Abstract: A data mining system extracts job opening information and derives, for a given job, relevant competencies and derives, for a given candidate, relevant competencies, for the candidate. In some embodiments, the data mining performs authentication of relevant competencies before performing matching. The matching outputs can be used to provide data to a candidate indicating possible future competencies to obtain, to provide data to a teaching organization indicating possible future competencies to cover in their coursework, and to provide data to employers related to what those teaching organizations are covering.

Abstract: Techniques are described for assigning, to target categories of a target scheme, items that have been obtained from a plurality of sources. In situations in which one or more of the sources has organized its information according to a source scheme that differs from the target scheme, the assignment may be based, in part, on an estimate of the probability that items from a particular source category should be assigned to a particular target category. Such probability estimates may be based on how many training set items associated with the particular source category have been assigned to the particular target category. Source categories may be grouped into clusters. The probability estimates may also be based on how many training set items within the cluster to which the particular source category has been mapped, have been assigned the particular target category.

Abstract: Techniques are described for assigning, to target categories of a target scheme, items that have been obtained from a plurality of sources. In situations in which one or more of the sources has organized its information according to a source scheme that differs from the target scheme, the assignment may be based, in part, on an estimate of the probability that items from a particular source category should be assigned to a particular target category. Such probability estimates may be based on how many training set items associated with the particular source category have been assigned to the particular target category. Source categories may be grouped into clusters. The probability estimates may also be based on how many training set items within the cluster to which the particular source category has been mapped, have been assigned the particular target category.

Abstract: Techniques are provided for automatic product categorization. In one aspect, the categorization is based on text and one or more other values associated with a product offering. In another aspect, a first categorization of a product offering is performed and, if the product category chosen is in a set of co-refinable product categories, then a second (or third, fourth and so on) categorization is performed among the set of co-refinable product categories. In a third aspect, products are categorized based on cost. In another aspect, after products are categorized, the products are flagged for further categorization processing if the cost for categorizing the product is beyond a predefined threshold.

Abstract: An improved system and method is provided for determining web page quality using collective inference based on local and global web page information. A classification engine may be provided for classifying a web page using local features of a seed set of web pages and global web graph information about the seed set of web pages. A dual algorithm based on graph regularization formulated as a well-formed optimization solution may be used in an embodiment for applying collective inference for binary classification of the web page using the local web page information and global web graph information of a web page, the local web page information and global web graph information of an authoritative set of web pages, and the local web page information and global web graph information of a non-authoritative set of web pages.

Abstract: An improved system and method is provided for determining web page quality using collective inference based on local and global web page information. A classification engine may be provided for classifying a web page using local features of a seed set of web pages and global web graph information about the seed set of web pages. A dual algorithm based on graph regularization formulated as a well-formed optimization solution may be used in an embodiment for applying collective inference for binary classification of the web page using the local web page information and global web graph information of a web page, the local web page information and global web graph information of an authoritative set of web pages, and the local web page information and global web graph information of a non-authoritative set of web pages.

Abstract: A Web server stores a table of Web page inlinks. When a Web page is accessed and a user wants to access other pages related to the accessed page, the user requests the table of inlinks, and from it generates a list of sibling links to the accessed page, the sibling links being outlinks of one or more of the inlinks in the table.

Abstract: A system and method are provided for eliciting interesting structure from a collection of entities or resources with explicit and/or implicit, static and/or dynamic relations, called “affinities,” between them. Interesting structure includes (1) notions of quality, authority, or definitiveness of information, (2) notions of relevance to a user's information need, (3) notions of similarity among the plurality of resources retrieved from a universe of resources by a query process, and (4) notions of similarity among the usages of resources by different users/servers. Similarities between entities are computed, based on similarities between the affinity values for the entities. That is, where the affinitiy values for two entities resemble each other, the two entities have a high degree of similarity. Using the similarities, the entities are ranked, clustered, etc., based on a significance derived from the similarities. The ranking, clustering, etc., makes up the interesting structure which is sought.

Abstract: A system and method for training an SVM in a scalable manner includes boosting the SVM during training. Specifically, individual SVMs in an ensemble of SVMs are trained using small subsets of a training data set, with data that earlier classifiers in the ensemble incorrectly classified being overrepresented in succeeding subsets. In this way, the speed with which the overall SVM is trained is increased and the memory requirements therefor are reduced, even for relatively large training data sets.

Abstract: A objective function based on a Bayesian statistical estimation framework is used to determine an optimal model selection by choosing both the optimal number of clusters and the optimal feature set. Heuristics can be applied to find the optimal (or at least sub-optimal) of this objective function in terms of the feature sets and the number of clusters, wherein the maximization of the objective function corresponds to the optimal model structure.

