Abstract: An information retrieval system is described herein that monitors a microblog data stream that includes microblog posts to discover and index fresh resources for searching by a search engine. The information retrieval system also uses data from the microblog data stream as well as data obtained from a microblog subscription system to compute novel and effective features for ranking fresh resources which would otherwise have impoverished representations. An embodiment of the present invention advantageously enables a search engine to produce a fresher set of resources and to rank such resources for both relevancy and freshness in a more accurate manner.

Abstract: Example methods, apparatuses, or articles of manufacture are disclosed that may be implemented using one or more computing devices to provide or otherwise support micro-blog message filtering.

Abstract: An information retrieval system is described herein that monitors a microblog data stream that includes microblog posts to discover and index fresh resources for searching by a search engine. The information retrieval system also uses data from the microblog data stream as well as data obtained from a microblog subscription system to compute novel and effective features for ranking fresh resources which would otherwise have impoverished representations. An embodiment of the present invention advantageously enables a search engine to produce a fresher set of resources and to rank such resources for both relevancy and freshness in a more accurate manner.

Abstract: In one embodiment, access a set of recency ranking data comprising one or more recency search queries and one or more recency search results, each of the recency search queries being recency-sensitive with respect to a particular time period and being associated with a query timestamp representing the time at which the recency search query is received at a search engine, each of the recency search results being generated by the search engine for one of the recency search queries and comprising one or more recency network resources. Construct a plurality of recency features from the set of recency ranking data. Train a first ranking model via machine learning using at least the recency features.

Abstract: In one embodiment, a method comprises accessing a search query received at a search engine; identifying a plurality of network resources for the search query; calculating a ranking score for each of the network resources; determining whether the search query is year-qualified; and if the search query is year-qualified, then adjusting the ranking scores of selected ones of the network resources based on a difference between the ranking score of an oldest one of the network resources and the ranking score of a newest one of the network resources and a confidence score representing a likelihood that the search query is year-qualified.