Abstract: The disclosed embodiments provide a system for performing A/B testing for search engine optimization (SEO). During operation, the system divides a set of web pages into a control group, an inbound treatment group, an outbound treatment group, and a full treatment group. Next, the system generates a first set of links from the outbound treatment group to the inbound treatment group and a second set of links within the full treatment group. The system then applies an A/B test to pairs of groups selected from the control group, the inbound treatment group, the outbound treatment group, and the full treatment group. Finally, the system outputs a result of the A/B test for use in assessing an effect of the first and second sets of links on search engine results associated with the set of web pages.

Abstract: Disclosed herein are compounds of formula I: and salts thereof. Also disclosed are compositions comprising compounds of formula I and methods using compounds of formula I.

Abstract: An embodiment of the disclosed technologies includes extracting, from an online connection network, digital data comprising target profile data and current profile data; where the target profile data is associated with an online submission process that has a plurality of possible outcomes and is executable via the online connection network; where the current profile data is associated with a member node of the online connection network; using an active learning process, in response to the current profile data, identifying attribute data that is in the target profile data but is not in the current profile data and is predicted to have a relationship with a positive outcome of the online submission process; outputting the attribute data for use by a downstream process or an automated digital assistant to determine a digital resource to associate with the member node through the online connection network or through an online learning system.

Abstract: A system and method for identifying trending topics in a document corpus are provided. First, multiple topics are identified, some of which topics may be filtered or removed based on co-occurrence. Then, for each remaining topic, a frequency of the topic in the document corpus is determined, one or more frequencies of the topic in one or more other document corpora are determined, a trending score of the topic is generated based on the determined frequencies. Lastly, the remaining topics are ranked based on the generated trending scores.

Abstract: In one technique, one or more search criteria associated with a first user are determined. Based on the one or more search criteria, a search of a first set of users is performed. As a result of the search, a subset of the first set of users is identified. A second set of users that have responded to messages from users in the subset is identified. Instances of attribute values of an attribute of the second set of users are aggregated to generate aggregated values, each of which corresponds to a different attribute value of the attribute values. Based on one or more of the aggregated values, content that is related to one or more attribute values that correspond to the one or more aggregated values is determined and presented to the first user.

Abstract: Techniques for delaying the transmission of a message to one or more recipients using an alert in order to provide data protection and security with respect to data included in the message are disclosed herein. In some embodiments, a computer-implemented method comprises: receiving a request to transmit a message from a computing device of a user to a recipient, the request comprising content of the message; detecting an issue with the request using at least one classifier to classify the request as having the issue; generating an alert based on the detecting of the issue; and prior to transmitting the message to a destination associated with the recipient, causing the generated alert to be displayed on the computing device of the user, the alert indicating the issue with the message.

Abstract: Methods, systems, and computer programs are presented for selecting features for a machine-learning model configured to detect anomalies in the evolution of data over time. One method includes an operation for identifying one or more key fields and value fields from the fields in a relational database. The method also includes grouping data of the value fields based on values of the one or more key fields and calculating one or more statistical values for each group of data of the value fields. The method further includes operations for monitoring an evolution of the one or more statistical values over time, and for selecting, based on the evolution of the one or more statistical values over time, features to be used by a machine-learning model to detect anomalies in content of the relational database over time. The method also includes executing the machine-learning model to detect the anomalies.

Abstract: Disclosed herein are compounds of formula I and salts thereof. Also disclosed are compositions comprising compounds of formula I and methods using compounds of formula I.

Abstract: Among other things, embodiments of the present disclosure discussed herein help identify trending topics and generate customized data feeds that present trending topics to a user based on information in the user's social network profile. In some embodiments, users may select topics of interest to the user and the system can identity and present trending articles in the selected topic to the user via the user's newsfeed.

Abstract: Disclosed herein are compounds of formula I and salts thereof. Also disclosed are compositions comprising compounds of formula I and methods using compounds of formula I.

Abstract: A spammer profile detector uses multi-stage machine learning approach, where a content-based machine learning model, a connection graph machine learning model, and a behavior-based machine learning model are used sequentially, each model generating a score indicating the likelihood that a profile is a spammer profile. The content-based machine learning model examines and evaluates information stored in a member profile. The connection graph machine learning model examines and evaluates a member's connections. The behavior-based machine learning model examines and evaluates activities of a member represented by a member profile. The score produced by the spammer profile detector can be used to determine whether the profile should be flagged as a spammer profile, whether the profile should be omitted when determining a count of the total number of active member profiles within the system, whether the profile should be restricted or removed from the system, etc.

