a multidimensional space is defined, wherein each dimension is capable of providing variable information. At least one dimension corresponds to user profiles. The multidimensional space is filled with multidimensional data corresponding to dimensions of the multidimensional space. Then, information from the multidimensional space is retrieved. Further, the recommendation is generated based on the retrieved information. In addition, it is possible to generate a recommendation-specific query. This can be performed by generating the recommendation-specific query to access a multidimensional cube and retrieve data stored therein. Then, the recommendation can be issued based on the data retrieved from the multidimensional cube.

Abstract: A process, system and computer software are rovided to facilitate at least one recommendation to one or more users (420) and/or one or more applications (430) using multidimensional data (410). In particular, the multidimensional data (410) which define a multidimensional space (400) is accessed. The multidimensional space (400) can have more than two dimensions, each capable of providing variable information. Then, information from the multidimensional space is retrieved. Further, the recommendation is generated based on the retrieved information. In addition, it is possible to generate a recommendation-specific query (440). This can be performed by generating the recommendation-specific query (440) to access a multidimensional cube and retrieve data stored therein. Then, the recommendation can be issued based on the data retrieved from the multidimensional cube.

Abstract: Exemplary non-transitory computer-readable medium, method and system for providing at least one recommendation to users and applications using multidimensional data. The multidimensional data can define a multidimensional space defined by a Cartesian product of the dimensions. The multidimensional space can have at least three dimensions, and each of the dimensions can be capable of (i) providing variable information, and (ii) having a type that is different from a type of another one of the dimensions. The exemplary non-transitory computer-readable medium, method and system can retrieve information from data associated with the multidimensional space. Further, the exemplary non-transitory computer-readable medium, method and system can generate the at least one recommendation based on the retrieved information. Further, at least one of the dimensions can include profiles.

Abstract: A system and method for generating and validating a user profile (25) for a user based on a static profile (10) and a dynamic profile (15) of the user. The method and system compresses the dynamic rules (15) into aggregated rules so that the user can view a comparatively small number of the aggregated rules and select the desired rules from the aggregated rules based on user desired criteria. The method and system validates user rules (60) using a processing device, which are retrieved from a storage device. The user rules are separated into at least one subset of a user set. Then, it is determined if a particular rule of the at least one subset is one of acceptable, unacceptable and undecided based on a defined criteria (415). If the particular rules of the at least one subset are acceptable, the particular rules of the at least one subset are provided (e.g. assigned) to a corresponding user (435).

Abstract: A process, system and computer software are rovided to facilitate at least one recommendation to one or more users (420) and/or one or more applications (430) using multidimensional data (410). In particular, the multidimensional data (410) which define a multidimensional space (400) is accessed. The multidimensional space (400) can have more than two dimensions, each capable of providing variable information. Then, information from the multidimensional space is retrieved. Further, the recommendation is generated based on the retrieved information. In addition, it is possible to generate a recommendation-specific query (440). This can be performed by generating the recommendation-specific query (440) to access a multidimensional cube and retrieve data stored therein. Then, the recommendation can be issued based on teh data retrieved from the multidimensional cube.

Abstract: A method and system for the analysis of biological, medical and/or biochemical data having values for each of a plurality of attributes, having a receiving portion for receiving the data and entering it into a storage arrangement like a relational database in accordance with the values and attributes of the data; a calculating portion for determining discrete bins for at least one of the attributes for the data in accordance with the values of the data entered in the storage arrangement; a re-organizing portion for re-organizing the data in the storage arrangement in accordance with the discrete bins; a data mining portion for mining the organized data in the storage arrangement to determine sets of applicable logical rules; and a processing and presenting portion for logical rules or groups of logical rules. The processing portion further involves the application of at least one operator to create a subset of rules in an iterative manner.