Abstract: Subsets of training data are selected for iterations of a statistical model through a training process. The selection can reduce the amount of data to be processed by selecting the training data that will likely have significant training value for the pass. This can include using a metric such as the loss or certainty to sample the data, such that easy to classify instances are used for training less frequently than harder to classify instances. A cutoff value or threshold can also, or alternatively, be used such that harder to classify instances are not selected for training until later in the process when the model may be more likely to benefit from training on those instances. Sampling can vary between passes for variety, and the cutoff value might also change such that all data instances are eligible for training selection by at least the last iteration.

Abstract: A system and method is described herein that cache web documents in two or more caches in an optimized manner. The web documents result from a plurality of queries presented to a web search engine. Each web document has a tier score indicating a position of the web document in the caches. The tier scores are modified in a manner that rearranges the web documents in caches. This rearrangement of the web documents in the caches can advantageously improve the retrieval time for the web documents.

Abstract: A system and method is described herein that cache web documents in two or more caches in an optimized manner. The web documents result from a plurality of queries presented to a web search engine. Each web document has a tier score indicating a position of the web document in the caches. The tier scores are modified in a manner that rearranges the web documents in caches. This rearrangement of the web documents in the caches can advantageously improve the retrieval time for the web documents.

Abstract: A contextual advertising system selects online advertisements for display on a network location. The system may transform page content of a page received in a platform over a network into a textual representation. In addition, the system may transform received site content of a site into a site signature. The site includes the page. The system then may correct the textual representation utilizing the site signature to produce modified textual representation. The system may utilize the modified textual representation to select an online advertisement. Considering a page in the context of the entire website to which it belongs leads to better understanding and interpretation of the page topic(s) and thus yields more accurate ad matching.