Abstract: The subject matter disclosed herein relates to segmentation of interleaved query missions into a plurality of query chains.

Abstract: A method of ascribing scores to web documents and search queries generates a hyperlink-click graph by taking the union of the hyperlink and click graphs, takes a random walk on the hyperlink-click graph, and associates the transition probabilities resulting from the random walk with scores for each of the documents and search queries.

Abstract: A computer-implemented method provides suggested search queries based on an input search query. The input search query is received. A first list of documents is determined that correspond to processing the query by a search engine determining the list of result queries, including processing the first list of documents to determine clusters of documents and determining potential queries that correspond to the determined clusters by comparing results of the potential queries with documents in the determined clusters. A list of result queries is determined, wherein executing the list of result queries would correspond to a second list of documents, that result from presenting the result queries to the search engine; and the documents of the second list of documents cover the documents of the first list of documents. The list of result queries based on the potential queries determined to correspond to the determined clusters.

Abstract: A computer-implemented method is such that suggested search queries are provided based on an input search query. The search query is received (such as from a user providing the search query to a search engine service) and a first list of documents is determined that correspond to processing the query by a search engine. A list of result queries is determined, wherein executing the list of result queries would correspond to a second list of documents, that result from presenting the result queries to the search engine, and the documents of the second list of documents cover the documents of the first list of documents. The list of result queries is returned as the suggested queries.

Abstract: Techniques for query processing in a multi-site search engine are described. During an indexing phase, each site of a multi-site search engine indexes a set of assigned web resources and each site calculates, for each term in the set of assigned web resources, a site-specific upper bound ranking score on the contribution of the term to the search engine ranking function for a query containing the term. During a propagation phase, all sites exchange their site-specific upper bound ranking scores with each other. In response to a site receiving a query, the site determines the set of locally matching resources and compares the ranking score of a locally matching resource with the site-specific upper bound ranking scores for the terms of the query that were received during the propagation phase and determines whether to communicate the query to other sites.

Abstract: Disclosed are methods and apparatus for detecting spam hosts. In one embodiment, one or more graphs are generated using data obtained from a query log, where the one or more graphs include at least one of an anticlick graph or a view graph. Values of one or more syntactic features of the one or more graphs are ascertained. Values of one or more semantic features of the one or more graphs are determined by propagating categories from a web directory among nodes in each of the one or more graphs. Spam hosts are then detected based upon the values of the syntactic features and the semantic features.

Abstract: Disclosed are methods and apparatus for detecting spam-attracting queries. In one embodiment, one or more graphs are generated using data obtained from a query log, where the one or more graphs include at least one of an anticlick graph or a view graph. Values of one or more syntactic features of the one or more graphs are ascertained. Values of one or more semantic features of the one or more graphs are determined by propagating categories from a web directory among nodes in each of the one or more graphs. Spam-attracting queries are then detected based upon the values of the syntactic features and the semantic features.

Abstract: The present invention is directed towards systems and methods for identifying high quality content in a social media environment. The method according to one embodiment of the present invention comprises retrieving a content item and retrieving a plurality of quality features associated with said content item wherein said quality features comprise intrinsic, usage and relationship features. The method then performs an analysis of said content item against said quality features and generates a quality score based on said analysis.

Abstract: A method of caching posting lists to a search engine cache calculates the ratios between the frequencies of the query terms in a past query log and the sizes of the posting lists for each term, and uses these ratios to determine which posting lists should be cached by sorting the ratios in decreasing order and storing to the cache those posting lists corresponding to the highest ratio values. Further, a method of finding an optimal allocation between two parts of a search engine cache evaluates a past query stream based on a relationship between various properties of the stream and the total size of the cache, and uses this information to determine the respective sizes of both parts of the cache.

Abstract: Systems and methods for identifying spam hosts are disclosed in which hosts known to the system and initially classified as spam or non-spam by a baseline classifier. Then for each node u in the host graph a new feature is computed. This feature is an aggregate function of the initial classifications produced by the baseline classifier for the neighbors of the node u. The set of neighbors can be defined in many different ways: in-link neighbors, out-link neighbors, bi-directional neighbors, k-hops neighbors, etc. The new feature computed above then is added to the existing set of features, and the baseline classifier is trained again, producing new predictions for each node. The results may then be used in many different ways including to filter search results based on host classifications so that spam hosts are not displayed or displayed last in a results set.

Abstract: Systems and methods for identifying spam hosts are disclosed in which hosts are known to the system and initially classified as spam or non-spam by a baseline classifier. The accuracy of the initial host classifications are then improved by propagating them using a random walk algorithm. The random walk used may be modified in order to obtain a weighted or skewed characterization of the host. The hosts may then be reclassified based on the characterization obtained from the random walk to obtain a final spam/non-spam classification. The final classification may then be used in many different ways including to filter search results based on host classifications so that spam hosts are not displayed or displayed last in a results set.

Abstract: Systems and methods for identifying spam hosts are disclosed in which hosts are known to the system and initially classified as spam or non-spam. Then the hosts are partitioned into clusters based on how each host is linked to other hosts. Each cluster is then analyzed and, depending on the number of spam and non-spam hosts it contains, the cluster may be classified as a spam cluster or a non-spam cluster. The hosts within the cluster may then be reclassified based on the cluster's classification. The results may then be used in many different ways including to filter search results based on host classifications so that spam hosts are not displayed or displayed last in a results set.

Abstract: The present invention discloses a document descriptor extraction method and system. The document descriptor extraction method and system creates a document descriptor by generalizing input sequences within a document; factoring the input sequences and generalized input sequences; and selecting a document descriptor from the input sequences, generalized sequences, and factored sequences, preferably using minimum descriptor length (MDL) principles. Novel algorithms are employed to perform the generalizing, factoring, and selecting.