Abstract: The disclosed embodiments provide a system for performing unified propensity modeling across product versions. During operation, the system determines features and labels related to converting to multiple versions of a product by a first set of members, wherein the features and the labels span a unified timeframe and adhere to a unified data logic. Next, the system inputs the features and the labels as training data for one or more machine learning models. The system then applies the machine learning model(s) to additional features for a second set of members to produce scores representing likelihoods of the second set of members converting to the multiple versions of the product. Finally, the system generates, based on the scores, output for targeting the second set of members with the product.

Abstract: Techniques for discovering related organizations through different types of online connections are provided. In one technique, connection data is stored that identifies, for each user in a first set of users, one or more other users with which that user has a connection. Job change data is stored that identifies, for each user of a second set of users, multiple organizations for which that user has worked or had sought an employment relationship. Based on the connection data, a number of connections between employees of a first organization and employees of a second organization is identified. Based on the job change data, a number of users that listed, in their respective online profiles, the first organization as an employer is identified. Based on the number of connections and the number of users, a determination of whether the first organization and the second organization are related is made.

Abstract: Techniques for expanding activity channels in an online network are provided. In one technique, one or more search criteria associated with a first user are determined. Based on the one or more search criteria, a search of a first set of users is performed. As a result of the search, a subset of the first set of users is identified. A second set of users that have responded to messages from users in the subset is identified. Instances of attribute values of an attribute of the second set of users are aggregated to generate aggregated values, each of which corresponds to a different attribute value of the attribute values. Based on one or more of the aggregated values, content that is related to one or more attribute values that correspond to the one or more aggregated values is determined and presented to the first user.

Abstract: The disclosed embodiments provide a system for performing A/B testing for search engine optimization (SEO). During operation, the system divides a set of web pages into a control group, an inbound treatment group, an outbound treatment group, and a full treatment group. Next, the system generates a first set of links from the outbound treatment group to the inbound treatment group and a second set of links within the full treatment group. The system then applies an A/B test to pairs of groups selected from the control group, the inbound treatment group, the outbound treatment group, and the full treatment group. Finally, the system outputs a result of the A/B test for use in assessing an effect of the first and second sets of links on search engine results associated with the set of web pages.

Abstract: Methods, apparatus, and systems to determine a niche market of items or services, the first phase of which identifies a gap between demand and supply for a set of items. Session logs may be evaluated to compare transactions involving a specific item to those of a larger group of items. The resultant information identifies areas of high demand, but with low availability. The niche market information may be provided as direct merchandising items for sellers. In one example, the method generates niche market item web pages in specific categories. Additional methods, apparatus, and systems are disclosed.

Abstract: Techniques in a search system for improving the precision and recall of search results returned for search queries including long tail queries submitted against a vertical search corpus are disclosed. The techniques include mapping a user query submitted to the system to a more representative query and executing the more representative query against the vertical search corpus. Documents identified as matching the more representative query may be returned in a search result as an answer to the user query in addition to or instead of documents identified as matching the user query. By including the documents identified as matching the more representative query in the search result, the search result may be relevant to the user than a search result that includes just documents matching the user query.

Abstract: Techniques are provided for predicting talent flow to and/or from a geographical region. In one technique, multiple entity profiles are stored and analyzed to generate training data that is labeled indicating whether a corresponding entity has moved to or moved from a region. A machine-learned prediction model is generated or trained based on the training data. Using the machine-learned prediction model, a prediction is made whether, for each entity corresponding to another entity profile, that entity will move to or move from a particular geographic region. Based on multiple predictions, a number of entities that are predicted to move to or move from the particular geographic region is determined. Talent flow data that is based on the number of entities is presented on a computer display.

Abstract: Techniques for automatically linking pages in a web site are provided. In one technique, training data for a machine-learned scoring model is generated that comprises a plurality of features related to content items. The training data comprises multiple entries, each corresponding to a different content item in a first set of content items. For each entry, a corresponding label is based on a ranking of the corresponding content item in one or more search engine results. The machine-learned scoring model is trained based on the training data. For each content item in a second set of content items, multiple attribute values associated with that content item are input into the machine-learned scoring model, which generates a result. Based on multiple results, determining, for a particular web page, a strict subset of the second set of content items to which the particular web page will include one or more links.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains validated training data containing a first set of content items and a first set of classification tags for the first set of content items. Next, the system uses the validated training data to produce a statistical model for classifying content using a set of dimensions represented by the first set of classification tags. The system then uses the statistical model to generate a second set of classification tags for a second set of content items. Finally, the system outputs one or more groupings of the second set of content items by the second set of classification tags to improve understanding of content related to the set of dimensions without requiring a user to manually analyze the second set of content items.