Abstract: Techniques for clustering of search results are described. In an example embodiment, a plurality of first clusters is determined, in a corpus of articles, independently of user queries issued against the corpus of articles, where each first cluster represents a group of articles that relate to a news story. One or more cluster identifiers are assigned to each article in the corpus, where the one or more cluster identifiers respectively identify one or more of the plurality of first clusters to which the article belongs. A query that specifies search criteria against the corpus of articles is received. In response to receiving the query, a result for the query is generated by at least selecting, from the corpus of articles, a set of articles based on the search criteria. The selected set of articles is grouped into one or more second clusters based at least on the one or more cluster identifiers that are assigned to each article in the set of articles.

Abstract: Disclosed is a method and structure that identifies relationships between users of a computerized network. The method extracts relationship information from databases in the network. The information includes address book information, calendar information, event information, to-do list information, journal information, and/or e-mail information. The invention evaluates the relationship information to produce relationship ratings of the users of the network. The invention determines the level of reciprocity of relations between different users; a longevity of relations between the different users; how current relations are between the different users; a frequency of relations between the different users; a level of exclusivity of relations between the different users; a level of complexity of relations between the different users; and/or a proximity of the different users.

Abstract: A method and apparatus for automatic inspection of periodic patterns typically found on patterned silicon wafers, printed circuit board, and the like is disclosed herein. The method comprises an inspection algorithm of two parts: a low-level algorithm and a higher level algorithm. The low-level algorithm utilizes the known periodically of the pattern to find defects by comparing identical cells in the periodic array. The high-level algorithm applies the low-level algorithm, some number of times (N) in succession on the image; accumulates defective pixels to form a separate image; and then applies a threshold-sort operation on a neighborhood to determine center pixel defectiveness.The apparatus for implementing the above method comprises a parallel/pipeline architecture for high speed processing and RAM LUT's to implement a plurality of subtract and compare functions.

Abstract: A method and apparatus for automatic inspection of periodic patterns typically found on patterned silicon wafers, printed circuit board, and the like is disclosed herein. The method comprises an inspection algorithm of two parts: a low-level algorithm and a higher level algorithm which includes, therein the operation of the low-level algorithm. The low-level algorithm utilizes the known periodicity of the pattern to find defects by comparing identical cells in the periodic array. The high-level algorithm comprises applying the low-level algorithm, some number of times (N) in succession on the image. An accumulator image is formed by adding the results of the low-level algorithm to create a separate image array where the pixels relate to the number of times that the pixel in the original image was detected as defective by the low-level algorithm.