Abstract: Techniques for determining an editable query which, when executed, identifies and presents a set of member profiles similar to a source member profile are described. In an embodiment, a preliminary set of member profiles similar to a source member profile is identified. A set of profile features is obtained from the preliminary set of similar member profiles, and a set of relevant profile features is extracted from the set of profile features. An editable query including the set of relevant profile features is presented. In an embodiment, the set of member profiles similar to the source member profile and corresponding to the set of relevant profile features is also presented. Upon having been edited, the editable query is executable to identify and present a new set of member profiles corresponding to the edited query.

Abstract: Techniques for determining an editable query which, when executed, identifies and presents a set of member profiles similar to a source member profile are described. In an embodiment, a preliminary set of member profiles similar to a source member profile is identified. A set of profile features is obtained from the preliminary set of similar member profiles, and a set of relevant profile features is extracted from the set of profile features. An editable query including the set of relevant profile features is presented. In an embodiment, the set of member profiles similar to the source member profile and corresponding to the set of relevant profile features is also presented. Upon having been edited, the editable query is executable to identify and present a new set of member profiles corresponding to the edited query.

Abstract: The author ranking technique described herein is a technique to rank authors in social media systems along various dimensions, using a variety of statistical methods for utilizing those dimensions. More particularly, the technique ranks authors in social media systems through a combination of statistical techniques that leverage usage metrics, and social and topical graph characteristics. In various exemplary embodiments, the technique can rank author authority by the following: 1) temporal analysis of link sharing in which authority is computed based on a user's propensity to provide early links to web pages that subsequently become popular; 2) topical authority based on the author's links and content updates in specific topic areas; and 3) popularity and influence based on nodal properties of authors.

Abstract: The author ranking technique described herein is a technique to rank authors in social media systems along various dimensions, using a variety of statistical methods for utilizing those dimensions. More particularly, the technique ranks authors in social media systems through a combination of statistical techniques that leverage usage metrics, and social and topical graph characteristics. In various exemplary embodiments, the technique can rank author authority by the following: 1) temporal analysis of link sharing in which authority is computed based on a user's propensity to provide early links to web pages that subsequently become popular; 2) topical authority based on the author's links and content updates in specific topic areas; and 3) popularity and influence based on nodal properties of authors.

Abstract: Methods, systems, and computer-readable media for searching microblog entries. The microblog entries may be generated through a single microblog website or across multiple microblog sites. Upon receiving a search input, a series of microblog entries responsive to the search input may be displayed to the user. The displayed microblog entries may be the most recently generated microblog entries that are responsive to the search input. In another embodiment, the microblog entries returned are a best match to the search criteria, which may be based on a user authority score for a user that drafted a microblog entry and additional characteristics of the microblog entry.

Abstract: To determine a configuration for a database system, a plurality of queries may be sampled from a representative workload using statistical inference to compute the probability of correctly selecting one of a plurality of evaluation configurations. The probability of correctly selecting may determine which and/or how many queries to sample, and/or may be compared to a target probability threshold to determine if more queries must be sampled. The configuration from the plurality of configurations with the lowest estimated cost of executing the representative workload may be determined based on the probability of selecting correctly. Estimator variance may be reduced through a stratified sampling scheme that leverages commonality, such as an average cost of execution, between queries based on query templates. The applicability of the Central Limit Theorem may be verified and used to determine which and/or how many queries to sample.

Abstract: To determine a configuration for a database system, a plurality of queries may be sampled from a representative workload using statistical inference to compute the probability of correctly selecting one of a plurality of evaluation configurations. The probability of correctly selecting may determine which and/or how many queries to sample, and/or may be compared to a target probability threshold to determine if more queries must be sampled. The configuration from the plurality of configurations with the lowest estimated cost of executing the representative workload may be determined based on the probability of selecting correctly. Estimator variance may be reduced through a stratified sampling scheme that leverages commonality, such as an average cost of execution, between queries based on query templates. The applicability of the Central Limit Theorem may be verified and used to determine which and/or how many queries to sample.