Abstract: A focussed Web crawler learns to recognize Web pages that are relevant to the interest of one or more users, from a set of examples provided by the users. It then explores the Web starting from the example set, using the statistics collected from the examples and other analysis on the link graph of the growing crawl database, to guide itself towards relevant, valuable resources and away from irrelevant and/or low quality material on the Web. Thereby, the Web crawler builds a comprehensive topic-specific library for the benefit of specific users.

Abstract: A method, apparatus, and article of manufacture for a computer implemented hypertext classifier. A new document containing citations to and from other documents is classified. Initially, documents within a neighborhood of the new document are identified. For each document and each class, an initial probability is determined that indicates the probability that the document fits a particular class. Next, iterative relaxation is performed to identify a class for each document using the initial probabilities. A class is selected into which the new document is to be classified based on the initial probabilities and identified classes.

Abstract: A method for identifying, filtering, ranking and cataloging information elements; as for example, World Wide Web pages, of the Internet in whole, part, or in combination. The method is preferably implemented in computer software and features steps for enabling a user to interactively create an information database including preferred information elements such as preferred World Wide Web pages in whole, part, or in combination. The method includes steps for enabling a user to interactively create a frame-based, hierarchical organizational structure for the information elements, and steps for identifying and automatically filtering and ranking by relevance, information elements, such as World Wide Web pages for populating the structure, to form; for example, a searchable, World Wide Web page database.

Abstract: A method for cataloging, filtering and ranking information, as for example, World Wide Web pages of the Internet. The method is preferably implemented in computer software and features steps for enabling a user to interactively create an information database including preferred information elements such as preferred-authority World Wide Web pages. The method includes steps for enabling a user to interactively create a frame-based, hierarchical organizational structure for the information elements, and steps for identifying and automatically filtering and ranking by relevance, information elements, such as World Wide Web pages for populating the structure, to form, for example, a searchable, World Wide Web page database.

Abstract: A method for cataloging, filtering and ranking information, as for example, World Wide Web pages of the Internet. The method is preferably implemented in computer software and features steps for enabling a user to interactively create an information database including preferred information elements such as preferred-authority World Wide Web pages. The method includes steps for enabling a user to interactively create a frame-based, hierarchical organizational structure for the information elements, and steps for identifying and automatically filtering and ranking by relevance, information elements, such as World Wide Web pages for populating the structure, to form, for example, a searchable, World Wide Web page database.

Abstract: A system, process, and article of manufacture for organizing a large text database into a hierarchy of topics and for maintaining this organization as documents are added and deleted and as the topic hierarchy changes. Given sample documents belonging to various nodes in the topic hierarchy, the tokens (terms. phrases, dates, or other usable feature in the document) that are most useful at each internal decision node for the purpose of routing new documents to the children of that node are automatically detected. Using feature terms, statistical models are constructed for each topic node. The models are used in an estimation technique to assign topic paths to new unlabeled documents. The hierarchical technique, in which feature terms can be very different at different nodes, leads to an efficient context-sensitive classification technique. The hierarchical technique can handle millions of documents and tens of thousands of topics.

Abstract: A method for cataloging, filtering and ranking information; as for example, World Wide Web pages of the Internet. The method is preferably implemented in computer software and features steps for enabling a user to interactively create an information database including preferred information elements such as preferred-authority World Wide Web pages. The method including steps for enabling a user to interactively creating a frame-based, hierarchical organizational structure for the information elements, and steps for identifying and automatically filtering and ranking by relevance, information elements, such as World Wide Web pages for populating the structure, to form; for example, a searchable, World Wide Web page database.

Abstract: A system, process, and article of manufacture for organizing a large text database into a hierarchy of topics and for maintaining this organization as documents are added and deleted and as the topic hierarchy changes. Given sample documents belonging to various nodes in the topic hierarchy, the tokens (terms, phrases, dates, or other usable feature in the document) that are most useful at each internal decision node for the purpose of routing new documents to the children of that node are automatically detected. Using feature terms, statistical models are constructed for each topic node. The models are used in an estimation technique to assign topic paths to new unlabeled documents. The hierarchical technique, in which feature terms can be very different at different nodes, leads to an efficient context-sensitive classification technique. The hierarchical technique can handle millions of documents and tens of thousands of topics.

Abstract: A system and method for data mining is provided in which temporal patterns of itemsets in transactions having unexpected support values are identified. A surprising temporal pattern is an itemset whose support changes over time. The method may use a minimum description length formulation to discover these surprising temporal patterns.

Abstract: A system and method are provided for supporting video browsing over a communication network such as the Internet/World Wide Web. A graphical user interface is provided through a client software tool such as a Web browser. A client/user selects a video data object stored at a remote server. A set of points within the object are displayed at the client's graphical user interface display, as representations, preferably thumbnail images, of the points within the object. The user selects an interval defined by the representations, preferably by using the graphical user interface to select two of the representations. The two selected representations delimit the beginning and end of a portion of the video object. Responsive to this selection, that portion of the video object is downloaded and displayed.