Abstract: Techniques are described for generating an authority value of a first one of a plurality of documents. A first component of the authority value is generated with reference to outbound links associated with the first document. The outbound links enable access to a first subset of the plurality of documents. A second component of the authority value is generated with reference to a second subset of the plurality of documents. Each of the second subset of documents represents a potential starting point for a user session. A third component of the authority value is generated representing a likelihood that a user session initiated by any of a population of users will end with the first document. The first, second, and third components of the authority value are combined to generate the authority value. At least one of the first, second, and third components of the authority value is computed with reference to user data relating to at least some of the outbound links and the second subset of documents.

Abstract: Methods and apparatus are described for optimally allocating an online advertising budget for a search engine marketing (SEM) campaign among a fixed set of keywords.

Abstract: Methods and apparatus are described for optimally allocating an online advertising budget for a search engine marketing (SEM) campaign among a fixed set of keywords.

Abstract: A variety of techniques are described by which keyword sets and target audience profiles may be generalized in a systematic and effective way with reference to relationships between keywords, profiles, and the data of an underlying user population.

Abstract: A variety of techniques are described by which keyword sets and target audience profiles may be generalized in a systematic and effective way with reference to relationships between keywords, profiles, and the data of an underlying user population.

Abstract: Techniques are described for generating an authority value of a first one of a plurality of documents. A first component of the authority value is generated with reference to outbound links associated with the first document. The outbound links enable access to a first subset of the plurality of documents. A second component of the authority value is generated with reference to a second subset of the plurality of documents. Each of the second subset of documents represents a potential starting point for a user session. A third component of the authority value is generated representing a likelihood that a user session initiated by any of a population of users will end with the first document. The first, second, and third components of the authority value are combined to generate the authority value. At least one of the first, second, and third components of the authority value is computed with reference to user data relating to at least some of the outbound links and the second subset of documents.

Abstract: A first component of an authority value is generated with reference to outbound links associated with a document and corresponding to a first subset of a plurality of documents. A second component of the authority value is generated with reference to a second subset of the plurality of documents that represent potential starting points for user sessions. A third component of the authority value is generated representing a likelihood that a user session initiated by any of a population of users will end with the document. At least one of the first, second, and third components of the authority value is computed with reference to user data relating to at least some of the outbound links and the second subset of documents.

Abstract: Methods and apparatus are described for storing a plurality of objects in a plurality of storage options. An importance index is generated for each of the plurality of objects with reference to importance data associated with each object. At least a portion of the importance data represents relevance of the associated object relative to a population of users interacting with the plurality of objects. Each of the objects is stored in a selected one of the storage options with reference to the corresponding importance index and a hierarchy of the storage options. The hierarchy of storage options represents at least partial ordering of the storage options with reference to economic costs and efficiency of retrieval.

Abstract: Data mining for managing marketing resources is disclosed. In one embodiment, a method for managing a marketing campaign includes the following. First, the method provides a data mining engine capable of being trained with training data and capable thereof of performing inference relative to the training data and on future data. Next, the method provides a user database defining observed characteristics of each one of a set of users. The characteristics include at least one of one or more user's attributes, and one or more of the user's preferences. Finally, the data mining engine is trained with a set of training data comprising the user data base, and a predetermined characteristic pertaining to the market campaign is input to the engine, such that, in response to the input, a subset of the users in the database is obtained that have the highest correlation to the characteristic.

Abstract: Methods and apparatus are described for optimally allocating an online advertising budget for a search engine marketing (SEM) campaign among a fixed set of keywords.

Abstract: Methods and apparatus are described for storing a plurality of objects in a plurality of storage options. An importance index is generated for each of the plurality of objects with reference to importance data associated with each object. At least a portion of the importance data represents relevance of the associated object relative to a population of users interacting with the plurality of objects. Each of the objects is stored in a selected one of the storage options with reference to the corresponding importance index and a hierarchy of the storage options. The hierarchy of storage options represents at least partial ordering of the storage options with reference to economic costs and efficiency of retrieval.

