Abstract: According to an example embodiment, a method comprises executing instructions by a special purpose computing apparatus to, for labeled source domain data having a plurality of original labels, generate a plurality of first predicted labels for the labeled source domain data using a target function, the target function determined by using a plurality of labels from labeled target domain data. The method further comprises executing instructions by the special purpose computing apparatus to apply a label relation function to the first predicted labels for the source domain data and the original labels for the source domain data to determine a plurality of weighting factors for the labeled source domain data.

Abstract: Disclosed are methods and apparatus for clustering news stories, which are to be presented over a computer network. In general, an incremental clustering system is configured to update a current set of news clusters with newly arrived news articles without having to recompute the clusters for the entire corpus, as well as form new clusters for recently generated news topics. In one embodiment, a plurality of news articles are initially obtained via the computer network, and the news articles are clustered into a plurality of initial clusters. For only news articles, including any unclustered news articles, that are less than a predetermined age limit, it is determined in an incremental clustering process whether to form one or more new clusters or assign to the initial clusters.

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: One particular embodiment clusters a plurality of documents using one or more clustering algorithms to obtain one or more first sets of clusters, wherein: each first set of clusters results from clustering the documents using one of the clustering algorithms; and with respect to each first set of clusters, each of the documents belongs to one of the clusters from the first set of clusters; accesses a search query; identifies a search result in response to the search query, wherein the search result comprises two or more of the documents; and clusters the search result to obtain a second set of clusters, wherein each document of the search result belongs to one of the clusters from the second set of clusters.

Abstract: A system for determining the intent of query that includes a search engine that receives a first search query, a query/click log module configured to store log data associated with the first search query; and a computational module that generates metric values associated with the first search query based on the log data and that determines that the first search query is one of a regional specific query or a global query based on the metric values, where the metric values reflect a likelihood of local intent of the first search query, and where the search engine provides search results selected in part based on the metric values.

Abstract: According to an example embodiment, a method comprises executing instructions by a special purpose computing apparatus to, for labeled source domain data having a plurality of original labels, generate a plurality of first predicted labels for the labeled source domain data using a target function, the target function determined by using a plurality of labels from labeled target domain data. The method further comprises executing instructions by the special purpose computing apparatus to apply a label relation function to the first predicted labels for the source domain data and the original labels for the source domain data to determine a plurality of weighting factors for the labeled source domain data.

Abstract: Exemplary methods and apparatuses are provided which may be used to provide or otherwise support segment sensitive query matching based on segmented portions of web pages and/or providing related information for use in information extraction and/or information retrieval systems.

Abstract: Exemplary methods and apparatuses are provided which may be used for classifying and indexing segmented portions of web pages and providing related information for use in information extraction and/or information retrieval systems.

Abstract: A geographic region is automatically determined for an Internet resource based on information that has been gathered over time through the automatic monitoring of certain “click” activities of Internet search engine-using users. Over time, the search engine collects information for each click. Using this click-related data, the search engine estimates the geographic region with which the resource ought to be associated. The fact that a significant proportion of clicks on a resource's hyperlink are clicks that “came through” a search engine portal that is associated with a geographic region tends to suggest that the resource ought to be associated with that geographic region. Similarly, the fact that a significant proportion of clicks on a resource's hyperlink are clicks that were made by users whose computers have IP addresses that are associated with a geographic region tends to suggest that the resource ought to be associated with that geographic region.

Abstract: To increase the amount of training data available to train a machine learning ranking function, data from multiple markets are normalized in such a manner as to optimize a measurement of quality of the ranking function trained on the various sets of normalized training data. Furthermore, the feature scores of training data from individual markets are adapted to conform to the distributions of feature scores from a base market. Such adapted training data from the various markets may be used to train a single, robust ranking function. Adaptation of feature scores in a particular training data set involves mapping feature scores of the particular training data set to feature scores of a base training data set to conform the distributions of the feature scores in the particular training data set to the distributions of the feature scores in the base training data set.

Abstract: A system for determining the intent of query that includes a search engine that receives a first search query, a query/click log module configured to store log data associated with the first search query; and a computational module that generates metric values associated with the first search query based on the log data and that determines that the first search query is one of a regional specific query or a global query based on the metric values, where the metric values reflect a likelihood of local intent of the first search query, and where the search engine provides search results selected in part based on the metric values.