Abstract: A network's evolution is characterized by graph evolution rules. A graph that represents an evolutionary network is mined to identify evolutional patterns of the network, and graph evolution rules are generated using identified evolutional patterns. The generated graph evolution rules represent the evolutional patterns of the network.

Abstract: A network's evolution is characterized by graph evolution rules. A graph, formed by merging multiple graphs representing the multiple snapshots of the network, that represents an evolutionary network is mined to identify evolutional patterns of the network. A pattern is selected from the identified patterns. Graph evolution rules are generated using identified evolutional patterns. The generated graph evolution rules represent the evolutional patterns of the network, the rules indicating that any occurrence of a child pattern of the selected pattern implies a corresponding occurrence of the selected pattern.

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: An advisor flowchart is built, which flowchart comprises a set of nodes and each node is associated with a user attribute selected from a set of user attributes in a user space, the set of attributes comprising information about users, e.g., lifestyles, interests, demographics, etc. and each node is associated with a ranking of products from a product space. The advisor flowchart may be used to make a set of recommendations available to a user, where the set of recommendations comprise one or more top-ranked products associated with the node at which the user is currently positioned. At each node, the associated user attribute is used to formulate a question that may be posed to the user. The user's answer to the question may be used to progress to another node of the advisor flowchart.

Abstract: A network's evolution is characterized by graph evolution rules. A graph, formed by merging multiple graphs representing the multiple snapshots of the network, that represents an evolutionary network is mined to identify evolutional patterns of the network. A pattern is selected from the identified patterns. Graph evolution rules are generated using identified evolutional patterns. The generated graph evolution rules represent the evolutional patterns of the network, the rules indicating that any occurrence of a child pattern of the selected pattern implies a corresponding occurrence of the selected pattern.

Abstract: A network's evolution is characterized by graph evolution rules. A graph, formed by merging multiple graphs representing the multiple snapshots of the network, that represents an evolutionary network is mined to identify evolutional patterns of the network. A pattern is selected from the identified patterns. Graph evolution rules are generated using identified evolutional patterns. The generated graph evolution rules represent the evolutional patterns of the network, the rules indicating that any occurrence of a child pattern of the selected pattern implies a corresponding occurrence of the selected pattern.

Abstract: Disclosed herein are a system, method and architecture for optimizing a manner in which queries and updates are issued to data stores servicing an application such as a social networking application. A social graph modeling a social network may be used to generate a data store request schedule that optimizes, e.g., minimizes, data store accesses, such as without limitation queries and updates to the data store.

Abstract: A matching between content items and consumers is discloses. More particularly, items and consumers are matched using a matching approach that uses capacity constraints associated with each consumer, capacity constraints associated with each item, and relationship weights, each relationship weight representing a similarity between a consumer and an item. Edges representing the relationships between consumers and items can be selected using an iterative selection that includes a matching approach that permits capacity constraints. Alternatively, edges can be selected using an iterative approach that allows a solution to be identified prior to completion of the selection processing.

Abstract: Disclosed herein are a system, method and architecture for optimizing a manner in which queries and updates are issued to data stores servicing an application such as a social networking application. A social graph modeling a social network may be used to generate a data store request schedule that optimizes, e.g., minimizes, data store accesses, such as without limitation queries and updates to the data store.

Abstract: A matching between content items and consumers is discloses. More particularly, items and consumers are matched using a matching approach that uses capacity constraints associated with each consumer, capacity constraints associated with each item, and relationship weights, each relationship weight representing a similarity between a consumer and an item. Edges representing the relationships between consumers and items can be selected using an iterative selection that includes a matching approach that permits capacity constraints. Alternatively, edges can be selected using an iterative approach that allows a solution to be identified prior to completion of the selection processing.

Abstract: Embodiments disclosed herein may relate to extracting tips from online sources and/or selecting tips for display to a user on a computing platform.

Abstract: Methods and apparatus are described for modeling sequences of events with Markov models whose states correspond to nodes in a provided taxonomy. Each state represents the events in the subtree under the corresponding node. By lumping observed events into states that correspond to internal nodes in the taxonomy, more compact models are achieved that are easier to understand and visualize, at the expense of a decrease in the data likelihood. The decision for selecting the best model is taken on the basis of two competing goals: maximizing the data likelihood, while minimizing the model complexity (i.e., the number of states).

Abstract: A network's evolution is characterized by graph evolution rules. A graph that represents an evolutionary network is mined to identify evolutional patterns of the network, and graph evolution rules are generated using identified evolutional patterns. The generated graph evolution rules represent the evolutional patterns of the network.

Abstract: A network's evolution is characterized by graph evolution rules. A graph, formed by merging multiple graphs representing the multiple snapshots of the network, that represents an evolutionary network is mined to identify evolutional patterns of the network. A pattern is selected from the identified patterns. Graph evolution rules are generated using identified evolutional patterns. The generated graph evolution rules represent the evolutional patterns of the network, the rules indicating that any occurrence of a child pattern of the selected pattern implies a corresponding occurrence of the selected pattern.

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: 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 network's evolution is characterized by graph evolution rules. A graph that represents an evolutionary network is mined to identify evolutional patterns of the network, and graph evolution rules are generated using identified evolutional patterns. The generated graph evolution rules represent the evolutional patterns of the network.

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: Methods and apparatus are described for modeling sequences of events with Markov models whose states correspond to nodes in a provided taxonomy. Each state represents the events in the subtree under the corresponding node. By lumping observed events into states that correspond to internal nodes in the taxonomy, more compact models are achieved that are easier to understand and visualize, at the expense of a decrease in the data likelihood. The decision for selecting the best model is taken on the basis of two competing goals: maximizing the data likelihood, while minimizing the model complexity (i.e., the number of states).

Abstract: A computer implemented system for search engine facility architecting and design. The system estimates the costs of power and networking based on system parameters, such as average CPU utilization, connection time, and bytes transferred over the network. Regional distribution of facilities may be evaluated to take into account the various parameters and optimize the cost and speed of the systems being designed. The parameters used in analyzing and formulating an architecture are independent of a particular indexing or query processing technique.