Abstract: Techniques are described for generating an authority value of a first one of a plurality of documents. A first component of the authority value is generated with reference to outbound links associated with the first document. The outbound links enable access to a first subset of the plurality of documents. A second component of the authority value is generated with reference to a second subset of the plurality of documents. Each of the second subset of documents represents a potential starting point for a user session. A third component of the authority value is generated representing a likelihood that a user session initiated by any of a population of users will end with the first document. The first, second, and third components of the authority value are combined to generate the authority value. At least one of the first, second, and third components of the authority value is computed with reference to user data relating to at least some of the outbound links and the second subset of documents.

Abstract: A variety of techniques are described by which keyword sets and target audience profiles may be generalized in a systematic and effective way with reference to relationships between keywords, profiles, and the data of an underlying user population.

Abstract: Retrofitting recommender systems, so that they can scale to large data, is disclosed. The principal notion is to reduce data requirements of existing recommender engines by performing a type of data reduction that minimizes the loss of information given the engine. The reductions covered in this invention are designed to be easily implemented on a database system, and are intended to have minimal impact on an existing implementation of a recommender system. In one embodiment, a method repeats reducing the data by a number of records, until an accuracy threshold or a performance requirement is met. If the accuracy threshold is met first, the method repeats removing a highest-frequency dimension from the data, until the performance requirement is also met. The reduced data is provided to the recommender system, which generates predictions based on the reduced data, and a query.

Abstract: A generalization of frequent item sets to error-tolerant frequent item sets (ETF) is disclosed, together with its application in data clustering using error-tolerant frequent item sets to either build clusters or as an initialization technique for standard clustering algorithms. Efficient feasible computational algorithms for computing ETF's from very large databases is presented. In one embodiment, a method determines a plurality of weak ETF's, which are strongly tolerant of errors, and determines a plurality of strong ETF's therefrom, which are less tolerant of errors. The resulting clusters can be used as an initial model for a standard clustering approach, or may themselves be used as the end clusters. In one embodiment, the data covered by the strong clusters is removed from the data, and the process is repeated, until no more weak clusters can be found.

Abstract: Method and apparatus for displaying and navigating data organized in the form of a graph structure (hierarchy or network) is presented. The invention has application for displaying a system of interconnected nodes such as a graph, a network, an organizational chart, a flowchart etc. wherein data or information is associated with nodes of the system. A user interface is implemented as an ActiveX control having a viewer component for displaying and navigating graph structur (for example a data mining model over data records or a directory structure over a set of files). The viewer component updates the contents of related windows that display different aspects of the components (nodes) of the data structure. A thumbnail window presents the user with an overview of the data structure. A layout window presents a more detailed view of part of the graph structure. Other windows display context and detailed properties associated with particular selected nodes.

Abstract: Iterative validation for efficiently determining error-tolerant frequent itemsets is disclosed. A description of the application of error-tolerant frequent itemsets to efficiently determining clusters as well as initializing clustering algorithms are also given. In one embodiment, a method determines a sample set of error-tolerant frequent itemsets (ETF's) within a uniform random sample of data within a database. This sample set of ETF's is independently validated, so that, for example, spurious ETF's and spurious dimensions within the ETF's can be removed. The validated sample set of ETF's, is added to the set of ETF's for the database. This process is repeated with additional uniform samples that are mutually exclusive from prior uniform samples, to continue building the database's set of ETF's, until no new sample sets can be found.

Abstract: A system that provides for the graphic visualization of the categories of a collection of records. The graphic visualization is referred to as “category graph.” The system optionally displays the category graph as a “similarity graph” or a “hierarchical map.” When displaying a category graph, the system displays a graphic representation of each category. The system displays the category graph as a similarity graph or a hierarchical map in a way that visually illustrates the similarity between categories. The display of a category graph allows a data analyst to better understand the similarity and dissimilarity between categories. A similarity graph includes a node for each category and an arc connecting nodes representing categories whose similarity is above a threshold. A hierarchical map is a tree structure that includes a node for each base category along with nodes representing combinations of similar categories.